# data[].attributes.headline
It will happen: a heart-breaking journey to motherhood through recurrent miscarriage and pregnancy loss / by Laura Buckingham

# data[].attributes.subject
It will happen: a heart-breaking journey to motherhood through recurrent miscarriage and pregnancy loss / by Laura Buckingham

# data[].attributes.body
In this candid memoir, Laura shares her isolating experiences and talks openly and honestly about how she and her husband navigated the harsh realities of their roller-coaster journey to parenthood. Written from the heart of someone with first-hand experiences, It Will Happen gives you tools and information to feel empowered and supported through the difficult times when trying to conceive.

# data[].attributes.attachment_caption
Co-authored by our very own Laura Buckingham

# data[].attributes.headline
The Worst Girl Gang Ever by Bex Gunn & Laura Buckingham

# data[].attributes.subject
The Worst Girl Gang Ever by Bex Gunn & Laura Buckingham

# data[].attributes.body
Following pregnancy loss you are entitled to grieve, and your grief is not disproportionate to your loss. This book opens the dialogue around miscarriage, without perpetuating the shame, judgement and isolation so many feel following pregnancy loss. Gain knowledge, tools and guidance to support.

# data[].attributes.body
To recieve any of the following current awareness bulletins complete our form and we will add you to the mailing list.

Register to recieve current awareness bulletins

AI in Healthcare

Assisted Dying

Education

Emergency Medicine & Critical Care

Frailty

Fundamentals of Care

Mental Health

Midwifery

Midwifery Monthly

Neonates & Paediatrics

Nursing News

Obstetrics & Gynaecology

Oncology

Orthopaedics

Ten Tasters - Medicine

# data[].attributes.headline
The Interplay of Cancer and Hypertension: Rising Mortality and Widening Disparities Across the United States (1999-2023)

# data[].attributes.subject
The Interplay of Cancer and Hypertension: Rising Mortality and Widening Disparities Across the United States (1999-2023)

# data[].attributes.attachment_link.title
The Interplay of Cancer and Hypertension: Rising Mortality and Widening Disparities Across the United States (1999–2023)

# data[].attributes.attachment_link.description
Background and Objectives: Growing evidence suggests a strong relationship between hypertension and cancer, which can increase the risk of poor prognosis. However, data regarding mortality related to cancer and hypertension are limited. Our study aims to analyze the mortality trends related to cancer and hypertension in the United States from 1999 to 2023. Materials and Methods: A retrospective observational analysis was conducted using mortality data for the adult U.S. population from 1999 to 2023, retrieved from the CDC WONDER database using death certificates. Age-adjusted mortality rates (AAMRs) were calculated, and annual percentage changes (APCs) were analyzed using JoinPoint Regression. Results: From 1999 to 2023, a total of 1,406,107 deaths related to cancer and hypertension were recorded in the United States. The AAMR increased from 12.59 in 1999 to 35.49 in 2023. Males had a higher mortality rate compared to women throughout the study period (AAMR; 30.3 vs. 20.4). Non-Hispanic (NH) Black Americans, or African Americans had the highest mortality rates, followed by NH white, Hispanic or Latino groups, and other NH groups. The highest AAMR was observed in the South, followed by the Midwest, the Northeast, and the West. Rural areas had higher mortality rates compared to urban areas. Conclusions: Cancer- and hypertension-related mortality rates have consistently increased in the United States from 1999 to 2023, particularly affecting males, NH Black Americans, the southern region, and rural areas. The trends highlight the need for targeted prevention, including early screening, lifestyle changes, and treatment adherence.

# data[].attributes.headline
MRI in the Diagnosis of Transient Global Amnesia: A Case Series and Review of Current Evidence

# data[].attributes.subject
MRI in the Diagnosis of Transient Global Amnesia: A Case Series and Review of Current Evidence

# data[].attributes.body
Amnesia: A Case Series and Review of Current

Evidence

# data[].attributes.headline
Effectiveness of TissuGlu in Reducing Seroma Formation and Postoperative Recovery in Mastectomy Patients: A Systematic Review and Meta-Analysis of Comparative Studies

# data[].attributes.subject
Effectiveness of TissuGlu in Reducing Seroma Formation and Postoperative Recovery in Mastectomy Patients: A Systematic Review and Meta-Analysis of Comparative Studies

# data[].attributes.headline
A rare example of humoral-related hypercalcaemia in pregnancy secondary to a uterine fibroid: a case report

# data[].attributes.subject
A rare example of humoral-related hypercalcaemia in pregnancy secondary to a uterine fibroid: a case report

# data[].attributes.attachment_link.title
A rare example of humoral-related hypercalcaemia in pregnancy secondary to a uterine fibroid: a case report - Chloe Gilkinson, Hannah Beresford, Carol Postlethwaite, Catherine Nelson-Piercy, Karan Sampat, 2025

# data[].attributes.attachment_link.description
Whilst uncommon in pregnancy, hypercalcaemia can lead to significant maternal and fetal morbidity. An important complication of hypercalcaemia is uncontrolled h…

# data[].attributes.headline
Hospital Volume as a Determinant of Outcomes After Partial Nephrectomy: A Systematic Review by the European Association of Urology Renal Cell Carcinoma Guidelines Panel

# data[].attributes.subject
Hospital Volume as a Determinant of Outcomes After Partial Nephrectomy: A Systematic Review by the European Association of Urology Renal Cell Carcinoma Guidelines Panel

# data[].attributes.attachment_link.title
Hospital Volume as a Determinant of Outcomes After Partial Nephrectomy: A Systematic Review by the European Association of Urology Renal Cell Carcinoma Guidelines Panel

# data[].attributes.attachment_link.description
Higher hospital volume is associated with better partial nephrectomy outcomes in renal
cell carcinoma. Volume recommendations issued by professional associations are largely
absent in Europe, and where present, differ considerably between countries.

# data[].attributes.headline
A Review of Access to Health Justice in Nigeria in the Covid-19 Era

# data[].attributes.subject
A Review of Access to Health Justice in Nigeria in the Covid-19 Era

# data[].attributes.headline
Imaging and surveillance in sporadic renal angiomyolipoma: how and when to monitor effectively

# data[].attributes.subject
Imaging and surveillance in sporadic renal angiomyolipoma: how and when to monitor effectively

# data[].attributes.body
renal angiomyolipoma: how and when to

monitor effectively

# data[].attributes.headline
Spontaneous subgaleal haematoma with severe headache in two children during acute painful sickle cell crisis

# data[].attributes.subject
Spontaneous subgaleal haematoma with severe headache in two children during acute painful sickle cell crisis

# data[].attributes.attachment_link.readable_text
1. Williams TN, Weatherall DJ. World distribution, population genetics, and health burden of the hemoglobinopathies. Cold Spring Harb Perspect Med. 2012 Sep 1;2(9):a011692‐a101169

2. Komarla R, Soares BP, Chern JJ, Milla SS. Spontaneous epidural hematoma secondary to bone infarction in sickle cell anaemia: case report. J Neurosurg Pediatr. 2018;22:18-21. doi:10.3171/2018.1.peds17407.

3. Arends S, Coebergh JA, Kerkhoffs JL, van Gils A, Koppen H. Severe unilateral headache caused by skull bone infarction with epidural haematoma in a patient with sickle cell disease. Cephalalgia. 2011 Sep;31(12):1325-8. doi: 10.1177/0333102411414441. Epub 2011 Jul 29. PMID: 21803935.

4. Page C, Gardner K, Height S, Rees DC, Hampton T, Thein SL. Nontraumatic extradural hematoma in sickle cell anemia: a rare neurological complication not to be missed. Am J Hematol. 2014 Feb;89(2):225-7. doi: 10.1002/ajh.23579. Epub 2013 Sep 30. PMID: 24038013.

5. Alqurashi MM, Raslan OM, Gmati GE. Spontaneous Subgaleal Hematoma in a Sickle Cell Disease Patient: A Case Report. J Med Cases. 2020 Feb;11(2):46-48. doi: 10.14740/jmc3433. Epub 2020 Feb 28. PMID: 34434360; PMCID: PMC8383627.

6. National Institute for Health and Care Excellence. Sickle cell disease: managing acute painful episodes in hospital (CG143) [Internet]. 2012 [cited 2024 May 18]. Available from: https://www.nice.org.uk/guidance/cg143/chapter/Recommendations

7. Gonçalves JS, Tribovane D, Pires M, Lopes RS, de Oliveira MRI, Inacio-Conceição C, et al. Cranial Masses in Sickle Cell Disease. J Pediatr. 2022 Apr;243:228-30.

8. Joy J, Vasnaik MA, Bhat V, Anandram S, George A. Spontaneous Epidural Hematoma in Sickle Cell Crisis: A Case Report. Cureus. 2022 Apr 26;14(4):e24492. doi: 10.7759/cureus.24492. PMID: 35651401; PMCID: PMC9134707.

9. Mishra SS, Senapati SB, Gouda AK, Behera SK, Patnaik A. Spontaneous extradural and subgaleal hematoma: A rare neurosurgical crisis of sickle cell disease. Asian J Neurosurg. 2017;12(1):47-50.

10. Kavanagh PL, Sprinz PG, Vinci SR, Bauchner H, Wang CJ. Management of children with sickle cell disease: a comprehensive review of the literature. Pediatrics. 2011 Aug;128(3):e586-93. doi: 10.1542/peds.2010-3253. PMID: 21873549.

11. Foula MS, Hassan A, AlQurashi A, Alsaihati A, Sharroufna M. Spontaneous subgaleal hematoma in a patient with sickle cell disease: A case report and literature review. Clin Case Rep. 2019 Oct 9;7(11):2220-2224. doi: 10.1002/ccr3.2435. PMID: 31788283; PMCID: PMC6878059.

12. DeBaun MR, Kirkham FJ. Central nervous system complications and management in sickle cell disease. Blood. 2016 Mar 17;127(7):829-38. doi: 10.1182/blood-2015-09-618579. PMID: 26637701.

# data[].attributes.attachment_link.description
Sickle cell disease is an inherited disorder of haemoglobin formation, predominantly affecting individuals of African, Indian, or Mediterranean descent. Acute painful episodes frequently occur in these patients due to the blockage of small blood vessels by sickled cells, leading to tissue infarction.

# data[].attributes.headline
THE SHOULDER TO CENTRE OF ROTATION OF STEM DISTANCE: A NOVEL TECHNIQUE TO REDUCE LEG LENGTH DISCREPANCY IN TOTAL HIP ARTHROPLASTY - The British Hip Society (BHS) Meeting 2025, Harrogate, England, 5–7 March 2025

# data[].attributes.subject
THE SHOULDER TO CENTRE OF ROTATION OF STEM DISTANCE: A NOVEL TECHNIQUE TO REDUCE LEG LENGTH DISCREPANCY IN TOTAL HIP ARTHROPLASTY - The British Hip Society (BHS) Meeting 2025, Harrogate, England, 5–7 March 2025

# data[].attributes.attachment_link.readable_text
Abstract

Limb length discrepancy (LLD) is the commonest cause of patient dissatisfaction and litigation after total hip replacement (THR). We present a new technique using the shoulder to centre of rotation of stem distance (SCRD) to reduce LLD.

SCRD was calculated for the most common stems in the NJR. All patients who underwent THR only for primary osteoarthritis between June 2023 and 2024 were included in this prospective study. THR for other indications was excluded. Depth of insertion of the stem was determined by SCRD of the stems used at our unit and varus/valgus/neutral position of the native neck of the operative or opposite side. Post-operative radiographs were analysed for LLD using the inter-teardrop and inter-lesser trochanter line by 3 independent observers and intra and inter-observer variability was analysed using SPSS version 29.0(IBM).

50 patients with a mean age of 70 years (57 to 92) were included. The mean LLD 2.5±1.2mm. The intra-observer coefficient was very good for rater 1,0.78 (0.448 - 0.900); excellent for raters 2 & 3, 0.962 (0.930 to 0.980) and 0.881 (0.777 to 0.937) respectively(p<0.001). The inter-rater reliability was excellent 0.835 (0.723 to 0.9) p<0.001.

SCRD is an excellent technique to reduce LLD in THR. It can be used in the absence of templating software and had good intra and inter-observer reliability.

# data[].attributes.attachment_link.title
THE SHOULDER TO CENTRE OF ROTATION OF STEM DISTANCE: A NOVEL TECHNIQUE TO REDUCE LEG LENGTH DISCREPANCY IN TOTAL HIP ARTHROPLASTY

# data[].attributes.attachment_link.description
THE SHOULDER TO CENTRE OF ROTATION OF STEM DISTANCE: A NOVEL TECHNIQUE TO REDUCE LEG LENGTH DISCREPANCY IN TOTAL HIP ARTHROPLASTY

# data[].attributes.headline
TRANSFER: ThReatened preterm birth, assessment of the need for in-utero tranSFER between 22 + 0–23 + 6 weeks’ gestation, a multicentre prospective service evaluation across the United Kingdom

# data[].attributes.subject
TRANSFER: ThReatened preterm birth, assessment of the need for in-utero tranSFER between 22 + 0–23 + 6 weeks’ gestation, a multicentre prospective service evaluation across the United Kingdom

# data[].attributes.headline
Factors influencing UK arthroplasty surgeons' decision-making between total and medial unicompartmental knee surgery: A vignette-based behavioural experiment

# data[].attributes.subject
Factors influencing UK arthroplasty surgeons' decision-making between total and medial unicompartmental knee surgery: A vignette-based behavioural experiment

# data[].attributes.attachment_link.title
Factors influencing UK arthroplasty surgeons’ decision-making between total and medial unicompartmental knee surgery: A vignette-based behavioural experiment - PubMed

# data[].attributes.headline
Thyroid eye disease in primary hypothyroidism- a rare manifestation

# data[].attributes.subject
Thyroid eye disease in primary hypothyroidism- a rare manifestation

# data[].attributes.attachment_link.title
Thyroid eye disease in primary hypothyroidism- a rare manifestation | SFEBES2025 | Society for Endocrinology BES 2025 | Endocrine Abstracts

# data[].attributes.attachment_link.description
Introduction: Thyroid eye disease occurs in around one quarter of patients with Graves’ hyperthyroidism. However, it is rarely associated with primary hypothyroidism. We describe a case of a patient with thyroid eye disease secondary to primary hypothyroidism.

# data[].attributes.attachment_link.title
A case of subclinical acromegaly | SFEBES2025 | Society for Endocrinology BES 2025 | Endocrine Abstracts

# data[].attributes.attachment_link.description
Acromegaly is a rare chronic disease due to sustained and unregulated hypersecretion of growth hormone that develops insidiously and progresses slowly. It may result in a variety of cardiovascular, respiratory, endocrine, metabolic, musculoskeletal, and neoplastic comorbidities. In more than 99% of cases this is due to a benign pituitary growth hormone secreting adenoma. Infrequently acromegaly occurs as a result of ectopic secretion of growth hormone releasing hormone from a peripheral neuroendocrine tumour. 5% of cases are associated with familial syndromes. It can remain undiagnosed for about 10 years with only 50% of patients with somatotroph adenomas revealing distinct phenotypic changes, whereas the other 50% are mostly asymptomatic. We present a case of a 34- year- old female who presented with chronic migraines. She had an MRI head that showed a left sided pituitary incidentaloma measuring 14 x5 x5mm. On endocrinology review, patient did not report any symptoms and there were no clinical manifestations of any hormone excess. Anterior pituitary profile showed a raised IGF-1(88.5 nmol/l) but the rest was normal. OGTT with serial growth hormone measurements also showed unsuppressed GH. This case was discussed in the pituitary MDT and it was decided that patient should have surgery, although there was no current clinical manifestation, but in view of insidious onset and impending manifestations. Transsphenoidal hypophysectomy was done in August 2024. Histology showed pit-1 strongly positive and GH present with 40% positivity, Ki67 3-4% in keeping with a somatotroph adenoma. Post operatively the headaches resolved, the IGF-1 normalised and OGTT showed suppressed growth hormone, and the AIP gene testing result is awaited.

# data[].attributes.headline
Medical career transparency in the digital age, a British perspective

# data[].attributes.subject
Medical career transparency in the digital age, a British perspective

# data[].attributes.attachment_link.title
Medical career transparency in the digital age, a British perspective - Serena Ramjee, Kwaku Duah-Asante, 2025

# data[].attributes.attachment_link.description
View all access and purchase options for this article.

# data[].attributes.headline
Tingling, Numbness, and Underlying Malignancy: A Case Report of Glioblastoma Multiforme

# data[].attributes.subject
Tingling, Numbness, and Underlying Malignancy: A Case Report of Glioblastoma Multiforme

# data[].attributes.attachment_link.title
Tingling, Numbness, and Underlying Malignancy: A Case Report of Glioblastoma Multiforme

# data[].attributes.attachment_link.description
Glioblastoma multiforme (GBM) is a World Health Organisation (WHO) grade IV glioma originating from astrocytes. It is the most common malignant primary tumour of the brain and central nervous system (CNS) and is associated with fast progression and violent local spread, with a median overall survival of approximately 15 months after diagnosis. Due to its late and varied presentation, it is often diagnosed only after it has grown considerably. The symptomatology can vary from the individual being completely asymptomatic to mild sensory or sensorimotor symptoms. The symptoms usually arise due to compression of the fibres rather than pressure on vital structures. We discuss a case of a 72-year-old male who presented with complaints of tingling in the left upper limb for one day, improving spontaneously. A noncontrast CT head was nondiagnostic, and an MRI reported a likely metastatic lesion, and further imaging was advised. A detailed history was taken from an oncology point of view but the patient denied any weight loss, fever, recent travel, and family history of cancers. The scans were discussed at a neuroradiology multidisciplinary team (MDT) discussion an MRI with contrast was planned. After a thorough discussion and further review by neuroradiology consultants, the patient was diagnosed with a grade IV glioblastoma - a primary tumour of the brain - which was confirmed by a biopsy and immunohistochemistry. He was treated with two cycles of radiotherapy initially, followed by chemotherapy. Unfortunately, he died eight months after the start of the treatment due to a massive pulmonary embolism, complicated by nosocomial infection. This report highlights the importance of early diagnosis and treatment for patients with glioma. It also sheds light on the symptomatology and difficulties faced in the diagnosis of gliomas. Treating physicians should adopt an MDT approach in such cases and discuss the various possibilities and differentials.

# data[].attributes.headline
Trends of acute myocardial infarction-related deaths in US patients from 1999 to 2020

# data[].attributes.subject
Trends of acute myocardial infarction-related deaths in US patients from 1999 to 2020

# data[].attributes.body
US patients from 1999 to 2020

# data[].attributes.attachment_link.title
Trends of acute myocardial infarction-related deaths in US patients from 1999 to 2020

# data[].attributes.attachment_link.description
Introduction: The objective of this study was to analyze the temporal trends and demographic/geographical disparities in acute myocardial infarction (AMI)-related mortality among individuals aged 15 and older across the United Sates (US). Material and methods: We evaluated death records from…

# data[].attributes.headline
Neuroendocrine tumour of the urinary bladder

# data[].attributes.subject
Neuroendocrine tumour of the urinary bladder

# data[].attributes.attachment_link.title
Neuroendocrine tumour of the urinary bladder

# data[].attributes.attachment_link.description
We report a rare case of urinary bladder neuroendocrine tumour (NET) in a young, non-smoking man. He had no known risk factors and no comorbidities. After being diagnosed with a bladder tumour while being investigated for flank pain and poor renal function, he was treated with transurethral resection of the bladder tumour and deroofing of ureters bilaterally. Characteristic histological features were identified for NETs. After a thorough staging workup by CT of the thorax, abdomen and pelvis, MRI of the liver and DOTATATE positron emission tomography-CT, no other lesion or metastasis was identified. Primary NETs in the genitourinary tract are rare, comprising approximately 1–2% of genitourinary malignancies. Timely staging and histological diagnosis are the keystones of initial management. Awareness of potential diagnostic pitfalls is essential to ensure the accurate and timely diagnosis of vesical NETs, given their significant impact on management strategies and patient prognosis.

# data[].attributes.headline
Determinants and progression of stigma in amyotrophic lateral sclerosis/motor neuron disease

# data[].attributes.subject
Determinants and progression of stigma in amyotrophic lateral sclerosis/motor neuron disease

# data[].attributes.attachment_link.title
Determinants and progression of stigma in amyotrophic lateral sclerosis/motor neuron disease

# data[].attributes.attachment_link.description
Objective: Stigma in amyotrophic lateral sclerosis/motor neurone disease (ALS/MND) may be felt or enacted; felt stigma covers feeling devalued by the illness, whereas enacted stigma refers to being…

# data[].attributes.headline
Assessing the landscape and charting paths: UK neurology trainees’ opinions on neuroinflammation subspecialty

# data[].attributes.subject
Assessing the landscape and charting paths: UK neurology trainees’ opinions on neuroinflammation subspecialty

# data[].attributes.attachment_link.provider_name
Multiple Sclerosis and Related Disorders

# data[].attributes.attachment_link.title
Assessing the landscape and charting paths: UK neurology trainees’ opinions on neuroinflammation subspecialty

# data[].attributes.attachment_link.description
Therapeutics of neuroinflammatory disorders including multiple sclerosis is one of
the fastest growing areas in neurology. However, pressures on higher specialty training
in neurology together with an expanding curriculum have led to challenges in adequately
preparing trainees for a subspecialist career. In this study we set out to understand
current perceptions and barriers to training in neuroinflammatory disorders among
neurology trainees in the UK. A structured questionnaire was used to assess trainees’
perspectives on training opportunities and career aspirations.

# data[].attributes.headline
Complications of electrosurgery: mechanisms and prevention strategies

# data[].attributes.subject
Complications of electrosurgery: mechanisms and prevention strategies

# data[].attributes.attachment_link.title
Complications of electrosurgery: mechanisms and prevention strategies - Facts, views & vision in ObGyn

# data[].attributes.attachment_link.description
S.M. El-Sayed1, E. Saridogan2, M.M. El-Sayed3

# data[].attributes.headline
An examination of service user satisfaction in forensic mental health settings

# data[].attributes.subject
An examination of service user satisfaction in forensic mental health settings

# data[].attributes.attachment_link.title
An examination of service user satisfaction in forensic mental health settings - Al Adiya Khan, Victoria Stirrup, Douglas MacInnes, 2025

# data[].attributes.attachment_link.description
High levels of service user satisfaction are viewed as a reliable indicator of a service providing good care and treatment. There has been limited research look…

# data[].attributes.headline
How Does the Pre-Registration Midwifery Programme Prepare the Newly Qualified Midwives for Their Post-Registration Perinatal Mental Health Role? A Mixed Methods Study

# data[].attributes.subject
How Does the Pre-Registration Midwifery Programme Prepare the Newly Qualified Midwives for Their Post-Registration Perinatal Mental Health Role? A Mixed Methods Study

# data[].attributes.attachment_link.title
How Does the Pre-Registration Midwifery Programme Prepare the Newly Qualified Midwives for Their Post-Registration Perinatal Mental Health Role? A Mixed Methods Study

# data[].attributes.attachment_link.description
Objective: In the United Kingdom (UK) and most countries worldwide, midwives are professionally required to undertake an initial perinatal mental health (PMH) risk assessment at every maternity contact. However, studies have found that midwives feel that they are not well-equipped to provide effective care for women with PMH needs. This study explores how the newly qualified midwives (NQMs) are prepared through pre-registration midwifery education and placements to have sufficient confidence in their knowledge, attitude, skills, and habits (KASH) for their post-registration PMH role. Methods: This explanatory sequential mixed methods study collected survey data from two independent groups: NQMs (n = 50), who qualified from 10 UK universities, and senior specialist midwives (SSMs) (n = 32). Descriptive and inferential responses were analysed using SPSS. Statistical differences between the ranged Likert scale responses of the NQMs and SSMs were analysed using the Mann-Whitney U test. The p-value of <0.05 was considered statistically significant. The semi-structured interview phase comprised of NQMs (n = 12) and SSMs (n = 8). The qualitative data were thematically analysed using NVivo. Results: The pre-registration midwifery programme significantly prepared the NQMs to have sufficient confidence in their knowledge of the related PMH role, multidisciplinary team (MDT) role, and available services (p < 0.05) and good attitude towards women with varying PMH conditions (p < 0.0005). The NQMs had sufficient confidence in their skills in using the validated tool for PMH assessment, to build rapport to facilitate disclosure, and recognise deteriorating PMH (p < 0.01). They had regular habits of discussing PMH well-being at booking and made prompt referrals (p < 0.05). The NQMs were not prepared to have sufficient knowledge of PMH medications, perinatal suicide prevention, and the impact of maternal mental health on partners (p < 0.01) including children (p < 0.05); skills in managing PMH emergencies (p < 0.05), and to regularly discuss suicidal thoughts (p < 0.01), issues of self-harm, and debrief women following pregnancy or neonatal losses and traumatic births (p < 0.05). Some aspects were either confirmed or contradicted at the interviews. Conclusions and recommendations: The pre-registration midwifery programme prepares the NQMs to some extent for their post-registration PMH role. Perceived areas for improvement suggest implications for the development of educational, practice, policy, and preceptorship to facilitate the NQMs’ sustainable confidence in their KASH.

# data[].attributes.headline
Fusobacterium nucleatum-Induced Empyema Masquerading as Lung Cancer: A Diagnostic Challenge

# data[].attributes.subject
Fusobacterium nucleatum-Induced Empyema Masquerading as Lung Cancer: A Diagnostic Challenge

# data[].attributes.attachment_link.title
Fusobacterium nucleatum-Induced Empyema Masquerading as Lung Cancer: A Diagnostic Challenge

# data[].attributes.attachment_link.description
A 73-year-old man, an ex-smoker with a history of asbestos exposure and hypertension, presented with progressive shortness of breath, weight loss, loss of appetite, and fatigue. He was referred by a general practitioner for evaluation of a round lesion in the right lung. Chest computed tomography (CT) revealed a pleural-based mass and small right-sided pleural effusion that was not amenable to aspiration. Routine blood investigations revealed elevated levels of the inflammatory markers. He was discharged with a course of oral antibiotics, levofloxacin, and scheduled for a two-week follow-up on the lung cancer pathway. The patient returned with worsening shortness of breath and enlarged pleural effusion. Ultrasound-guided diagnostic aspiration yielded purulent fluid, with cultures identifying Fusobacterium nucleatum. Cytological examination of the pleural fluid yielded negative results for malignant cells. Further investigations ruled out septic thrombophlebitis of the internal jugular vein (Lemierre syndrome) and septic mediastinitis. After excluding all other possible infection sites and conducting an oral examination, the pleural infection was attributed to periodontal disease. Empyema was effectively managed with antibiotics and drainage. However, empyema resulted in a visceral pleural rind, leading to an unexpandable lung. Surgical intervention was not pursued because of the patient’s comorbidities and clinical and biochemical resolution of the infection. This case highlights the importance of considering rare pathogens, such as Fusobacterium nucleatum, in pleural infections, particularly when linked to oral sources.

# data[].attributes.headline
The National Joint Registry Data Quality Audit of elbow arthroplasty

# data[].attributes.subject
The National Joint Registry Data Quality Audit of elbow arthroplasty

# data[].attributes.attachment_link.title
The National Joint Registry Data Quality Audit of elbow arthroplasty | Bone & Joint

# data[].attributes.attachment_link.description
The National Joint Registry Data Quality Audit of elbow arthroplasty

# data[].attributes.headline
Atypical Motor-Predominant Presentation of Subacute Combined Degeneration of Spinal Cord Due to Vitamin B12 Deficiency: A Case Report of Stroke Mimicry in the Absence of Classic Symptoms

# data[].attributes.subject
Atypical Motor-Predominant Presentation of Subacute Combined Degeneration of Spinal Cord Due to Vitamin B12 Deficiency: A Case Report of Stroke Mimicry in the Absence of Classic Symptoms

# data[].attributes.attachment_link.title
Atypical Motor-Predominant Presentation of Subacute Combined Degeneration of Spinal Cord Due to Vitamin B12 Deficiency: A Case Report of Stroke Mimicry in the Absence of Classic Symptoms

# data[].attributes.attachment_link.description
Vitamin B12 deficiency is a prevalent condition that can lead to serious neurological disorders, including subacute combined degeneration (SCD) of the spinal cord, which can result in lasting damage if not promptly treated. This report discusses a unique case of a 53-year-old female patient who presented with a one-week history of gait instability and falls, ultimately diagnosed with SCD due to severe vitamin B12 deficiency. Notably, the patient exhibited an atypical presentation, lacking classic symptoms such as paraesthesia and hematologic abnormalities, which often accompany B12 deficiency. Clinical evaluation revealed no previous neurological deficits or hematological issues, suggesting an acute decline in B12 levels. Neuroimaging, particularly MRI of the spine, showed demyelination affecting the dorsal columns and corticospinal tracts, consistent with SCD while excluding ischemic causes. Laboratory tests confirmed low serum B12 levels, supporting the diagnosis. This case underscores the necessity for clinicians to maintain a high index of suspicion for vitamin B12 deficiency in patients presenting with unexplained neurological symptoms. Early intervention is crucial; in this case, immediate treatment with intramuscular B12 led to significant recovery in gait stability and neurological function. The findings highlight the importance of thorough assessments and ongoing education about the diverse presentations of B12 deficiency, especially in populations at risk, such as the elderly and those with malabsorption issues. Awareness of the neurological consequences of B12 deficiency is essential for effective management and improved patient outcomes.

# data[].attributes.headline
Complications Following Shoulder Arthroplasty: A Review of the Recent Literature

# data[].attributes.subject
Complications Following Shoulder Arthroplasty: A Review of the Recent Literature

# data[].attributes.attachment_link.provider_name
Journal of Clinical Orthopaedics & Trauma

# data[].attributes.attachment_link.title
Complications Following Shoulder Arthroplasty: A Review of the Recent Literature

# data[].attributes.attachment_link.description
Glenohumeral joint arthroplasty is a safe and effective treatment with osteoarthritis
being the most common indication. The incidence of shoulder arthroplasty has increased
over twofold in the last ten years (1) but increasing reoperation rates are also noted
(2). Revision surgery is associated with higher complication rates and poorer patient
outcomes (2).

# data[].attributes.headline
Comprehensive consent in urology using decision aids, leaflets, videos and newer technologies: empowering patient choice and shared decision-making

# data[].attributes.subject
Comprehensive consent in urology using decision aids, leaflets, videos and newer technologies: empowering patient choice and shared decision-making

# data[].attributes.body
decision aids, leaflets, videos and newer

technologies: empowering patient choice

and shared decision-making

# data[].attributes.headline
National Dermatological Surgery Sustainability Survey: An Evaluation of Healthcare Professional Beliefs and Practices

# data[].attributes.subject
National Dermatological Surgery Sustainability Survey: An Evaluation of Healthcare Professional Beliefs and Practices

# data[].attributes.headline
A Storm of Polyserositis: Unravelling Multisystem Effusions in Hypereosinophilic Syndrome

# data[].attributes.subject
A Storm of Polyserositis: Unravelling Multisystem Effusions in Hypereosinophilic Syndrome

# data[].attributes.attachment_link.title
A Storm of Polyserositis: Unravelling Multisystem Effusions in Hypereosinophilic Syndrome

# data[].attributes.attachment_link.description
Idiopathic hypereosinophilic syndrome (i-HES) is a rare disorder characterized by persistent eosinophilia and organ involvement, without an identifiable secondary cause. This case report describes a 42-year-old man with no significant medical history, who initially presented with symptoms resembling community-acquired pneumonia, including fever, shortness of breath, and pleuritic chest pain. Despite antibiotic treatment, his condition rapidly progressed to polyserositis, characterized by bilateral pleural effusions, pericardial tamponade, and ascites. Extensive diagnostic evaluation excluded the secondary causes of hypereosinophilia, leading to a final diagnosis of i-HES. Prompt initiation of high-dose corticosteroids resulted in dramatic clinical improvement, with resolution of the fever, pleural effusion, and pericardial effusion. This case highlights the diagnostic challenges associated with the atypical presentations of i-HES and emphasizes the importance of early recognition, comprehensive evaluation, and appropriate corticosteroid therapy. It also raises awareness of the potential for i-HES to present with life-threatening complications, underscoring the need for multidisciplinary management.

# data[].attributes.attachment_link.title
When I say … neurodiversity paradigm - PubMed

# data[].attributes.headline
Iatrogenic Type A Aortic Dissection Following Percutaneous Coronary Intervention

# data[].attributes.subject
Iatrogenic Type A Aortic Dissection Following Percutaneous Coronary Intervention

# data[].attributes.body
Percutaneous Coronary Intervention

# data[].attributes.headline
Carbon footprinting and sustainability impact assessment in urological surgical practice - A systematic review

# data[].attributes.subject
Carbon footprinting and sustainability impact assessment in urological surgical practice - A systematic review

# data[].attributes.attachment_link.readable_text
The .gov means it's official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you're on a federal government site.

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

doi: 10.1177/00369330241280206.

Affiliations

¹ Department Of Urology, Cardiff, and Vale University Health Board, Cardiff, UK.

² Department of Urology, Dartford, and Gravesham NHS Trust, Dartford, UK.

³ Department of Urology, Royal Glamorgan Hospital, Llantrisant, Rhondda Cynon Taff, UK.

⁴ Pro Vice Chancellor Research and Innovation, University of South Wales, Pontypridd, Wales, UK.

⁵ School of Medicine, Centre for Medical Engineering and Technology, University of Dundee, Dundee, UK.

doi: 10.1177/00369330241280206.

Affiliations

¹ Department Of Urology, Cardiff, and Vale University Health Board, Cardiff, UK.

² Department of Urology, Dartford, and Gravesham NHS Trust, Dartford, UK.

³ Department of Urology, Royal Glamorgan Hospital, Llantrisant, Rhondda Cynon Taff, UK.

⁴ Pro Vice Chancellor Research and Innovation, University of South Wales, Pontypridd, Wales, UK.

⁵ School of Medicine, Centre for Medical Engineering and Technology, University of Dundee, Dundee, UK.

Abstract

Objectives: To systematically synthesize existing reported literature calculating the carbon footprint (CFP) of urological surgical practice and identify opportunities for improving the environmental impact of urology surgical practice.

Methods: A systematic review was performed following PRISMA guidelines. The Cochrane, Embase, Ovid MEDLINE, and PubMed were searched between 1971 and 2023, with inclusion and exclusion criteria. The outcome measures were mapped across the included studies including assessment of risk of bias.

Results: A total of 345 studies with titles were identified from an initial search, however only 5 were included. Three studies compared singleuse with reusable cystoscopes concluded that single-use cystoscopes are non-inferior to reusable cystoscopes environmentally due to the carbon footprint associated with decontamination and repackaging. Similarly, in a single study, the CFP of single-use and reusable ureteroscopes is comparable. Lastly, a single study concluded that robotics-assisted surgery in prostate cancer may be a better option than other approaches in terms of environmental sustainability.

Conclusions: In conclusion, although minimally invasive (including robotic approaches) and endoscopic surgeries offer significant opportunities to improve healthcare we do need to consider the environmental impact. However, there is a paucity of good-quality literature to guide urological surgical practice to reduce the CFP and improve sustainability.

Keywords: Carbon footprinting; sustainability; urological surgery.

PubMed Disclaimer

Conflict of interest statement

Declaration of conflicting interestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Similar articles

Carbon Footprint in Flexible Ureteroscopy: A Comparative Study on the Environmental Impact of Reusable and Single-Use Ureteroscopes.

Davis NF, McGrath S, Quinlan M, Jack G, Lawrentschuk N, Bolton DM. Davis NF, et al. J Endourol. 2018 Mar;32(3):214-217. doi: 10.1089/end.2018.0001. Epub 2018 Feb 21. J Endourol. 2018. PMID: 29373918

The Carbon Footprint of Surgical Operations: A Systematic Review.

Rizan C, Steinbach I, Nicholson R, Lillywhite R, Reed M, Bhutta MF. Rizan C, et al. Ann Surg. 2020 Dec;272(6):986-995. doi: 10.1097/SLA.0000000000003951. Ann Surg. 2020. PMID: 32516230

Perspectives on technology: to use or to reuse, that is the endoscopic question-a systematic review of single-use endoscopes.

Anderson S, Patterson K, Skolarikos A, Somani B, Bolton DM, Davis NF. Anderson S, et al. BJU Int. 2024 Jan;133(1):14-24. doi: 10.1111/bju.16206. Epub 2023 Nov 8. BJU Int. 2024. PMID: 37838621 Review.

Uncovering the Evidence for Sustainability in Urology: A Scoping Review.

Abdulrasheed H, Adenipekun A, Elsayed W, Mohsin MS, Madarshahian D, Almedej H, Osman B. Abdulrasheed H, et al. Urol Res Pract. 2024 Oct 21;50(3):160-166. doi: 10.5152/tud.2024.24093. Urol Res Pract. 2024. PMID: 39498946 Free PMC article. Review.

# data[].attributes.attachment_link.keywords[]
national center for biotechnology information

# data[].attributes.attachment_link.title
Carbon footprinting and sustainability impact assessment in urological surgical practice - A systematic review - PubMed

# data[].attributes.attachment_link.description
In conclusion, although minimally invasive (including robotic approaches) and endoscopic surgeries offer significant opportunities to improve healthcare we do need to consider the environmental impact. However, there is a paucity of good-quality literature to guide urological surgical practice to re ...

# data[].attributes.headline
Gas Embolism Complicating Endoscopic Retrograde Cholangiopancreaticography: Case Report of a Complex Condition

# data[].attributes.subject
Gas Embolism Complicating Endoscopic Retrograde Cholangiopancreaticography: Case Report of a Complex Condition

# data[].attributes.attachment_link.title
Gas Embolism Complicating Endoscopic Retrograde Cholangiopancreaticography: Case Report of a Complex Condition

# data[].attributes.attachment_link.description
This case report explores the complex clinical trajectory of a 72-year-old female with a history of hypertension, iron-deficiency anaemia, and vertigo, who underwent an endoscopic retrograde cholangiopancreaticography (ERCP) procedure for common bile duct (CBD) stone removal. After an uneventful laparoscopic cholecystectomy, she continued to experience abdominal pain and icterus.

# data[].attributes.headline
Using disease-modifying treatments in multiple sclerosis: Association of British Neurologists (ABN) 2024 guidance

# data[].attributes.subject
Using disease-modifying treatments in multiple sclerosis: Association of British Neurologists (ABN) 2024 guidance

# data[].attributes.attachment_link.title
Using disease-modifying treatments in multiple sclerosis: Association of British Neurologists (ABN) 2024 guidance

# data[].attributes.attachment_link.description
The Association of British Neurologists last published guidelines on disease-modifying treatment (DMT) in multiple sclerosis (MS) in 2015. Since then, additional DMTs have been licensed and approved for prescribing within the National Health Service for relapsing-remitting MS, early primary progressive MS and active secondary progressive MS. This updated guidance provides a consensus-based approach to using DMTs. We provide recommendations for eligibility, starting, monitoring, switching and stopping of DMTs; pregnancy; equitable access to DMT; autologous haemopoietic stem-cell transplantation; and use of generics. We highlight best practice where it exists and discuss future priorities. No data are available.

# data[].attributes.headline
A case of SLE presenting with acute haemorrhagic longitudinally extensive transverse myelitis

# data[].attributes.subject
A case of SLE presenting with acute haemorrhagic longitudinally extensive transverse myelitis

# data[].attributes.attachment_link.provider_name
Journal of Neurology, Neurosurgery & Psychiatry

# data[].attributes.attachment_link.authors[].name
Zieda Anete, Lichtblau Nicole, Doshi Anisha, Kumar GuruDarent Valley Hospital

# data[].attributes.attachment_link.title
A case of SLE presenting with acute haemorrhagic longitudinally extensive transverse myelitis

# data[].attributes.attachment_link.description
A 54-year-old Ghanaian woman with a history of chronic back pain and sciatica presented with acute severe lower radicular pain followed by flaccid areflexic paraplegia, T9 sensory level and urinary retention. Weakness reached nadir within 3 hours of pain onset. Magnetic resonance imaging demonstrated complete cross sectional spinal cord oedema from T9 to the conus, with small foci of intramedullary haemorrhage. There was lumbosacral nerve root enhancement. Laboratory investigations revealed strongly positive ANA, Anti-Ro, and Anti- Smith antibodies in keeping with a new diagnosis of systemic lupus erythematosus (SLE). Cerebrospinal fluid showed raised protein and mild predominantly neutrophilic pleocytosis. Further assessment revealed long standing arthralgia of the feet with no signs of active inflammation on examination. There was no other organ involvement from SLE, and no other cause of LETM was identified. Transverse myelitis is a rare (0.5% to 1%) complication of SLE. Acute haemorrhagic LETM is exceedingly more uncommon, reported in only a handful of cases. Unlike typical inflammatory myelitis, it has a hyperacute onset more evocative of a vascular event and a medically refractory course. This unique case alerts neurologists to a rare presentation and also highlights the importance of detailed radiological and laboratory evaluation of such cases.

# data[].attributes.headline
CSF neurofilament light chain profiling and quantitation in neurological diseases

# data[].attributes.subject
CSF neurofilament light chain profiling and quantitation in neurological diseases

# data[].attributes.attachment_link.readable_text
Abstract

Introduction

Neurofilament light chain (NfL) is a structural protein found within large fibre myelinated axons of the human central and peripheral nervous system and is an established fluid biomarker of neuronal injury. It is released into the CSF and blood of healthy individuals, but concentrations are elevated in a range of neurodegenerative and neuroinflammatory diseases. NfL is also significantly increased in non-primary neurological diseases such as hypoxic brain injury and COVID-19. Levels change dynamically in response to acute neuronal injury in traumatic brain injury and multiple sclerosis relapses. In chronic neurodegenerative diseases, levels correlate with rates of brain atrophy and with clinical progression making it an attractive biomarker of neurodegeneration. It is now widely used for clinical diagnostic purposes (e.g. to help identify neuronal damage) and on a research basis for measuring the clinical response to disease-modifying therapies. It is frequently deployed as an outcome measure in clinical trials across a range of diseases, including Alzheimer's disease, Huntington's disease, amyotrophic lateral sclerosis and multiple sclerosis.

NfL concentration in biofluids is currently measured using sandwich immunoassays with antibodies directed against the rod domain of the protein, for example using single-molecule array (Simoa) or enzyme-linked lectin assay (Ella). There are several limitations to these immunoassay platforms: scientific, logistic and economic. Firstly, antibody approaches are less reliable for absolute quantitation because they may miss protein oligomerization, post-translational modification, truncation and are liable to epitope masking by auto-antibodies and/or the presence of hetero-aggregates in biofluids. This is because the epitope to which the antibody binds may not be 'visible' to the antibody if it is not accessible. Secondly, the antibody is produced by commercial entities, which limits its characterization and adaptability. Finally, the antibody and assay kits are costly, which may restrict the uptake of NfL into widespread clinical practice especially as alternative tests for NfL are unavailable.

NfL has previously been characterized in CSF, identifying three main truncated species. One particular peptide that corresponds to the rod Coil 2B domain of the protein is elevated in Alzheimer's disease and is more likely to be relevant as a biomarker. It is not yet clear whether this peptide has similar relevance across the other neurological diseases. We aimed to profile NfL across a range of neurological diseases and then develop a rapid translational targeted mass spectrometry (MS) assay, using antibodies against tryptic peptides for more reliable quantitation of this particular rod domain of NfL. We aimed to compare this against the Simoa immunoassay and with an alternative independent targeted MS assay. The intended outcome was to generate a cost-effective diagnostic and reference tool that can be used across the full spectrum of neurological diseases.

Materials and methods

Participant recruitment and clinical demographics

Dementia

We prospectively recruited individuals with suspected neurodegenerative diseases from the specialist cognitive disorders clinics at the National Hospital for Neurology and Neurosurgery (NHNN), Queen Square and Darent Valley Hospital in Kent. Individuals provided consent to donate additional CSF for research prior to undergoing diagnostic lumbar puncture. Consensus criteria were used to classify individuals as probable Alzheimer's disease, behavioural variant frontotemporal dementia, dementia with Lewy bodies, corticobasal syndrome and semantic dementia. All individuals gave informed written consent (ethical permit: 12/LO/1504).

Huntington's disease

Individuals were recruited from the Huntington's disease multidisciplinary clinic at NHNN to the HD-CSF study. Expanded CAG repeat in HTT was genetically confirmed, and participants consented to research lumbar puncture. Ethical approval was provided by the London Camberwell St Giles Ethics Committee (ref: 186932).

Multiple sclerosis

Individuals were recruited from the multiple sclerosis service at the Royal London Hospital to the MS-SMART study. All individuals fulfilled clinical criteria for secondary progressive multiple sclerosis and gave consent to a research lumbar puncture at University College London (UCL). Ethical approval was provided by the Scotland A Research Ethics Committee (REC: 13/SS/0007).

Healthy controls

Controls were spouses or relatives of individuals attending the specialist cognitive disorder clinic at NHNN or who expressed an interest in research through Join Dementia Research ( www.joindementiaresearch.nihr.ac.uk). They did not have cognitive concerns and scored >27 on Mini-Mental State Examination, but CSF neurodegenerative biomarker profiles are not available. They were known not to be at risk of a genetic neurodegenerative disease. All individuals provided informed written consent. Ethical approval was given by the Hampstead Ethics Committee (ref: 19/LO/0913).

Sample collection

All CSF was collected by lumbar puncture according to local clinical standard operating procedures, in polypropylene containers between 09:00 and 15:00 and handled according to standardized predefined standard operating procedures as previously described. All CSF samples were stored at −80°C until analysis.

Simoa

CSF analysis was performed using the NF-L advantage kit with NfL concentrations measured on a Simoa HDx analyser (Quanterix). Samples were diluted 100×, and the assay performed as per the manufacturer's protocol. All samples were measured within one experiment and in singlicate with the analyst blinded to clinical status. Internal quality controls (QCs) were monitored to assess the intra-assay and inter-assay coefficients of variation (CV), which were determined to be 5.1-10.5 and 7.8%, respectively.

IP-MS for profiling of NfL (Washington University in St Louis)

Protein-level immunoprecipitation and sample preparation

As previously described, antibodies targeting Coil 1A/1B (HJ30.13), rod domain Coil 2B (HJ30.4) and tail subdomain (HJ30.11) of NfL were coupled to M270 Epoxy Dynabeads (Invitrogen) and mixed in a 1:1:1 ratio and suspended in 1× phosphate-buffered saline (PBS) to a final concentration of 15 mg/mL coupled beads. CSF samples (350 µL aliquots) were thawed and mixed with 0.5 ng of isotopically labelled internal standard ('ISTD', recombinant, ubiquitously labelled ¹⁵N-NfL, Promise Proteomics) and spiked with 25 µL of a master mix containing detergent (0.5% IGEPAL CA630), chaotropic reagent (5 mM guanidine) and 1× protease inhibitors (Roche cOmplete Protease Inhibitor Cocktail). CSF-ISTD mixes were transferred to a 96-well plate, at which point 30 µL antibody slurry was added to each sample well. Immunoprecipitation (IP) was carried out on a Kingfisher Flex Station (Thermo Scientific), which mixed CSF and antibody slurry for 90 min prior to three sequential washes of the NfL-coupled beads [25 mM triethylammonium bicarbonate (TEABC), 1 mL]. NfL-coupled beads were suspended in 100 µL TEABC (25 mM) for on-bead reduction and alkylation with dithiothreitol (50 mM DTT in 25 mM TEABC, 49 μg spike/sample, 1 h, 1000 rpm, room temperature (RT)] followed by iodoacetamide (IAA, 100 mM in 25 mM TEABC, 50 min, RT, light protected). Trypsin-Lys-C mix (Mass Spec Grade, Promega, in 25 mM TEABC) was then spiked into each sample (400 ng per sample) and incubated for 16 h at 37°C. Resultant tryptic peptides of NfL were isolated and cleaned up via solid-phase extraction (SPE; C-18 TopTip, Glygen). Stationary phase was wetted with 60% acetonitrile (ACN) and 0.1% formic acid (FA; 150 μL) and re-equilibrated with 0.1% FA (three additions of 150 μL). NfL peptides were loaded to TopTip via centrifugation (1109 x g, 2 min) and washed by adding 0.1% FA (three additions of 150 μL) to TopTip and centrifugation (1109 x g, 2 min). Peptides were eluted by adding 60% ACN and 0.1% FA (two additions of 50 μL) to TopTip and centrifugation (1109 x g, 1 min). Cleaned peptide extracts were concentrated by evaporation of eluent in vacuo and reconstituted in 25 μL 0.1% FA. Reconstituted samples were centrifuged (21 000 × g, 4°C, 15 min), and 21 μL was transferred for analysis via nano-liquid chromatography (LC)-tandem MS (MS/MS).

LC-MS/MS

Samples were injected (4.5 µL aliquot) by an M-Class nano-Acquity LC (Waters Corporation) fitted with High Strength Silica (HSS) C18 T3 analytical column (75 µm × 100 µm, 1.8 µm particle diameter). Samples were loaded on column via direct inject at 0.7 µL/min, with mobile phase composition of 99.5% A (0.1% FA) and 0.5% B (ACN, 0.1% FA) from t = 0 to 7.5 min. NfL peptides were separated at 0.4 µL/min with the following gradient: t = 7.6 min, %A: 99.5, %B: 0.5; t = 7.7 min, %A: 94, %B: 6; t = 24 min, %A: 66, %B: 34; t = 25 min, %A: 5, %B: 95; t = 26.99 min, %A: 5, %B: 95; and t = 27 min, %A: 99.5, %B: 0.5. NfL peptides were analysed in positive ion mode, spray voltage was 2.2 kV, and ion transfer tube temperature was 275°C. Parallel reaction monitoring was employed for characteristic transitions of endogenous and isotopically labelled (U-15N) NfL peptides (see Supplementary Table 1). All samples were measured with the analyst blinded to clinical status. NfL concentrations were calculated based on ratio to ISTD and reported in picograms per millilitre based on the volume of CSF used for IP.

Quantitative IP-MS/MS for NfL in CSF (University College London)

Tryptic digestion and peptide-level IP of NfL

For each sample, 450 μL of CSF was thawed and spiked with 1 ng of heavy labelled recombinant NfL (Promise Proteomics) prior to protein precipitation by addition of three sample volumes of ice-cold acetone and incubation at −20°C for 16 h. Precipitated protein was pelleted by centrifugation at 14 000 × g for 15 min at 4°C. The protein pellet was allowed to air-dry before re-solubilizing in 40 μL digest buffer (8 M urea, 200 mM Tris HCl, pH 8) for at least 30 min. Reduction and alkylation were performed with dithioerythritol (90 μg/sample) at RT with shaking at 1500 rpm for 1 h, followed by incubation with IAA (216 μg/sample) in the dark and at RT with shaking at 1500 rpm for 50 min. Samples were diluted with high-performance LC-grade ultrapure water prior to addition of MS-grade Trypsin-Lys-C to a final concentration of 2 µg/mL, and samples were digested for 16 hours at 37˚C. Post-digestion, and immediately prior to IP, all samples were spiked with 5 μL 6 mM tosyl-L-lysine chloromethyl ketone hydrochloride to inhibit Trypsin-Lys-C activity.

To provide enrichment of NfL, custom rabbit polyclonal antibodies were generated against the NfL ₃₁₆₋₃₂₃ peptide (TLEIEACR) from the Coil 2B rod domain (Eurogentec, Belgium). Purified IgG antibodies were coupled to M270 Epoxy Dynabeads™ following the manufacturer's instructions of the Dynabeads™ Antibody coupling kit (Invitrogen). Coupled beads were resuspended in 1× PBS at 10 ⁹ beads/mL. Fifty microlitres of antibody-coupled beads were added to each sample digest and incubated with rotation for 1.5 h at RT (20°C). The NfL-coupled beads were washed three times in 0.5 mM CHAPS (3-[(3-cholamidopropyl)dimethylammonio]-1-propane s ulfonate) in PBS before eluting in 50 μL 1% FA (in 0.5 mM CHAPS) with shaking at 1000 rpm for 6 min. Eluates containing the enriched NfL peptide were transferred to a 96-well sample collection plate fitted at the bottom with a magnet (SISCAPA Assay Technologies) ready for ultra-performance LC (UPLC)-MS/MS analysis.

UPLC-MS/MS

Analysis of NfL was performed on an Acquity™ I-Class PLUS UPLC coupled to a Xevo™ TQ-XS triple quadrupole mass spectrometer operated in positive electrospray ionization (ESI⁺) mode (Waters Corporation). Samples (15 μL) were injected onto an Acquity Premier peptide ethylene bridged hybrid (BEH) C18 analytical column (300 Å, 1.7 μm, 2.1 × 50 mm) held at 50°C. Initial mobile phase composition was set to 97% A (0.1% FA) and 3% B (ACN, 0.1% FA) at 0.2 mL/min. Chromatographic separation was performed over the following 16-min gradient: initial conditions were held until 0.2 min after which B was linearly increased to 35% by 11 min. To wash the column, B was increased to 100% over a 1-min linear gradient and held for 1.8 min at an increased flow rate of 0.6 mL/min before returning the system to initial conditions and re-equilibrating the column for 2.2 min. Mass spectrometer settings were as follows: 300°C desolvation temperature, 600 L/h desolvation gas flow, 2.5 kV capillary voltage, 150 L/h cone gas and 0.15 mL/min collision gas.

Samples were injected in a randomized order, with high and low QC samples analysed every 20 injections to monitor system performance. All samples were measured with the analyst blinded to clinical status.

All data were acquired by scheduled multiple reaction monitoring (MRM), with one quantifier and one qualifier ion monitored for each transition (see Supplementary Table 1). Raw acquisition data were imported and processed in Skyline (version 22.2, MacCoss Lab, University of Washington). Integrated peak areas and peak area ratios were exported into Microsoft Excel. NfL concentrations in picograms per millilitre were calculated based on an eight-point calibration curve as previously described.

Statistical analysis

Statistical analysis was performed in IBM Statistical Package for the Social Sciences (SPSS) Statistics (version 26) and R (version 4.2.2). Normality of the data was assessed visually by Q-Q plots and numerically by the Shapiro-Wilk or Kolmogorov-Smirnov tests where appropriate. Due to cohort ( n = 85) and disease group ( n = 6-19) size, the Spearman ranked correlation was used to assess the relationship between analytical methods for the overall cohort and within clinical diagnostic groups. To identify significant differences in NfL ₃₁₆₋₃₂₃ (TLEIEACR) concentrations between clinical groups, non-parametric Mann-Whitney U-tests were performed.

To assess agreement between quantitative methods, IP-MS/MS (UCL) and Simoa, Bland-Altman testing was performed. The calculated differences between methods were assessed for normality, and data found to reject the null hypothesis were log transformed prior to the Bland-Altman analysis.

To evaluate and compare method performance, confusion matrix analysis was performed based on current age-related clinical cut-off values for normal CSF NfL concentrations. Actual class positive or negative assignment was based on clinical diagnosis of study participants at time of sampling as those with a neurodegenerative disease or as a healthy control, respectively. Predictive class positive or negative assignment was based on current age-related clinical cut-off concentrations for normal CSF NfL as specified in Yilmaz et al.

Results

Profiles of NfL in CSF across neurodegenerative and neuroinflammatory disease groups

To map the relative amounts of protein fragments (proteoforms) of NfL in CSF, protein-level IP-MS analysis was performed at Washington University in St Louis (WashU) with the analyst blinded to clinical status. For all clinical groups, a total of 13 NfL peptides were detected across the following structural domains: Coil 1A ( n = 3), Coil 1B ( n = 5), Coil 2B ( n = 3), C-terminal tail subdomain A ( n = 1) and tail subdomain B ( n = 1). The resulting CSF NfL profiles for healthy controls and the studied neurodegenerative and neuroinflammatory diseases are shown in Fig. 1, with the greatest detection for the neighbouring Coil 2B peptides NfL ₃₂₄₋₃₃₁ (GMNEALEK) and NfL ₃₁₆₋₃₂₃ (TLEIEACR) observed in all clinical groups. Some notable but subtle differences were observed at the N- and C-terminus peptides ( Fig. 1). NfL ₃₂₄₋₃₃₁ and NfL ₅₃₀₋₅₄₀ relative profiles by disease are shown in Supplementary Fig. 1 to determine potential qualitative differences in NfL proteolysis by pathology.

Comparison of NfL targeted MS methods to Simoa

The study cohort demographics and NfL measures across analytical assays by clinical group are summarized below in Table 1, with NfL peptide-level IP-MS/MS (UCL) and NfL protein-level IP-MS (WashU) determined by detection of the NfL ₃₁₆₋₃₂₃ peptide (TLEIEACR).

Relative differences in mean NfL concentration across groups remained the same for all assays, with lowest-highest mean NfL concentrations observed in healthy controls, multiple sclerosis, dementia with Lewy bodies, Alzheimer's disease, semantic dementia, corticobasal syndrome, behavioural variant frontotemporal dementia and Huntington's disease ( Supplementary Fig. 2).

From all the NfL peptides measured during CSF profiling, NfL ₃₁₆₋₃₂₃ peptide concentrations quantified by IP-MS/MS (UCL) and IP-MS (WashU) methods were found to correlate most strongly with Simoa measures, r = 0.90 ( P < 0.001) and r = 0.89 ( P < 0.001), respectively ( Fig. 2A and B). NfL ₃₁₆₋₃₂₃ concentrations measured by the different targeted MS approaches across the study centres were also found to strongly correlate, r = 0.86 ( P < 0.001) ( Fig. 2C). Correlations between IP-MS (WashU) and Simoa for all detected NfL peptides are provided in Table 2.

To better determine the agreement between Simoa and the IP-MS/MS (UCL) method, Bland-Altman analysis was performed on log-transformed NfL concentrations ( Supplementary Fig. 3E), with limits of agreement (LoA) defined as the mean difference ± 1.96 × the standard deviation of the differences (s; Fig. 3). Visual assessment of the Bland-Altman plot suggests good agreement between IP-MS/MS (UCL) and Simoa methods. NfL concentrations measured by IP-MS/MS (UCL) were on average 59% higher than those measured by Simoa. Further comparison of all methods showed good agreement between the IP-MS/MS (UCL) and IP-MS (WashU) methods ( Supplementary Fig. 3C and D) and the IP-MS (WashU) method with Simoa ( Supplementary Fig. 3A and B).

Clinical group differences determined by Simoa are replicated by quantitative NfL₃₁₆₋₃₂₃ IP-MS/MS (UCL)

To further assess agreement between quantitative methods, differences in NfL concentrations across clinical diagnosis groups were evaluated for IP-MS/MS (UCL) and Simoa measures ( Fig. 4). The same significant differences in NfL concentrations measured by Simoa ( Fig. 4A) and IP-MS/MS ( Fig. 4B) were observed between healthy controls and all neurodegenerative diseases, except for the multiple sclerosis group. The most significant difference in NfL concentration between healthy controls and disease was observed for the Huntington's disease group ( P < 0.0005; n = 10) for both IP-MS/MS and Simoa methods.

Spearman ranked correlation was used to assess the relationship between analytical methods within clinical diagnostic groups. We found that the correlation strength of Simoa and IP-MS/MS (UCL) methods varied by disease group ( Supplementary Fig. 4). Very strong correlations were seen in behavioural variant frontotemporal dementia ( r = 0.94, P < 2.2e −16), multiple sclerosis ( r = 0.85, P = 0.004), dementia with Lewy bodies ( r = 0.81, P = 3e −5), corticobasal syndrome ( r = 0.8, P = 0.3) and Alzheimer's disease ( r = 0.79, P = 7e −04). Strong correlations were seen in Huntington's disease ( r = 0.64, P = 0.05) and controls ( P = 0.56, P = 0.1). The weakest correlation was seen in semantic dementia ( r = 0.37, P = 0.1; slope = 0.23).

Finally, we evaluated the clinical sensitivity, specificity and positive and negative predictive values of the IP-MS/MS (UCL) assay compared to Simoa. This analysis determined the IP-MS/MS (UCL) assay to provide equivalent positive and negative predictive values as Simoa, but greater sensitivity, accuracy and precision ( Supplementary Fig. 5).

Discussion

We have characterized NfL in CSF across a range of neurodegenerative and neuroinflammatory diseases and show that the most abundant NfL peptides identifiable by MS were from Coil 2B of the protein (amino acids 281-396). Having confirmed this, we have developed a targeted MRM method (IP-MS/MS) to quantitate NfL in CSF. Our results are highly correlated with the current 'gold standard' clinically accredited Simoa immunoassay that is used in clinical research to quantitate NfL in CSF and plasma to support diagnosis and monitor disease progression.

As disease-modifying therapies are now widely used in multiple sclerosis, have recently been licenced in Alzheimer's disease, with more FDA approvals likely and are in trial in other neurodegenerative diseases, it is critically important that we have access to biomarkers that support diagnosis and can be used to monitor target engagement. We show that this novel multiplexable assay can reliably and inexpensively quantitate NfL across a broad spectrum of neurodegenerative and neuroinflammatory diseases and has similar clinical diagnostic utility.

We used a large cohort of well-characterized participants from a single specialist centre. These findings were replicated between two independent research institutions, using autonomously developed methods, in academic labs in the UK and USA. One used peptide-level IP and the other used protein-level IP, both delivering similar results. We show that the targeted IP-MS/MS method has potential for translation into a clinical assay on a MS platform that is widely available in routine clinical laboratories. Although the upfront cost of a MS is high, the test itself costs around 12 USD, making it up to 10-fold cheaper than Simoa to run and could be multiplexed with other MS assays. It could also be used to value assign reference materials in further standardization projects.

Based on previous work, we suspected that existing immunoassays bind and quantitate the rod domain of the NfL protein. We set out to establish whether the relevant abundance of this NfL species was consistent across diseases. Using in-house antibodies that bind to different regions of the NfL protein, we were able to obtain comprehensive antibody pull-down in human CSF. We show that the most abundant NfL peptides identifiable by MS were from peptides corresponding to Coil 2B of the protein (amino acids 281-396). Importantly, this region is consistently increased across neurodegenerative and neuroinflammatory diseases and controls, showing that we are likely to be measuring the same NfL species across very different diseases, at unselected stages of disease.

Although the relative concentrations of NfL were consistent between the two assays (with some exceptions, discussed below), we noted with interest a ∼2-fold increase in mean CSF NfL ₃₁₆₋₃₂₃ concentration measured by MS compared to Simoa ( Supplementary Fig. 2), which may reflect the detection of NfL forms that are missed by Simoa. We already know that different truncations are found in CSF, and that these truncations are dimerized, making them difficult to detect by sandwich immunoassays. More specifically, it may be that most NfL species in CSF are dimers with truncated N- and C-termini; such a dimer would be quantified as one monomer using a sandwich immunoassay and two monomers using MS-based assays, potentially explaining our results.

There are few studies that directly compare protein and peptide antibody approaches for the same protein, but it has been suggested that peptide antibodies are more sensitive and specific, but with antibody efficiency being dependent on the structure of the protein or peptide in question. It is noteworthy that both approaches for purifying NfL, using either peptide or protein-level IP, delivered comparable results. This implies that NfL can, in principle, be effectively captured by either approach.

We observed some subtle disease-specific differences in correlations. The weakest correlation and notably different correlation slope between assays were observed in semantic dementia, a language-led variant of frontotemporal dementia with a strong clinicopathological correlation with TDP-43 type C pathology. This raises the possibility that the CSF pool of NfL in semantic dementia could represent different NfL truncations or different sub-populations of truncations.

We also observed some differences in peptide fold change stratification by disease state ( Fig. 1I and J). Generally, fold change ranking and stratification were consistent by disease state from Coil 1 to Coil 2 peptides (including immunoassay analogues NfL ₃₁₆₋₃₂₃ and NfL ₃₂₄₋₃₃₁). Mean fold change ranking by disease state was identical to a larger ELISA-based meta-analysis. Stratification and disease state fold change rank changed for C-terminal tail subdomain B peptide (NfL ₅₃₀₋₅₄₀), where semantic dementia, corticobasal syndrome, Huntington's disease, and behavioural variant frontotemporal dementia show highest fold change (ranked third, fourth, first and second, respectively, by NfL ₃₁₆₋₃₂₃ fold change stratification). This could imply variability in proteolysis of the tail subdomain relative to processing of Coil 2 of NfL and warrants further investigation.

A major strength of this study is that we developed a targeted method for NfL in one academic laboratory and then validated it using an independent method on a different mass spectrometer in a different institution. We used the same cohort of participants from CSF aliquots collected and handled identically. We were able to show a high level of correlation of results between centres, methods and equipment. This demonstrates that IP targeted MS is an extremely sensitive, specific and reproducible method for quantitating NfL, with potential for simple translation into validated clinical laboratories-for example, triple quadrupole platforms are found in many clinical laboratories in the UK, making it potentially translatable into clinical practice.

This study is not free from limitations. Our clinical cohorts are not demographically balanced; however, this reflects the rarity of selected conditions and the different ages at which these diseases commonly present. Methodologically, the use of different methods to report NfL concentrations between the IP-MS and IP-MS/MS assays limits the extent to which the two can be quantitatively compared.

In summary, we describe a novel assay to quantitate NfL, a widely used fluid biomarker that tracks disease activity and neurodegeneration. Our assay requires an antibody for tryptic peptide pull-down, but is less dependent on epitope visibility and other potential analytical challenges of current immunoassays such as the documented presence of auto-antibodies against neurofilaments due to their release into CSF during neurodegeneration and the masking of the epitopes of Uman antibodies used in immunoassays for NfL. Specifically, peptide-based MS assays overcome such issues due to the sample preparation pipeline prior to analysis, which utilizes trypsin to digest proteins. This makes it inherently more suitable for absolute protein quantitation as the peptides detected result from tryptic cleavage of all forms of NfL. The IP-MS/MS (UCL) method can be run rapidly in 16 min on a triple quadrupole mass spectrometer, such as those currently used in clinical practice and at a lower cost of ∼£10 (∼12 USD) per sample compared to ∼£80/sample by immunoassay. This assay could also be multiplexed with other targeted MRMs to allow quantitation of several proteins in tandem at low cost and on a high-throughput basis.

Supplementary material

Supplementary material is available at Brain Communications online.

Acknowledgements

The authors would like to thank all the study participants and those who care for them, for their time and contribution to this research. We are grateful to Prof. Simon Eaton (UCL) for his statistical expertise and to The NfL Consortium (AbbVie, Biogen, Bristol Myers Squibb and Hoffman de la Roche).

Funding

This research was supported by funding for C.A.L., J.B.C. and R.W.P. C.A.L. was supported by research funding from The Neurofilament Light Consortium and Medical Research Council. R.W.P. is supported by an Alzheimer's Association clinician scientist fellowship (AACSF-20-685780), an Alzheimer's Association Part the Cloud grant (AACSF-20-685780), the National Institute for Health and Care Research University College London Hospitals Biomedical Research Centre and UK Dementia Research Institute. T.A.G. is supported by an Alzheimer's Association Research Fellowship (23AARFD-1029918). E.J.W. is supported by CHDI Foundation. H.Z. is a Wallenberg Scholar supported by grants from the Swedish Research Council (#2022-01018 and #2019-02397), the European Union's Horizon Europe research and innovation programme under grant agreement no. 101053962, Swedish State Support for Clinical Research (#ALFGBG-71320), the Alzheimer's Drug Discovery Foundation (#201809-2016862), the Alzheimer's Disease Strategic Fund and the Alzheimer's Association (#ADSF-21-831376-C, #ADSF-21-831381-C and #ADSF-21-831377-C), the Bluefield Project, the Olav Thon Foundation, the Erling-Persson Family Foundation, Stiftelsen för Gamla Tjänarinnor, Hjärnfonden, Sweden (#FO2022-0270), the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 860197 (MIRIADE), the European Union Joint Programme-Neurodegenerative Disease Research (JPND2021-00694), the National Institute for Health and Care Research University College London Hospitals Biomedical Research Centre and the UK Dementia Research Institute (UKDRI-1003). L.M.B. is supported by the Medical Research Council (MR/W026686/1).

Competing interests

H.Z. has served at scientific advisory boards and/or as a consultant for AbbVie, Acumen, Alector, Alzinova, ALZPath, Annexon, Apellis, Artery Therapeutics, AZTherapies, Cognito Therapeutics, CogRx, Denali, Eisai, Nervgen, Novo Nordisk, Optoceutics, Passage Bio, Pinteon Therapeutics, Prothena, Red Abbey Labs, reMYND, Roche, Samumed, Siemens Healthineers, Triplet Therapeutics and Wave, has given lectures in symposia sponsored by Cellectricon, Fujirebio, Alzecure, Biogen and Roche and is a co-founder of Brain Biomarker Solutions in Gothenburg AB (BBS), which is a part of the GU Ventures Incubator Program (outside submitted work). R.J.B. and R.W.P. lead The Neurofilament Light Consortium, an industry academic collaboration that is supported by AbbVie, Bristol Myers Squibb, Biogen and Roche. R.W.P. has received honoraria from GE Healthcare for educational talks, which is used to support academic work. R.J.B. has received research funding from Avid Radiopharmaceuticals, Janssen, Roche/Genentech, Eli Lilly, Eisai, Biogen, AbbVie, Bristol Myers Squibb and Novartis. Washington University and R.J.B. have equity ownership interest in C2N Diagnostics and receive income based on technology (neurofilament light chain assays and materials) licenced by Washington University to C2N Diagnostics. R.J.B. receives income from C2N Diagnostics for serving on the scientiﬁc advisory board. R.J.B. serves on the Roche Gantenerumab Steering Committee as an unpaid member. J.C. has received support from the Health Technology Assessment (HTA) Programme (National Institute for Health Research, NIHR), the UK MS Society, the US National MS Society and the Rosetrees Trust. He is supported in part by the National Institute for Health and Care Research University College London Hospitals Biomedical Research Centre, London, UK. He has been a local principal investigator for a trial in multiple sclerosis funded by the Multiple Sclerosis Society of Canada. A local principal investigator for commercial trials was funded by Ionis, Novartis and Roche and has taken part in advisory boards/consultancy for Azadyne, Biogen, Lucid, Janssen, Merck, NervGen, Novartis and Roche. The MS-SMART trial was funded by the Efficacy and Mechanism Evaluation programme as project number 11/30/11. MS-SMART is an investigator-led project sponsored by the University College London. This independent research is awarded by and funded by the Medical Research Council, the UK MS Society and the National MS Society and is managed by the National Institute for Health Research on behalf of the Medical Research Council-National Institute for Health partnership. Additional support came from the University of Edinburgh, the National Institute for Health Research University College London Hospitals Biomedical Research Centre and University College London and the National Institute for Health Research Leeds Clinical Research Facility (Dental Translational and Clinical Research Unit). Riluzole was provided without charge by Sanofi-Genzyme who was not involved in either the trial design, running of the trial or analysis. F.D.A. received speaker honoraria from Neurology Academy, Janssen, Merck, Novartis and Sanofi; is on the advisory board for Novartis and Coloplast; has received congress fees from Janssen, Merck, Novartis and Roche; and is a regional coordinator for the Oratorio Hand Trial (Hoffmann-La Roche). The rest of the authors declared no conflicting interests.

Data availability

The data sets generated during the current study are available from the corresponding author upon reasonable request.

References

Author notes

# data[].attributes.attachment_link.title
CSF neurofilament light chain profiling and quantitation in neurological diseases

# data[].attributes.attachment_link.description
Leckey et al. report a new mass spectrometry-based method to capture and quantify neurofilament light (NfL) from CSF. The assay targets a specific tryptic

# data[].attributes.headline
International Alliance of Urolithiasis (IAU) consensus on miniaturized percutaneous nephrolithotomy

# data[].attributes.subject
International Alliance of Urolithiasis (IAU) consensus on miniaturized percutaneous nephrolithotomy

# data[].attributes.attachment_link.title
International Alliance of Urolithiasis (IAU) consensus on miniaturized percutaneous nephrolithotomy - Military Medical Research

# data[].attributes.attachment_link.description
Over the past three decades, there has been increasing interest in miniaturized percutaneous nephrolithotomy (mPCNL) techniques featuring smaller tracts as they offer potential solutions to mitigate complications associated with standard PCNL (sPCNL). However, despite this growing acceptance and recognition of its benefits, unresolved controversies and acknowledged limitations continue to impede widespread adoption due to a lack of consensus on optimal perioperative management strategies and procedural tips and tricks. In response to these challenges, an international panel comprising experts from the International Alliance of Urolithiasis (IAU) took on the task of compiling an expert consensus document on mPCNL procedures aimed at providing urologists with a comprehensive clinical framework for practice. This endeavor involved conducting a systematic literature review to identify research gaps (RGs), which formed the foundation for developing a structured questionnaire survey. Subsequently, a two-round modified Delphi survey was implemented, culminating in a group meeting to generate final evidence-based comments. All 64 experts completed the second-round survey, resulting in a response rate of 100.0%. Fifty-eight key questions were raised focusing on mPCNLs within 4 main domains, including general information (13 questions), preoperative work-up (13 questions), procedural tips and tricks (19 questions), and postoperative evaluation and follow-up (13 questions). Additionally, 9 questions evaluated the experts’ experience with PCNLs. Consensus was reached on 30 questions after the second-round survey, while professional statements for the remaining 28 key questions were provided after discussion in an online panel meeting. mPCNL, characterized by a tract smaller than 18 Fr and an innovative lithotripsy technique, has firmly established itself as a viable and effective approach for managing upper urinary tract stones in both adults and pediatrics. It offers several advantages over sPCNL including reduced bleeding, fewer requirements for nephrostomy tubes, decreased pain, and shorter hospital stays. The series of detailed techniques presented here serve as a comprehensive guide for urologists, aiming to improve their procedural understanding and optimize patient outcomes.

# data[].attributes.headline
Case Series of Abdominal Actinomycosis: An Old Diagnostic Conundrum

# data[].attributes.subject
Case Series of Abdominal Actinomycosis: An Old Diagnostic Conundrum

# data[].attributes.attachment_link.title
Case Series of Abdominal Actinomycosis: An Old Diagnostic Conundrum

# data[].attributes.attachment_link.description
Abdominal actinomycosis is a rare disease caused by the Actinomyces bacteria. We report a case series of two similar cases with a mismatch between the initial differential diagnosis, the radiological findings, the surgical findings, and the actual histological result. The first case is a 25-year-old woman with a month’s history of right-sided abdominal pain. The diagnostic workup including computed tomography (CT) showed possible acute appendicitis, in addition to ascending colon looking abnormal with inflammatory changes and adjacent peritoneal nodules. A diagnostic laparoscopy revealed a normal-looking appendix and a hard mass involving the ascending colon potentially of inflammatory or malignant origin. A laparoscopic right hemicolectomy was performed. Surprisingly, the histology concluded actinomycosis. The second case is a 38-year-old woman with a six-week history of lower abdominal pain and right iliac fossa (RIF) swelling. The diagnostic workup including a CT scan showed a complex mass suggesting complicated appendicitis, pelvic inflammatory disease, or neoplastic process. Furthermore, magnetic resonance imaging (MRI) of the pelvis showed complex bilateral cystic lesions in both iliac fossas with an abscess formation within the subcutaneous fat overlying the lower pelvis. The patient underwent an ultrasound (US)-guided drainage of the subcutaneous pelvic collection and a diagnostic laparoscopy that showed an inflamed mass with dense adhesions to the anterior abdominal wall. Intraoperative biopsies were taken to confirm the diagnosis, which ultimately confirmed severe pelvic actinomycosis. Both patients were discharged home and received extended antibiotic treatment according to microbiology guidelines with good outcomes. Both cases are interesting because there was a mismatch between the initial differential diagnosis, the radiological findings, the intraoperative findings, and the final histology. Reported cases in the literature highlight the diagnostic challenges of abdominal actinomycosis, as it often presents with atypical symptoms and imaging findings sometimes mimic malignancy leading to surgical intervention.

# data[].attributes.headline
Laparoscopic renal denervation: A treatment option for management of refractory loin pain

# data[].attributes.subject
Laparoscopic renal denervation: A treatment option for management of refractory loin pain

# data[].attributes.headline
Risk Factors Associated With Negative Appendicectomy Rates: A Retrospective Cohort Study

# data[].attributes.subject
Risk Factors Associated With Negative Appendicectomy Rates: A Retrospective Cohort Study

# data[].attributes.attachment_link.title
Risk Factors Associated With Negative Appendicectomy Rates: A Retrospective Cohort Study

# data[].attributes.attachment_link.description
Background: Acute appendicitis (AA) is the most common emergency general surgical condition worldwide. Diagnosis is challenging and incorporates clinical, biochemical and radiological investigations. Our aim was to provide data from routine practice investigating widely utilised diagnostic methods from a single centre within the United Kingdom.

# data[].attributes.headline
Description and Cross-Sectional Analyses of 25,880 Adults and Children in the UK National Registry of Rare Kidney Diseases Cohort

# data[].attributes.subject
Description and Cross-Sectional Analyses of 25,880 Adults and Children in the UK National Registry of Rare Kidney Diseases Cohort

# data[].attributes.headline
Cystoscopic retrograde study using gadolinium as a contrast medium in a patient with iodinated contrast agent allergy

# data[].attributes.subject
Cystoscopic retrograde study using gadolinium as a contrast medium in a patient with iodinated contrast agent allergy

# data[].attributes.headline
Resolution of multiorgan sarcoid-like reaction after treatment of renal cell carcinoma

# data[].attributes.subject
Resolution of multiorgan sarcoid-like reaction after treatment of renal cell carcinoma

# data[].attributes.attachment_link.readable_text
Resolution of multiorgan sarcoid-like reaction after treatment of renal cell carcinoma

Abstract

Sarcoid -like reactions (SLRs) can occur in several malignancies adjacent to primary tumour location or the draining lymph nodes. The presence of peritumoural and intratumoural SLR in patients suffering from renal cell carcinoma (RCC) has been reported in few instances. However, the association of RCC with SLR in spleen, liver and other organs in the absence of systemic sarcoidosis is very rare.

We present an unusual case of a gentleman in his 30s, who presented with a lesion in the left kidney along with non-specific lesions (likely granulomatous) in liver, spleen and lungs. Partial Nnephrectomy specimen confirmed conventional/clear cell RCC. The histopathology revealed an extensive epithelioid granulomatous reaction affecting both peritumoural and intratumoural areas. Follow-up images demonstrated an almost complete resolution of lesions in the spleen, liver and lungs. Our case supports the hypothesis that non-caseating granulomas of SLR could be a manifestation of an immunologically mediated antitumour response.

Renal intervention

Cancer intervention

Statistics from Altmetric.com

Request Permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center's RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

Read the full text or download the PDF:

# data[].attributes.attachment_link.title
Resolution of multiorgan sarcoid-like reaction after treatment of renal cell carcinoma

# data[].attributes.attachment_link.description
Sarcoid -like reactions (SLRs) can occur in several malignancies adjacent to primary tumour location or the draining lymph nodes. The presence of peritumoural and intratumoural SLR in patients suffering from renal cell carcinoma (RCC) has been reported in few instances.

# data[].attributes.headline
Patients' Preferences for Cytoreductive Treatments in Newly Diagnosed Metastatic Prostate Cancer: The IP5-MATTER Study

# data[].attributes.subject
Patients' Preferences for Cytoreductive Treatments in Newly Diagnosed Metastatic Prostate Cancer: The IP5-MATTER Study

# data[].attributes.headline
Intracardiac diffuse large B-cell lymphoma: an unexpected diagnosis

# data[].attributes.subject
Intracardiac diffuse large B-cell lymphoma: an unexpected diagnosis

# data[].attributes.attachment_link.readable_text
Abstract

Intracardiac lymphomas are exceedingly rare accounting for only 1% of all primary cardiac tumours. Historically, due to their insidious development and non-specific clinical presentation, the diagnosis has been challenging with most cases being confirmed on post-mortem examination. Our case report details the experience of a previously fit and active woman in her 60s who presented with gradual onset exertional dyspnoea. Through a series of multimodal imaging tools (including echocardiogram, cardiac MRI, CT and positron emission tomography-CT) and biopsy, we confirmed the diagnosis of intracardiac diffuse large B-cell lymphoma. Our patient was managed with chemotherapy and went on to demonstrate excellent radiological response with near-complete resolution of the intracardiac mass. Subjectively, our patient reported significant improvement in exercise tolerance within weeks of commencing treatment.

Statistics from Altmetric.com

Request Permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center's RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

Read the full text or download the PDF:

# data[].attributes.attachment_link.title
Intracardiac diffuse large B-cell lymphoma: an unexpected diagnosis

# data[].attributes.attachment_link.description
Intracardiac lymphomas are exceedingly rare accounting for only 1% of all primary cardiac tumours. Historically, due to their insidious development and non-specific clinical presentation, the diagnosis has been challenging with most cases being confirmed on post-mortem examination. Our case report details the experience of a previously fit and active woman in her 60s who presented with gradual onset exertional dyspnoea. Through a series of multimodal imaging tools (including echocardiogram, cardiac MRI, CT and positron emission tomography-CT) and biopsy, we confirmed the diagnosis of intracardiac diffuse large B-cell lymphoma. Our patient was managed with chemotherapy and went on to demonstrate excellent radiological response with near-complete resolution of the intracardiac mass. Subjectively, our patient reported significant improvement in exercise tolerance within weeks of commencing treatment.

# data[].attributes.headline
Global 30-Day Morbidity and Mortality of Primary Bariatric Surgery Combined with Another Procedure: The BLEND Study - Amira Said - June 2024

# data[].attributes.subject
Global 30-Day Morbidity and Mortality of Primary Bariatric Surgery Combined with Another Procedure: The BLEND Study - Amira Said - June 2024

# data[].attributes.attachment_link.readable_text
Abstract

Background

No robust data are available on the safety of primary bariatric and metabolic surgery (BMS) alone compared to primary BMS combined with other procedures.

Objectives

The objective of this study is to collect a 30-day mortality and morbidity of primary BMS combined with cholecystectomy, ventral hernia repair, or hiatal hernia repair.

Setting

This is as an international, multicenter, prospective, and observational audit of patients undergoing primary BMS combined with one or more additional procedures.

Methods

The audit took place from January 1 to June 30, 2022. A descriptive analysis was conducted. A propensity score matching analysis compared the BLEND study patients with those from the GENEVA cohort to obtain objective evaluation between combined procedures and primary BMS alone.

Results

A total of 75 centers submitted data on 1036 patients. Sleeve gastrectomy was the most commonly primary BMS ( N = 653, 63%), and hiatal hernia repair was the most commonly concomitant procedure ( N  = 447, 43.1%). RYGB accounted for the highest percentage (20.6%) of a 30-day morbidity, followed by SG (10.5%). More than one combined procedures had the highest morbidities among all combinations (17.1%). Out of overall 134 complications, 129 (96.2%) were Clavien-Dindo I-III, and 4 were CD V. Patients who underwent a primary bariatric surgery combined with another procedure had a pronounced increase in a 30-day complication rate compared with patients who underwent only BMS (12.7% vs. 7.1%).

Conclusion

Combining BMS with another procedure increases the risk of complications, but most are minor and require no further treatment. Combined procedures with primary BMS is a viable option to consider in selected patients following multi-disciplinary discussion.

Graphical Abstract

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

Article Open access

References

1. Marzouk AMSM, Ali HOE. Laparoscopic ventral hernia repair combined with sleeve gastrectomy in morbidly obese patients: early outcomes. Surg J (N Y). 2019;05(3):e87-91. https://doi.org/10.1055/s-0039-1694979.

Article Google Scholar

2. von Elm E, Altman DG, Egger M, et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. J Clin Epidemiol. 2008;61(4):344-9. https://doi.org/10.1016/j.jclinepi.2007.11.008.

Article Google Scholar

3. IBM Corp. Released 2020. IBM SPSS Statistics for Windows, Version 27.0. Armonk, NY: IBM Corp

4. R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. 2019. https://www.R-project.org/.

5. Ho D, Imai K, King G, Stuart EA. MatchIt: nonparametric preprocessing for parametric causal inference. J Stat Softw. 2011;42:1-28. https://doi.org/10.18637/jss.v042.i08.

Article Google Scholar

6. ACS National Surgical Quality Improvement Program. ACS. Accessed December 5, 2023. https://www.facs.org/quality-programs/data-and-registries/acs-nsqip/

7. Malaussena Z, Mhaskar R, Richmond N, et al. Hernia repair in the bariatric patient: a systematic review and meta-analysis. Surg Obes Relat Dis. Published online October 14, 2023:S1550-7289(23)00749-9. https://doi.org/10.1016/j.soard.2023.10.005

Download references

Author information

Authors and Affiliations

1. Department of Surgery, Duke University, Durham, NC, USA

Alessandro Martinino

2. University Hospitals of Derby & Burton NHS Foundation Trust, Derby, UK

Kushan D. L. Nanayakkara & Brij Madhok

3. Northern Clinical School, The University of Sydney, Camperdown, Australia

Geoffrey Yuet Mun Wong

4. Department of Surgery, Barts Health NHS Trust, Royal London Hospital, London, UK

Mohamed Abouelazayem

5. Internal Medicine Department, Advocate Illinois Masonic Medical Center, Chicago, IL, USA

Juan Pablo Scarano Pereira

6. ABVIMS & Dr.RML Hospital, New Delhi, India

Ishaan Wazir

7. Ysbyty Gwynedd Hospital, Bangor, Wales

Vignesh Balasubaramaniam

8. Department of Surgery, Darent Valley Hospital, Dartford, UK

Amira Said

9. Centro Hospitalar Universitário Lisboa Central, Lisbon, Portugal

Cláudia Marques

10. Badr Hospital - Helwan University, Cairo, Egypt

Amr Abdelbaeth, Ayman Kamal, Ahmed Mohamed Ali, Karim Mostafa Mohamed & Omnya Osama

11. Al-Basheer Hospital, Amman, Jordan

Khayry Al-Shami, Almu'atasim Khamees & Khaled Ahmad Sawaftah

12. Alfaisal University, Riyadh, Saudi Arabia

Muna Albashari

13. Gharyan Central Hospital, Gharyan, Libya

Akram Alkaseek

14. Prince Sattam Bin Abdulaziz University, Riyadh, Saudi Arabia

Mohammad Abdullah Almayouf

15. Aleppo Private Hospital, Aleppo, Syria

Mohammad Aloulou

16. King Saud University, Riyadh, Saudi Arabia

Awadh Robaan Alqahtan

17. Luton and Dunstable University Hospital, Luton, UK

Alan Askari & HMinali R. Perera

18. General Surgery Department, Faculty of Medicine, Ain Shams University, Cairo, Egypt

Meena Faiez Assad Attia, Ahmed K. Awad & Amr Elgazar

19. Pamukkale University, Denizli, Turkey

Muhammed Rasid Aykota

20. Cantacuzino Clinical Hospital, Bucharest, Romania

Nicolae Bacalbasa

21. Christus Muguerza Hospital Sur, Monterrey, Mexico

Francisco J. Barrera-Rodriguez

22. Department of Bariatric and Metabolic Surgery, San Carlo of Nancy Hospital and University of Rome Tor Vergata, Rome, Italy

Domenico Benavoli, Michela Campanelli & Paolo Gentileschi

23. Dr. Sulaiman Alhabib Hospital, Riyadh, Saudi Arabia

Srikar Billa

24. IRCCS Humanitas Research Hospital, Milan, Italy

Vincenzo Borrelli, Giuseppe M. Marinari, Giovanni Piscitelli & Manuela Trotta

25. Çam&Sakura City Hospital, Istanbul, Turkey

İsmail Çalıkoğlu

26. Center of Excellence for the Study and Treatment of Obesity and Diabetes, Valladolid, Spain

Miguel A. Carbajo & David Ramírez

27. King Saud Medical City, Riyadh, Saudi Arabia

Sharfuddin Chowdhury

28. Faculty of Medicine and Surgery, University of Verona, Verona, Italy

Luca Cristin

29. International School Reduced Scar Laparoscopy, Humanitas Gavazzeni University Hospital, Bergamo, Italy

Giovanni Dapri

30. The First Affiliated Hospital of Jinan University, Guangzhou, China

Zhiyong Dong, Cunchuan Wang, Zhuoqi Wei & Wah Yang

31. Najjar Hospital, Beirut, Lebanon

Mohamad Hayssam Elfawal & Diyaaldeen Mohammed

32. Faculty of Medicine, University of Tripoli, Tripoli, Libya

Muhammed Elhadi

33. Faculty of Health Sciences and Wellbeing, University of Sunderland, Sunderland, UK

Yitka Graham

34. Holy Family Hospital, Nazareth, Israel

Bassel Haj & Nasser Sakran

35. The Azrieli Faculty of Medicine, Bar-Ilan University, ZefatRamat Gan, Israel

Bassel Haj

36. Highland Hospital, University of Rochester, Rochester, NY, USA

Joseph Andrew Johnson, Anna Kamocka, William Edward O'Malley, Aaron Sabbota, Nasser Sakran & Kaci Schiavone

37. Al-Azhar University, Cairo, Egypt

Abd-Elfattah Morsi Kalmoush

38. Department of Surgery, Sant'Eugenio Hospital, Viale Dell'Umanesimo 10, Rome, Italia

Giorgio Lisi

39. Hospital Regional de Alta Especialidad del Bajio, León, Mexico

Edgard Efren Lozada Hernandez

40. Azienda Ospedaliero Universitaria Policlinico, Bari, Italy

Gennaro Martines

41. Bagcilar Training and Research Hospital, Istanbul, Turkey

Serhat Meric & Merve Tokocin

42. University of Oklahoma, Oklahoma City, USA

Fernando Mier

43. General University Hospital of Patras, Patras, Greece

Francesk Mulita & Georgios -Ioannis Verras

44. Advanced Biomedical Sciences Department, Federico II University, Naples, Italy

Mario Musella

45. San Marco Hospital GSD, Zingonia, Italy

Stefano Olmi & Matteo Uccelli

46. Azerbaijan Medical University, Baku, Azerbaijan

Taryel Omarov

47. Hopital Bichât, Paris, France

Tigran Poghosyan

48. Inova Fairoaks Hospital, Bariatric Center of Excellence, Fairfax, USA

Masoud Rezvani

49. Hospital Lusiadas Amadora, Amadora, Portugal

Rui Ribeiro

50. Nişantaşı University, Istanbul, Turkey

Ozan Şen

51. Evaggelismos Hospital, Athen, Greece

Maria Sotiropoulou

52. University of Foggia, Foggia, Italy

Nicola Tartaglia

53. Türkçapar Bariatrics, Istanbul, Turkey

Ahmet Gökhan Türkçapar

54. Hospital General Tlahuac, Mexico City, Mexico

Cesar Vargas & Carlos Zerrweck

55. Department of Surgery & Cancer, Imperial College London, London, UK

Eloise Owen

56. Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK

Georgios V. Gkoutos & Victor Roth Cardoso

57. University Hospital Birmingham NHS Foundation Trust, West Midlands, UK

Rishi Singhal

58. South Tyneside and Sunderland NHS Foundation Trust, University of Sunderland, Sunderland, UK

Kamal Mahawar

Consortia

BLEND Study Collaborative Group

Corresponding author

Correspondence to Alessandro Martinino.

Ethics declarations

Competing Interests

The authors declare no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

KeyPoints

* Primary bariatric surgery combined with another procedure had a pronounced increase in 30-day complication rate.

* RYGB accounted for the highest percentage (20.6%) of 30-day morbidity, followed by SG (10.5%).

* More than one combined procedures had the highest morbidities among combined procedures (17.1%).

* Combined procedures with primary BMS is a viable option to consider in selected patients.

Supplementary Information

Below is the link to the electronic supplementary material.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
Reprints and permissions

About this article

Cite this article

Martinino, A., Nanayakkara, K.D.L., Madhok, B. et al. Global 30-Day Morbidity and Mortality of Primary Bariatric Surgery Combined with Another Procedure: The BLEND Study. OBES SURG (2024). https://doi.org/10.1007/s11695-024-07296-0
Download citation

Share this article

Anyone you share the following link with will be able to read this content:

Get shareable link

Provided by the Springer Nature SharedIt content-sharing initiative

Keywords

# data[].attributes.attachment_link.title
Global 30-Day Morbidity and Mortality of Primary Bariatric Surgery Combined with Another Procedure: The BLEND Study - Obesity Surgery

# data[].attributes.attachment_link.description
Background No robust data are available on the safety of primary bariatric and metabolic surgery (BMS) alone compared to primary BMS combined with other procedures. Objectives The objective of this study is to collect a 30-day mortality and morbidity of primary BMS combined with cholecystectomy, ventral hernia repair, or hiatal hernia repair.

# data[].attributes.headline
The development of the Egyptian 24-h movement guidelines for adults aged 50 years and older: an integration of sleep, sedentary behavior, and physical activity by the Egyptian Academy of Bone and Muscle Health

# data[].attributes.subject
The development of the Egyptian 24-h movement guidelines for adults aged 50 years and older: an integration of sleep, sedentary behavior, and physical activity by the Egyptian Academy of Bone and Muscle Health

# data[].attributes.attachment_link.readable_text
The development of the Egyptian 24-h movement guidelines for adults aged 50 years and older: an integration of sleep, sedentary behavior, and physical activity by the Egyptian Academy of Bone and Muscle Health

Abstract

Background

With the vision of healthy aging, the Egyptian Academy of Bone and Muscle Health followed an established guideline development process to create the Egyptian 24-h movement clinical guideline for adults aged 50 years and older adults. This guideline highlights the significance of movement behaviors across the whole 24-h day. Online databases (PubMed, Embase, and Cochrane Library) were searched for relevant peer-reviewed studies that met the a priori inclusion criteria.

Results

A total of 53 studies met the inclusion criteria. Leveraging evidence from the review of the literature led to the development of 27 statements answering the 5 key questions. Results revealed a major change in the previous basic understandings as it shifts away from focussing on a sole movement behavior to the combination of all the movement behaviors. Based on this, the final guideline was developed providing evidence-based recommendations for a "Healthy 24-Hour Day", comprising a mix of light-intensity and moderate-to-vigorous-intensity physical activity, sleep, and sedentary behavior.

Conclusion

The developed guidelines are meant to help in the decision-making process and are intended for use by adults and older both nationally and internationally; also, for endorsement by the policy-makers. Dissemination and implementation efforts would impact positively on both health professionals and researchers and would also be useful to interested members of the public sector.

Similar content being viewed by others

Article Open access

Article Open access

Article Open access

Background

Lack of physical activity has been linked to poor health and the development of various chronic illnesses with consequent potential disability in later life [ 1]. Despite these findings, it has been reported that nearly a quarter of people aged 50 years and older do less than 30 min of physical activity a week [ 2]. Musculoskeletal-wise, physical inactivity has a negative impact on both bone and muscle strength, reaction time, as well as endurance and posture. Concerning body organs, low level of physical activity is a well-known predisposing factor for several comorbidities including obesity, type II diabetes mellitus, hyperlipidemia, hypertension, coronary artery disease, stroke, and cancer particularly colon and breast cancer leading to premature death or disability [ 3]. At the supernational level, the World Health Organization (WHO) had estimated a yearly rate of two million premature deaths due to physical inactivity [ 4]. Although most of this data are from younger populations, other studies reported that this problem applies to older populations as well [ 2].

In the next Egyptian demographic transition, the number of elderly persons aged 60 + is expected to be more than twice as high between 2020 and 2050 from 8.4 million (8% of the total population) to 22 million (14%) [ 5]. In concordance with the industrial countries, a lack of physical activity has also been reported amongst Egyptian older adults. Earlier data revealed that less than 10% of the Egyptian population practice regular exercises, of them, the most inactive population were those over the age of 60 years old [ 6, 7]. The WHO report about physical activity in Egypt revealed that the prevalence of physical inactivity in Egyptian females over 70 years old was 55% whereas in men of the same age group was 35% [ 8]. Ageing is an evitable stage of life; therefore, it is important to have guidelines for physical activity which so far are not available in Egypt. With the vision of healthy aging, this work was carried out aiming to develop the Egyptian 24-h movement guidelines for adults aged 50 years and older with consideration of a balanced approach to sleep, sedentary behavior, and physical activity. These guidelines emphasize the significance of movement behaviors across the whole 24-h day.

Methodology

Study design

The framework used to develop the guidelines is consistent with the "Clinical, Evidence-based, Guidelines" (CEG) initiative protocol [ 9]. The methodology was designed to minimize bias, maximize transparency, and ensure high quality of the systematic reviews. The evidence-based component of the manuscript accommodated the preferred reporting items for systematic reviews and meta-analysis guidelines for reporting systematic reviews [ 10]. The project was an initiative led by the Egyptian Academy of Bone and Muscle Health.

Ethical aspects

This study was performed in accordance with the Helsinki Declaration. This was a multistep process that followed the "Clinical, Evidence-based, Guidelines" (CEG) initiative protocol, ethical approval code: 34842/8/21, ethical board Tanta University.

Core team

The core team provided an overview of the guideline development process, responsibilities, and timelines. The core team also drafted a set of research questions for each of the three behaviors: sleep, sedentary, and physical activity, as well as the integration of all these behaviors. The core team reached an agreement on the target Population, Intervention, Comparator and Outcomes (PICO) [ 11] (Table 1).

Literature review team

The evidence reviews were conducted by 2 experienced researchers and an expert in methodology. This depended on the identified research questions. The team addressed the gaps and generated the info for every behavior [ 12]. The articles search was carried out for the period from January 2000 till January 2024. The search keywords were identified based on different combinations of the PICO elements. Literature searches were carried out on 18th December 2023 for PubMed and Cochrane Library databases, and on 29th December 2023 for Embase. Duplicate screening of literature search results was carried out electronically. Further studies of relevance to the review were identified by an update of the review of the literature and from the lists of references of studies retrieved in the former initial database search. Recommendations regarding each section were provided by each of the experts in charge of the review of the literature, based on the evidence, when this was available, or on their own experience. The workgroup used the Oxford Centre for Evidence-based Medicine (OCEBM) system [ 13] to determine the level of evidence for each section.

Inclusion criteria

To be included in the current review, studies were required to meet the following criteria: (1) the study was published in an English-language, refereed journal with full-text availability; (2) the study contained original research (clinical guidelines, systematic reviews, randomized controlled trials (RCTs), uncontrolled trials, observational studies including cohort, case-control and cross-sectional studies); (3) the study included one or more assessment of each 24-h movement behavior, that is, physical activity, sedentary behavior and sleep; (4) to have a clearly described methodology including the PICO elements of the reviewed question.

Exclusion criteria

(1) Editorials, commentaries, conference abstracts, and non-evidence-based narrative/personal reviews were excluded; 2. Studies or clinical guidelines that referred only to admitted or hospitalized populations; 3. Studies or clinical guidelines that included populations other than adults or older adults.

Results

Review of the literature

The database systematic literature search yielded a total of 4987 relevant potential publications. Figure 1 shows the flowchart summarising the study selection process. After removing duplicates, 3813 records remained. After screening the titles and abstracts, 99 potentially relevant citations were obtained for full-text review. Of those, after completing the reading 51 studies met the inclusion criteria. Two additional citations relevant to this work were identified following an up-to-date search and those retrieved from the bibliography of the included articles. Therefore, a total of 53 studies published met the eligibility criteria and consequently were included in this work. These included nine clinical guidelines: WHO [ 14] (World Health Organization, 2010), USA [ 15] (Department of Health and Human Services, 2018), Canada [ 16] (Canadian Society for Exercise Physiology, 2011), Germany [ 17], United Kingdom-UK [ 18] (Department of Health, Physical Activity, Health Improvement and Protection, 2011), Australia [ 19], the Netherlands [ 20], New Zealand (Ministry of Health, 2013) [ 21] and India [ 22].

Flow chart for the literature review and study selection process

Targeted population and guidelines development process

The targeted population included adults aged 50 years and older. The Egyptian Academy of Bone and Muscle Health was the organizing body. The professionals involved were experts in rehabilitation medicine, physical activity and health promotion, epidemiology, guidelines development, psychology as well as fall prevention. Consensus was achieved following multiple online meetings followed by online comprehensive feedback.

Results of the systematic review

The exercise prescription

This guideline provides evidence-based public health physical activity programs constructed in a systematic and individualized style in terms of frequency, intensity, time, type, volume, and progression that offer significant health benefits and mitigate health risks. This has been identified as the FITT-VP formula or principle. The FITT is a good approach to monitor the individual person's exercise program and progression. The parameters of the exercise prescription are shown in Table 2.

Baseline assessment and goal setting

The initial step to implement changes in the subject's physical activity is best predicted by evaluating the person's baseline activities and readiness to change. This should be carried out using an evidence-informed model with the goal of identifying: (1) the current level of exercise, (2) the presence or absence of asymptomatic/symptomatic known disease, and (3) desired intensity of exercise. Subsequently, the healthcare professional should educate the individual about the benefits of physical activity, changing some of the current behaviors, and motivate him/her with relevant personal goals, such as improving physical function or strength, balance, preventing falls, management of weight, improving chronic disease management, and preventing falls. Consequently, the individual should be able to agree with the healthcare professional on an initial set of achievable goals. Table 3 shows the developed Arabic Sedentary, Activity, Sleep Assessment (SASA) questionnaire, and associated explanatory figures for the assessment and monitoring of the exercise level of the individual subject (Supplement 1 shows the English copy of the SASA questionnaire).

Statements

Guided by the key questions, the systematic review was carried out to identify the effects of the 4 behaviors on the identified health outcomes. These are summarized in Table 4.

The Egyptian 24-h movement guidelines

Considering the overall health benefits, adults aged 50 years and older should be physically active every day, ensure sufficient sleep, and minimize sedentary behavior. Greater health benefits can be achieved by replacing sedentary behavior with extra physical activity and trading light physical activity for more moderate to vigorous physical activity, whilst continuing to have adequate sleep.

Overarching principles

All persons 50 years and above should keep moving/physically active as much and as frequently as possible. They should practice physical exercises on a regular basis at least 5 days a week.

Exercise programs should be customized to the individual's needs. No common exercise program can fit all.

Individual's medical and physical status are considerable factors in choosing the parameters of the adopted exercise program.

The heavier the exercise level, the greater the benefit. However, light-moderate physical activity is better than nothing.

Benefits of physical activity included a reduced risk of falling and the potential to develop a fracture; also reduced risk of several chronic health conditions, provides longer healthy life span, improved quality of life, and reduced overall mortality rate.

Sedentary behavior in the elderly is the biggest opponent of healthy aging.

Whenever appropriate, daily physical activity is advised.

Baseline assessments for functional ability, quality of life, sarcopenia, and falls risk are important and should be carried out for every older adult.

The physical activity programs are dynamic and progressive in nature, including exercises with a progressive intensity focusing on daily mobility routine with a flexible frequency.

Gradual increase in physical activity is the safest method for minimizing the risk of injury. The optimum approach is to start with moderate-intensity activities, with a progressive increase first in terms of activity duration, then in frequency, and finally in intensity. This would lead to increased benefits with a low incidence of side effects.

Physically inactive people but otherwise healthy and asymptomatic may start with light- to moderate-intensity exercise. In the absence of symptoms, they should progress gradually as advised by the exercise prescription guidelines.

Progression of physical activity over time is not only important for more health benefits but also for motivation and adherence.

Active older adults may engage in physical activities beyond the identified thresholds.

Consulting an experienced healthcare professional/practitioner is advisable before increasing the physical load is recommended for healthy older adults.

Multicomponent physical activities integrating many types of exercises (strengthening, endurance, and balance exercises) are advised.

Injuries and adverse effects during all forms of physical activity are negligible, however appropriate safety practices must be ensured.

Structured and group-based intervention/rehabilitation is advised for improving motivation, reducing cost, understaffing, and improving long-term adherence.

The guidelines and physical activities advised should be promoted at several levels individual, family, community, caregivers, technology, and policymakers.

No current recommendations support the use of personal devices such as wearables

Guidelines

To achieve a healthy 24-h, adults aged 50 years or older should:

General elderly population

1. 1.
Physical activity

1.1 Aerobic training:

Thirty to 60 min a day of moderate-intensity aerobic activity at least 5 days/week; or

Fifteen to 30 min a day of high-intensity aerobic activity at least 5 days/week; or

an equivalent mix of moderate- and high-intensity aerobic workouts all around the week.

1.2 Resistance training:

Non-consecutive 2 to 3 days a week of resistance training should be recommended.

Each exercise should include 2-3 sets of resistance exercises working on multi-joint exercises per major muscle group and of intensity equal to 70-85% of 1 repetition maximum (1RM).

Performing the muscle strengthening exercises in the positions and forms of real-life daily activity movements is prescribed as functional strengthening exercises. This type of exercise is recommended as well as regular strengthening exercises.

1.3 Balance training:

2. 2.
Sedentary behavior:

All adults including older adults are advised to decrease their sedentary time and push their bodies to move as frequently as possible; therefore, the individual should:

3. 3.
Sleep:

4. 4.
Integrated behavior:

All adults and older adults are advised to practice regular frequent multicomponent physical training exercise that involves a combination of aerobic, strengthening, and balance exercises in different levels of intensity. This is besides decreasing the inactive time and ensuring good sleep quality.

Elderly people with special conditions

1.
People with chronic conditions

Among older adults, chronic comorbidities and illnesses such as cancer, obesity, diabetes, cardiovascular, hyperlipidemia, and arthritis are the leading causes of death and/or disability among older adults [ 35]. There is no direct evidence of specific sedentary behavior for these subpopulations. Hence, the evidence for sedentary behavior recommendations for general populations remains applicable to them [ 14]. On the other hand, special precautions should be considered when offering an exercise prescription for those patients with chronic conditions. Table 5 shows the suggested exercise prescription modifications and special considerations and physical activity recommendations for patients with specific medical conditions.

2.
Patients at high risk of fragility fracture

Strict caution should be practiced when prescribing moderate (e.g., running, racquet sports, skipping) or high (e.g., drop or high vertical jumps) impact exercise for these patients.

Safety or efficacy is questionable in individuals with a history of fractured vertebrae or Major osteoporotic fracture FRAX score of 15% calculated by the Egyptian FRAX.

The most dangerous movements especially for those with vertebral fracture are those that entail flexion and twisting of the spine or rapid, repetitive, sustained, weighted, or end range of motion

3.
Frail adults/older adults

Multicomponent exercise program including progressive resistance training works well for frailty fighting.

Before prescribing the exercise dose, measuring aerobic fitness by cardiopulmonary exercise testing is recommended to determine exercise tolerance.

Progression or regression of exercise intensity is dependent on the person's tolerance and general condition is recommended according to the person's tolerance and health condition.

Resistance training has better results if accompanied by the intake of the proper amount of protein.

Specific structured exercise programs such as modified tai chi or certain types of yoga could prevent injury from falls.

Supervised, group-based exercising protocols are advised as they may enhance motivation and adherence

Homed-based and even bedside exercises are possible options to promote physical activity in very frail old adults.

Table 6 shows a summary, with examples of the Egyptian "Healthy 24-Hour" movement guideline.

Discussion

Preceded only by tobacco use, hypertension, and high blood glucose levels, physical inactivity was categorized as the fourth leading risk factor for noncommunicable diseases [ 36, 37], triggering about 41 million deaths annually (correspondent to 74% of all deaths globally) [ 38]. New research studies recommend that the structure of movement behaviors within a 24-h period may have a strong effect on health across the lifespan. Consistent with this paradigm of integrated movement behavior, the WHO as well as several countries across the world have developed "24-h movement guidelines" for different age groups. The purpose of this work was to develop "the Egyptian 24-h movement guidelines" for adults 50 years and older. This document is proposed for use by policymakers, health professionals, researchers, and interested individuals. Figure 2 shows the logo of the proposed national campaign. This 24-h movement guideline is relevant to all Egyptians aged 50 years or older, irrespective of gender, socio-economic status, or cultural background. The guideline development process adhered to the "Clinical, Evidence-based, Guideline" framework used to develop previous national guidelines in Egypt [ 9].

The logo of the proposed national campaign in Egypt: Movement is a blessing "الحركه بركه" composed of 4 s (strong, step, sit, and sleep)

The principal concept of the developed 24-h movement guideline is that the structure of all movement behaviors throughout the day is strongly correlated to the individual's health, and delivers exclusive, evidence-based opportunities to participate in movement behavior integrations that meet the individual's requirements and personal preferences. This comes in agreement with the previously published 24-h guidelines published by the WHO and 8 other health authorities worldwide [ 14, 15, 17, 18, 19, 20, 21, 22]. This paradigm represents a major change in the previous basic understandings, as it shifts away from focussing on a sole movement behavior to the combination of all the movement behaviors. In turn, this endorses the growing body of evidence advocating that the mix of movement behaviors over a 24-h day impacts a wide range of health outcomes [ 39, 40, 41, 42].

The disengagement from any form of physical activity is not only prevalent in Egypt. In fact, it is an international challenge. Whilst 35% of older adult men and 55% of women have been reported as physically inactive, more than 40% of the adult European population do not engage in any form of physical activity, and only 8% regularly exercise [ 43]. Sedentary behavior and physical inactivity are directly linked to increased prevalence of cardiovascular disease [ 44], obesity, diabetes [ 45], and autoimmune rheumatic diseases [ 46]. WHO data [ 8] indicate that 86% of deaths in Egypt are due to non-communicable diseases (NCDs) mortality, with cardiovascular disease followed by cancer being the main causes on top of the list. This highlights the importance of having a national 24-h movement guideline in Egypt, particularly, increasing levels of physical activity have been reported as a catalyst in the reduction of the above consequences.

In concordance with the earlier published guidelines [ 5, 29], the developed Egyptian 24-h movement guideline, revealed similar physical activity components for both adults and older adult age groups. Demographic data from Egypt reveal that life expectancy at birth for men is 68.5 years whereas for women it is 73.2 years. Results of a recent study in Egypt revealed that patients aged 50 years and older are at higher risk of falling and sustaining a fragility fracture [ 47]. This was the reason for including Egyptian adults aged 50 years and older in this guideline. However, this guideline may not be appropriate for adults aged 50 years or older living with a disability or a medical condition; these individuals should seek advice from their treating health professional for guidance. The guidelines are meant to help in the decision-making process but do not clarify all uncertainties of patient care. Although adopting this guideline can be challenging at times; progressing towards any of the targets identified in this guideline will result in some health benefits.

These guidelines stated that enhancing physical activities among adults and older adults should be promoted at different levels. This can be at the individual level, based on instinct-individual motivation; or community-based (families, friends, caregivers, policy-makers), or health professionals (individually or in small groups in generic or tailored exercise regimen) to technology (devices that assess activity, e-health or m-health solutions, mixed reality platform for increasing motivation). A logo (Fig. 2) has been developed by the Egyptian Academy of Bone and Muscle Health to spread the word and enhance the involvement of Egyptian adults and older adults at a national level. Evidence-based strategies could enhance adherence and monitoring could facilitate success.

In conclusion, there is a large body of evidence for the benefits of physical activities for healthy aging, and this is expressed in the development of several guidelines for different health conditions that stress the importance of incorporating physical activities for adults and older adults. This is endorsed by the fact that promoting physical activity, particularly in older adults could be more beneficial as health gains could come faster than in other age groups. physical inactivity results in limitations in body functioning and mobility and reduces the opportunity for independent living in later life. Physical activity in both adults and older adults, regardless of chronic disease, was reported to be associated with delayed physical disability and the maintenance of independent living. The developed Egyptian 24-h movement guideline endorses the recommendations for physical activity, sedentary behavior, and sleep which should be combined into a single public health domain that incorporates movement across the full 24-h day. A national campaign should be launched under the title "Moving more make your life matter".

Availability of data and materials

Available upon reasonable request.

Abbreviations

BMD:

Bone mineral density

FRAX:

Fracture Risk Assessment

NCDs:

Non-communicable diseases

PICO:

Population, Intervention, Comparator and Outcomes

RCT:

Randomized controlled trials

WHO:

World Health Organization

References

1. Warburton DE, Nicol C, Bredin SS (2006) Health benefits of physical activity: the evidence. Can Med Assoc J 174:801-809. https://doi.org/10.1503/cmaj.051351

Article Google Scholar

2. Luo L, Cao Y, Hu Y, Wen S, Tang K, Ding L, Song N (2022) The associations between meeting 24-Hour Movement Guidelines (24-HMG) and self-rated physical and mental health in older adults-cross sectional evidence from China. Int J Environ Res Public Health 19(20):13407. https://doi.org/10.3390/ijerph192013407

3. The rights and wellbeing of older persons in Egypt. https://arabstates.unfpa.org/sites/default/files/pub-pdf/country_profile_-_egypt_27-10-2021_0.pdf Accessed on 7 Mar 2024

4. El Miedany Y, Mahran S, Elwakil W (2023) One musculoskeletal health: towards optimizing musculoskeletal health in Egypt-how to be a bone and muscle builder by the Egyptian Academy of Bone Health and Metabolic Bone Diseases. Egypt Rheumatol Rehabil 50:33. https://doi.org/10.1186/s43166-023-00199-5

Article Google Scholar

5. Abdelkawy K, Elbarbry F, El-Masry SM, Zakaria AY, Rodríguez-Pérez C, El-Khodary NM (2023) Changes in dietary habits during Covid-19 lockdown in Egypt: the Egyptian COVIDiet study. BMC Public Health 23(1):956. https://doi.org/10.1186/s12889-023-15777-7

6. WHO report on physical activity profile in Egypt (2022) https://cdn.who.int/media/docs/default-source/country-profiles/physical-activity/physical-activity-egy-2022-country-profile.pdf?sfvrsn=50db9547_5&download=true. Accessed on 7 Mar 2024

7. El Miedany Y, Abu-Zaid MH, El Gaafary M et al (2022) Egyptian guidelines for the treatment of Rheumatoid Arthritis - 2022 update. Egypt Rheumatol Rehabil 49:56. https://doi.org/10.1186/s43166-022-00153-x

Article Google Scholar

8. Schardt C, Adams MB, Owens T, Keitz S, Fontelo P (2007) Utilization of the PICO framework to improve searching PubMed for clinical questions. BMC Med Inform Decis Mak 2007(7):16

Article Google Scholar

9. OCEBM Levels of Evidence Working Group (2011) The Oxford levels of evidence 2. Oxford Centre for Evidence-Based Medicine, Oxford, UK

Google Scholar

10. Physical Activity (2018) Guidelines for Americans, 2nd edition. U.S. Department of Health and Human Services. Physical Activity Guidelines for Americans, 2nd edition. Washington, DC: U.S. Department of Health and Human Services; https://health.gov/sites/default/files/2019-09/Physical_Activity_Guidelines_2nd_edition.pdf. Accessed 30 April 2024

11. Canadian Society for Exercise Physiology (2011) Canadian Physical Activity Guidelines and Canadian Sedentary Behaviour Guidelines. http://www.csep.ca/en/guidelines/read-the-guidelines

12. Rütten A & Pfeifer K (2016) National Recommendations for Physical Activity and Physical Activity Promotion FAU University Press. https://opus4.kobv.de/opus4-fau/home

13. Department of Health, Physical Activity, Health Improvement and Protection Start Active, Stay Active:A report on physical activity from the four home countries'Chief Medical Officers. London: Department of Health, Physical Activity, Health Improvement and Protection; 2011. https://www.sportengland.org/media/2928/dh_128210.pdf

14. Brown WJ, Moorhead GE, Marshall AL (2005) Choose Health:Be Active:a physical activity guide for older Australians. Commonwealth of Australia and the Repatriation Commission, Canberra

Google Scholar

15. Weggemans RM, Backx FJG, Borghouts L, Chinapaw M, Hopman MTE, Koster A et al (2018) Committee Dutch Physical Activity Guidelines 2017. The 2017 Dutch Physical Activity Guidelines. Int J BehavNutr Phys Act 15(1):58

Article Google Scholar

16. Ministry of Health Guidelines on Physical Activity for Older People (aged 65 years and over) Wellington: Ministry of Health; 2013. https://www.health.govt.nz/publication/guidelines-physical-activity-older-people-aged-65-years-and-over.

17. Misra A, Nigam P, Hills AP, Chadha DS, Sharma V, Deepak KK et al (2012) Physical Activity Consensus Group. Consensus physical activity guidelines for Asian Indians. Diabetes TechnolTher 14(1):83-98

Article Google Scholar

18. El-Kotob, R., Ponzano, M., Chaput, J.-P., Janssen, I., Kho, M.E., Poitras, V.J., et al. (2020) Resistance training and health in adults: an overview of systematic reviews. Appl. Physiol. Nutr. Metab. 45(10 Suppl. 2): this issue. https://doi.org/10.1139/apnm-2020-0245

19. Ross R, Chaput JP, Giangregorio LM, Janssen I, Saunders TJ, Kho ME, Poitras VJ, Tomasone JR, El-Kotob R, McLaughlin EC, Duggan M, Carrier J, Carson V, Chastin SF, Latimer-Cheung AE, Chulak-Bozzer T, Faulkner G, Flood SM, Gazendam MK, Healy GN, Katzmarzyk PT, Kennedy W, Lane KN, Lorbergs A, Maclaren K, Marr S, Powell KE, Rhodes RE, Ross-White A, Welsh F, Willumsen J, Tremblay MS (2020) Canadian 24-Hour Movement Guidelines for Adults aged 18-64 years and Adults aged 65 years or older: an integration of physical activity, sedentary behaviour, and sleep. Appl Physiol Nutr Metab 45(10 (Suppl. 2):S57-S102. https://doi.org/10.1139/apnm-2020-0467

20. Sherrington C, Fairhall NJ, Wallbank GK, Tiedemann A, Michaleff ZA, Howard K et al (2019) New Cochrane review assesses the benefits and harms of exercise for preventing fall s in older people living in the community. Saudi Med J 40(2):204-205

Google Scholar

21. 2018 Physical Activity Guidelines Advisory Committee (2018) 2018 Physical Activity Guidelines Advisory Committee Scientific Report, Washington, DC, USA. https://health.gov/sites/default/files/2019-09/PAG_Advisory_Committee_Report.pdf Accessed on 8 Mar 2024

22. Chaput JP, Dutil C, Featherstone R, Ross R, Giangregorio LM, Saunders TJ et al. (2020) Sleep duration and health in adults: an overview of systematic reviews. Appl. Physiol. Nutr. Metab 45(10 Suppl. 2). https://doi.org/10.1139/apnm-2020-0034

23. Janssen I, Clarke AE, Carson V, Chaput JP, Giangregorio LM, Kho ME, et al. (2020) A systematic review of compositional data analysis studies examining associations between sleep, sedentary behaviour, and physical activity with health outcomes in adults. Appl. Physiol. Nutr. Metab 45(10 Suppl. 2): https://doi.org/10.1139/apnm-2020-0160

24. Kochanek KD, Murphy SL, Xu J, Arias E (2014) Mortality in the United States, 2013. NCHS Data Brief 178:1-8

Google Scholar

25. WHO. Global status report on noncommunicable diseases (2014) World Health Organization. https://www.who.int/publications/i/item/9789241564854. Accessed 9 Mar 2024

26. World Health Organization (‎2009)‎ Global health risks : mortality and burden of disease attributable to selected major risks. World Health Organization. https://iris.who.int/handle/10665/44203. Accessed 9 March 2024

27. WHO. Physical activity. https://www.who.int/news-room/fact-sheets/detail/physical-activity Accessed on 9 Mar 2024

28. McGregor DE, Carson V, Palarea-Albaladejo J, Dall PM, Tremblay MS, Chastin SFM (2018) Compositional analysis of the associations between 24-h movement behaviours and health indicators among adults and older adults from the Canadian health measure survey. Int J Environ Res Publ Health 15(8):1779

Article Google Scholar

29. Nikitas C, Kikidis D, Bibas A, Pavlou M, Zachou Z, Bamiou DE (2022) Recommendations for physical activity in the elderly population: a scoping review of guidelines. J Frailty Sarcopenia Falls 7(1):18-28. https://doi.org/10.22540/JFSF-07-018

30. (2014) European Commmision Eurobarometer on Sport and Physical Activity. Brussels. http://europa.eu/rapid/press-release_MEMO-14-207_el.htm

Download references

Funding

All authors declare that they did not receive any kind of funding.

Author information

Authors and Affiliations

1. Canterbury Christ Church University, Canterbury, England, UK

Yasser El Miedany

2. Darent Valley Hospital, Kent, England

Mathias Toth

3. Institute of Medical Science, Canterbury Christ Church University, Canterbury, UK

Susan Plummer

4. Community and Public Health, Ain Shams University, Cairo, Egypt

Maha El Gaafary

5. Physical Medicine, Rheumatology and Rehabilitation, Assiut University, Assiut, Egypt

Safaa Mahran

6. Lecturer Physical Medicine, Rheumatology and Rehabilitation, Alexandria University, Alexandria University, Alexandria, Egypt

Walaa Elwakil

7. H. senior Clinical Lecturer, King's college, London, United Kingdom

Mathias Toth

Contributions

All the authors contributed to the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Yasser El Miedany.

Ethics declarations

Ethics approval and consent to participate

The Clinical, Evidence-based, Guidelines (CEG) initiative protocol was approved by the local ethical committee. Ethical approval code: 34842/8/21, ethical board Tanta University.

Consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

Prof. Safaa Mahran and Yasser El Miedany are from the editorial board of the journal. All other authors declare that they have no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1: Supplement 1. Self-reported sedentary, physical activity and sleep quality assessment questionnaire for the evaluation and monitoring of the exercise level of the individual person.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Reprints and permissions

About this article

Cite this article

El Miedany, Y., Toth, M., Plummer, S. et al. The development of the Egyptian 24-h movement guidelines for adults aged 50 years and older: an integration of sleep, sedentary behavior, and physical activity by the Egyptian Academy of Bone and Muscle Health. Egypt Rheumatol Rehabil 51, 31 (2024). https://doi.org/10.1186/s43166-024-00259-4
Download citation

Share this article

Anyone you share the following link with will be able to read this content:

Get shareable link

Provided by the Springer Nature SharedIt content-sharing initiative

Keywords

# data[].attributes.attachment_link.title
The development of the Egyptian 24-h movement guidelines for adults aged 50 years and older: an integration of sleep, sedentary behavior, and physical activity by the Egyptian Academy of Bone and Muscle Health - Egyptian Rheumatology and Rehabilitation

# data[].attributes.attachment_link.description
Background With the vision of healthy aging, the Egyptian Academy of Bone and Muscle Health followed an established guideline development process to create the Egyptian 24-h movement clinical guideline for adults aged 50 years and older adults. This guideline highlights the significance of movement behaviors across the whole 24-h day.

# data[].attributes.headline
Prostatic stents: a narrative review of current evidence

# data[].attributes.subject
Prostatic stents: a narrative review of current evidence

# data[].attributes.headline
Prevalence of Prehypertension, Hypertension, and its Determinants Among Young Adults in Enugu State, Nigeria.

# data[].attributes.subject
Prevalence of Prehypertension, Hypertension, and its Determinants Among Young Adults in Enugu State, Nigeria.

# data[].attributes.attachment_link.readable_text
Main Article Content

Obinna C Nwoke

Department of Pharmacology and Therapeutics, Faculty of Medical Sciences, College of Medicine, University of Nigeria, Nsukka, Nigeria

Department of Pharmacology and Therapeutics, Faculty of Medical Sciences, College of Medicine, University of Nigeria, Nsukka, Nigeria.

Acute Medicine Department, Darent Valley Hospital, Dartford, United Kingdom

Ndubuisi Hospital and Maternity, Achara Road, Nsukka, Enugu State, Nigeria

Department od Medical Laboratory Sciences, Faculty of Health Sciences and Technology, College of Medicine, University of Nigeria, Nsukka, Nigeria.

Department of Pharmacology and Therapeutics, Faculty of Medical Sciences, College of Medicine, University of Nigeria, Nsukka, Nigeria

Keywords

Prehypertension, Hypertension, Medical Students, Risk Factors, Blood Pressure

Abstract

Background: Emerging epidemiological data suggest that Hypertension (HTN) has become a significant public health challenge in sub-Saharan Africa. HTN in young adults is a problem lacking relevant attention because it is still erroneously considered a disease of the old. This study aimed to determine the prevalence of hypertension and its associated risk factors in undergraduate medical students at the University of Nigeria, Enugu Campus, Enugu State, Nigeria.
Methodology: This was a cross-sectional study conducted between March and April 2021. This study recruited 279 consenting medical students (136 males and 143 females) aged 18-35 years. They were administered with a structured questionnaire. Data on sociodemographic information and risk factors for hypertension were collected. Blood pressure, waist circumference, weight, height, and body mass index were measured using standard methods. All data collected were carried out following the Institutional ethical guidelines and that of the Helsinki as revised in 2000. Data were analyzed using IBM Statistical Package for Social Sciences version 25, and statistical tools employed include descriptive statistics and Chi tests. Results were recorded as mean standard deviation, and statistical significance was taken at p<0.05. Results: This present study has shown a prevalence rate of 19.93% for hypertension. Isolated diastolic hypertension constituted a greater burden with a prevalence of 13.65% than systolic Hypertension (0.74%) and systolic-diastolic Hypertension 5.4%. The prevalence of prehypertension was 48.7%, with a higher incidence observed in females (25.8%), individuals aged 21-25 years (26.4), and those with normal BMI (35.1%). A significant association was observed between the stage of hypertension and gender (p = 0.005), and age category (p = 0.037). Of the examined cohort, 7.75% were underweight, 16.5% overweight, and 2.2% obese. Notably, systolic, and diastolic blood pressure, weight, as well as waist circumference showed significant (p = 0.01, p = 0.007, p =0.01 and p<0.0001 respectively) increases concomitant with advancing age.
Conclusion: There is an increased prevalence of prehypertension and hypertension among young adults. This calls for a comprehensive national screening, public enlightenment, and targeted prevention programs that foster healthy lifestyle behaviours, physical activity, and healthy eating among students

Abstract 1 | PDF Downloads 0

References

1. Chijioke C, Anakwue R, Okolo T, Ekwe E, Eze C, Agunyenwa C, Nwosu N, amah C, Nwadike K, Chijioke U. Awareness, treatment, and control of hypertension in primary health care and secondary referral medical outpatient clinic settings at Enugu, Southeast Nigeria. Inter. J. Hypertens.2016: 1-5. http://dx.doi.org/10.1155/2016/5628453.
2. Nwaneli CU, Omejua EG. Clinical presentation and aetiology of hypertension in young adults in Nnewi South East Nigeria. AFRIMEDIC Journal 2010:1(1):24-6.
3. Choi J, Oh C, Shim SJS, Kim HS and Kim M. Reduction in prevalence of hypertension and blood heavy metals among curry-consumed Korean. TJEM.2018: 244:219-29.
4. Pawliczak F, Bielecka-Dabrowa A, Maciejewski M, Banach M. Treating mild hypertension in young adults: is pharmacotherapy necessary? Exp Opi on Pharmaco.2020: 21(10):1115-8.
5. Xu J, White AJ, Niehoff NM, O'Brien M, Sandler DP. Airborne metals exposure and risk of hypertension in the Sister Study. Environ Res. 2020:119: 110144
6. Odili AN, Chori BS, Danladi B, Nwakile PC, Okoye IC, Abdullah U, et al. Prevalence, Awareness, Treatment and Control of Hypertension in Nigeria: Data from a Nationwide Survey 2017. Glob. Heart; 2020;15(1):47.
7. Banigbe BF, Itanyi IU, Ofili EO, Ogidi AG, Patel D, Ezeanolue EE. High prevalence of undiagnosed hypertension among men in North Central Nigera: Results from the Healthy beginning Initiative. PLoS One 2020;15 (11): e0242870. 1-15.
8. Oguanobi NI, Ejim ECE, Onwubere BJB, Ike SOS, Anisiuba BBC, Ikeh VVO, et al. Pattern of cardiovascular disease amongst medical admissions in a regional teaching hospital in Southeastern Nigeria. Nigerian Journal of Cardiology. 2013;10:77-80. https://doi.org/10.4103/0189-7969.127005.
9. Okubadejo NU, Ozoh OB, Ojo OO, Akinkugbe AO, Odeniyi IA, Adegoke O, Bello BT, Agabi OP (2019). Prevalence of hypertension and blood pressure profile amongst urban-dwelling adults in Nigeria: a comparative analysis based on recent guideline recommendations. Clin Hypertens 2019;25:7. https://doi.org/10.1186/s40885-019-0112-
10. Umegbolu EI, Ogamba JO. Primary hypertension in young adults (18-40 years) in Enugu State, Southeast Nigeria: a cross-sectional study. IJCMPH 2016; 3(10):2825-31.
11. Hinton TC, Adams ZH, Baker RP, Hope KA, Paton JFR, Hart EC, Nightingale AK. Investigation and treatment of high blood pressure in young people. Too much medicine or appropriate risk reduction? Hypertension. 2020; 75:16-22.
12. Ujunwa AF, Ikefuna NA, Nwokocha RCA, Chinawa MJ. Hypertentsion and prehypertension among adolescents in secondary schools in Enugu, South East Nigeria. Ital. J Pediatr.2013; 39(70):1-6.
13. Ezeudu CE, Chukwuka JO, Ebenebe JC, Igwe WC, Egbuonu I. Hypertension and prehypertension among adolescents attending secondary schools in urban area of South- East, Nigeria. PAMJ. 2018;31(145): 1-9.
14. Ugochukwu EF, Onubogu CU, Ofora VC, Okeke KN, Uju CM. Blood pressure profiles and determinants of hypertension among public secondary school students in Nnewi, Southeast Nigeria. EJMED. 2020;2(3): 1-7.
15. Jones SWE, Esack I, Mangena P, Rayner LB. Hypertension in adolescents and young adults referred to a tertiary hypertension clinic in cape Town, South Africa. Medicine.2020; 99(48): 1-5.
16. Liu X, Xiang Z, Shi X, Schenck H, Yi X, Ni R, Liu C. The risk factors of high blood pressure among youg adults in the Tujia-Nationality settlement of China. Biomed. Res. Int. 2017: 1-6.
17. Dahiru T, Aliyu A, Kene TS. Statistics in medical research: Misuse of sampling and sample size determination. Ann. Afri. Med.. 2006; 5(3):158-61.
18. Onwubere BJC, Ejim EC, Okafor CI, Emehel A, Mbah AU, Onyia U, Mendis S. Pattern of blood pressure indices among the residents of a rural community in South East Nigeria. Int. J. Hypertens 2011:ID 621074. 1-6. Doi:10.4061/2011/621074.
19. Donato KA. Executive summary of the clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults. Arch. Intern. Med. 1998; 158:1855-67.
20. Chobanian AV, Bakris GL, Black H.R, Cushman WC, Green LA, Izzo J.L, et al . The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: The JNC 7 Report. JAMA .2003; 289:2560-72.
21. Peters JL, Fabian MP, Levy JI. Epidemiologically-informed cumulative risk hypertension models simulating the impact of changes in metal, organochlorine, and non-chemical exposures in an environmental justice community. Environ Res. 2019;176:108544.
22. Adeloye D, Owolabi EO, Ojji DB, Auta A, Dewan MT, Olanrewaju TO, et al. Prevalence, awareness, treatment, and control of hypertension in Nigeria in 1995 and 2020: A systematic analysis of current evidence. J Clin Hypertens (Greenwich). 2021 May;23(5):963-977.
23. Ondimu DO, Kikuvi GM, Otieno WN. Risk factors for hypertension among young adults (18-35) years attending in Tenwek mission hospital, Bomet County, Kenya in 2018. PAMJ.2019; 33:210 doi:10.11604/pamj.2019.33.210.18407.
24. De Venecia T, Lu M, Figueredo VM. Hypertension in young adults. Postgrad Med. 2016;128(2):201-7.
25. Chattopadhyay A, Taraphdar P, KumarSahu B, Maulik S, Ghosh R, Sinha A, Biswas M. A study on prevalence of Hypertension and its related risk factors among undergraduate medical students in Kolkata. IOSR-JDMS.2014;13: 01-07.
26. Abd-Elaziz KM, Dewedar SA, Sabbour S, El Gafaary MM, Marzouk DM, Aboul Fotouh A, Allam MF. Screening for hypertension among adults: community outreach in Cairo, Egypt. J Public Health (Oxf). 2014;37(4), 701-6.
27. AlWabel AH, Almufadhi MA, Alayed FM, Aloraini A.Y, Alobaysi HM, Alawi RM. Assessment of hypertension and its associated risk factors among medical students in Qassi University. Saudi J. Kidney Dis Transplant 29:1100-8.
28. Isezuo SA, Sabir AA, Ohwovorilole AE, Fasanmade OA. Prevalence, associated factors and relationship between prehypertension and hypertension: a study of two ethnic African populations in Northern Nigeria 2011. J Hum Hypertens. 25: 224-230.
29. Tadesse T, Alemu H. Hypertension and associated factors among university students in Gondar, Ethiopia: a cross-sectional study. BMC Public Health 14, 937 (2014). https://doi.org/10.1186/1471-2458-14-937
30. Al-Majed H, Sadek A: Pre-hypertension and hypertension in college students in Kuwait: a neglected issue. J Family Community Med. 2012, 19: 105-10.4103/2230-8229.98296.
31. Hajer A-S, Jalila El A, Pierre T, Habiba B, Sabrina E, Francis D, Noureddine A, Bernard M. Blood pressure and associated factors in a North African adolescent population. A national cross-sectional study in Tunisia. BMC Public Health. 2012, 12: 98-10.1186/1471-2458-12-98.
32. Van der Sande MA, Milligan PJ, Nyan OA, Rowley JT, Banya WA, Ceesay SM, Dolmans WM, Thien T, McAdam KP, Walraven GE: Blood pressure patterns and cardiovascular risk factors in rural and urban Gambian communities. J Hum Hypertens. 2000, 14: 489-496. 10.1038/sj.jhh.1001050.
33. Awoke A, Awoke T, Alemu S, Megabiaw B: Prevalence and associated factors of hypertension among adults in Gondar. Northwest Ethiopia: a community-based cross-sectional study. BMC Cardiovasc Disord. 2012, 12: 113-10.1186/1471-2261-12-113.
34. World Health Organisation (2013). A global brief on hypertension, Geneva: WHO Press.2013.

Article Details

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

This is an open-access journal and articles are distributed under the terms of the Creative Commons Attribution Non-Commercial Share-Alike License 4.0. This licence allows users to download and share, remix, tweak and build upon the article for non-commercial purposes, so long as the original authorship is acknowledged and the new creations are licensed under identical terms.

# data[].attributes.attachment_link.description
Background: Emerging epidemiological data suggest that Hypertension (HTN) has become a significant public health challenge in sub-Saharan Africa. HTN in young adults is a problem lacking relevant attention because it is still erroneously considered a disease of the old.

# data[].attributes.headline
Meaningful patient engagement in inflammatory arthritis: development of the Patient Motivation Questionnaire

# data[].attributes.subject
Meaningful patient engagement in inflammatory arthritis: development of the Patient Motivation Questionnaire

# data[].attributes.attachment_link.readable_text
Abstract

The objective of this study is to develop a questionnaire for evaluating the patient's "motivation" and assess the psychometric properties of that measure in patients with chronic inflammatory arthritis. Using Rasch analysis and questions item pool, content analysis, and semi-structured group discussion, the questionnaire was developed including 10-item scale (0-10 on VAS scale). Construct validity was assessed by correlating the questionnaire score to parameters of disease activity (DAS-28, ASDAS, and DAPSA scores), functional disability, quality of life, patient self-helplessness measure, as well as the patients' compliance to therapy. Reliability and comprehensibility and sensitivity to change were also assessed. The questionnaire was assessed in 432 RA, 415 psoriatic arthritis patients, and 232 ankylosing spondylitis patients. Dimensionality analysis revealed a 1-factor solution, explaining 98% of the total variance. It showed acceptable validity as it correlated significantly with disease activity measures: DAS-28: r = −0.85, ASDAS: r = −0.86, and DAPSA: r = −0.89. It also correlated significantly with functional disability score: r = −0.91, QoL: r = −0.90, as well as patient self-helplessness: r = −0.88. The questionnaire was reliable (Cronbach's alpha 0.958) and had no misfitting items. In addition, it was comprehensible (9.4) and sensitive to change ( p < 0.01). The patient motivation score showed significant ( p < 0.01) variation with the medication compliance. The measure is a patient-reported tool that is valid, reliable, comprehensible, and unidimensional scale that reflects the patients' motivation and engagement. The measure has good psychometric properties indicating that it can be used at the individual patient level to tailor management and monitor changes.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

Article Open access

Article Open access

References

1. Ruta DA, Garratt AM, Russell IT (1999) Patient centered assessment of quality of life for patients with four common conditions. Qual Health Care 8:22-29

Article CAS PubMed PubMed Central Google Scholar

2. Garratt AM, Ruta DA (1999) The Patient Generated Index. In: Joyce CRB, O'Boyle CA, McGee HM (eds). Individual quality of life: Approaches to conceptualisation and assessment. Amsterdam Harwood Academic Publishers;105-18

3. Ahn, Y. H., Yi, C. H., Ham, O. K., & Kim, B. J (2014) Psychometric properties of the Korean version of the "Patient Activation Measure 13"(PAM13-K) in patients with osteoarthritis. Eval Health Prof: 0163278714540915

4. Barello, S., & Graffigna, G (2014) Engaging patients to recover life projectuality: an Italian cross disease framework. Qual Life Res; doi: 1-10. 10.1007/s11136-014-0846-x

Download references

Acknowledgements

We express thanks to all participants, our colleagues, research assistants, and nurses for their cooperation and help to bring this research to its final conclusions. Special thanks to Ms. Deborah Palmer, advanced nurse practitioner, North Middlesex University Hospital, London for her contribution in the work.

Author information

Authors and Affiliations

1. Rheumatology and Rehabilitation, Ain Shams University, Cairo, Egypt

Y. El Miedany, Sally Youssef & Nadia El Aroussy

2. Darent Valley Hospital, Dartford, Kent, England, DA2 8DA, UK

Y. El Miedany

3. Public Health and Community Department, Ain Shams University, Cairo, Egypt

Maha El Gaafary

Contributions

All authors had a substantial contribution to the conception and design of the study, drafting/revising of the article and final approval of the version to be published.

Corresponding author

Correspondence to Y. El Miedany.

Ethics declarations

Local ethical and methodological protocols for approval of the study were followed. All patients who participated in the study signed an informed consent according to the Declaration of Helsinki (at the General Assembly in October 2008).

Disclosures

None.

Ethics approval

The study was approved by the Ain Shams University Research Ethics Board.

Electronic supplementary material

About this article

Cite this article

El Miedany, Y., El Gaafary, M., Youssef, S. et al. Meaningful patient engagement in inflammatory arthritis: development of the Patient Motivation Questionnaire. Clin Rheumatol 43, 1793-1801 (2024). https://doi.org/10.1007/s10067-017-3605-x
Download citation

Share this article

Anyone you share the following link with will be able to read this content:

Get shareable link

Provided by the Springer Nature SharedIt content-sharing initiative

Keywords

# data[].attributes.attachment_link.title
Meaningful patient engagement in inflammatory arthritis: development of the Patient Motivation Questionnaire - Clinical Rheumatology

# data[].attributes.attachment_link.description
The objective of this study is to develop a questionnaire for evaluating the patient's "motivation" and assess the psychometric properties of that measure in patients with chronic inflammatory arthritis. Using Rasch analysis and questions item pool, content analysis, and semi-structured group discussion, the questionnaire was developed including 10-item scale (0-10 on VAS scale).

# data[].attributes.headline
Innovations, interventions and insights in clinical child psychology and psychiatry

# data[].attributes.subject
Innovations, interventions and insights in clinical child psychology and psychiatry

# data[].attributes.headline
A low-grade somatotroph adenoma presenting as a giant pituitary macro-adenoma

# data[].attributes.subject
A low-grade somatotroph adenoma presenting as a giant pituitary macro-adenoma

# data[].attributes.attachment_link.readable_text
A 31-year-old lady was referred to the outpatient endocrine clinic for subfertility, intermittent galactorrhoea and amenorrhoea since birth of her son 5 year ago. However, she denied visual disturbances and headache. She was struggling to lose weight but she had no clinical features suggestive of corticosteroid or growth hormone excess apart from an increase in her UK shoe size from 5.5 to 6.5 and family members noted her hands were slightly bigger. She was on an antidepressant, Sertraline, which was withheld for two weeks, so that a repeat pituitary profile can be carried out. It showed hypogonadotropic hypogonadism. The results were as follows: FSH 1.2 IU/l (2.5-10.2), LH <0.2 IU/l (1.9-12.5); oestradiol <55 pmol/l (55 - 422), Prolactin 1200 mIU/l (70 - 566) and IGF11 45 mol/l (10.2 to 40.7). But the Cortisol level, TSH and ACTH were within acceptable range. MRI pituitary demonstrated a pituitary/suprasellar mass with a 45mm craniocaudally dimension, which was displacing the optic chiasm superiorly and compressing on it. Formal visual field testing showed bilateral superior temporal quadrantanopia. She underwent Trans-sphenoidal surgery and was initiated on hydrocortisone replacement post-operatively. There was evidence of residual tumour in postoperative MRI scan and histology showed eosinophilic excess with intranuclear inclusions and immunohistochemistry demonstrated PIT 1 lineage pituitary adenoma, variably intense positivity for TSH predominantly, second most frequent was GH with Ki 67 3 %. Post-surgery, the Pituitary multidisciplinary team meeting (MDT), diagnosis was clinically silent and low-grade somatotroph adenoma biochemically. There was subjective improvement in the vision post operatively with normal VF confrontation and normal prolactin 289 mIU/l but persistently raised IGF153.9 mol/l. MDT noted that good debulking surgery but there was still a residual suprasellar part of tumour. Somatostatin analogue (SSA) therapy was recommended and re-do surgery for residual tumour if SSA therapy failed to achieve the therapeutic goal. The plan is to repeat MRI Pituitary and assess pituitary function with insulin tolerance test in 3 months. Learning points: This case highlights the somatotroph adenoma is presenting with a silent pituitary mass for decades and that diagnosis can be delayed until the clinical or biochemical manifestation of acromegaly. We picked up the diagnosis early by chance simply because she was investigated for subfertility. Surgical debulking surgery is main stay of treatment in somatotroph adenoma as it can lower GH levels and improve the cure rate with subsequent SSAs.

# data[].attributes.attachment_link.description
A 31-year-old lady was referred to the outpatient endocrine clinic for subfertility, intermittent galactorrhoea and amenorrhoea since birth of her son 5 year ago. However, she denied visual disturbances and headache.

# data[].attributes.headline
Streams, rivers and data lakes: an introduction to understanding modern electronic healthcare records

# data[].attributes.subject
Streams, rivers and data lakes: an introduction to understanding modern electronic healthcare records

# data[].attributes.attachment_link.description
About ScienceDirect
Shopping cart
Contact and
supportTerms and
conditionsPrivacy policy

# data[].attributes.headline
Medicine Trainees attending clinics – easier said than done!

# data[].attributes.subject
Medicine Trainees attending clinics – easier said than done!

# data[].attributes.attachment_link.description
About ScienceDirect
Shopping cart
Contact and
supportTerms and
conditionsPrivacy policy

# data[].attributes.headline
Strengthening the trainee voice at the Medical Local Faculty Group

# data[].attributes.subject
Strengthening the trainee voice at the Medical Local Faculty Group

# data[].attributes.attachment_link.description
About ScienceDirect
Shopping cart
Contact and
supportTerms and
conditionsPrivacy policy

# data[].attributes.headline
Skills not roles: the key to better training and better patient care

# data[].attributes.subject
Skills not roles: the key to better training and better patient care

# data[].attributes.headline
Identifying barriers to engaging older adults with primary care sexual health services

# data[].attributes.subject
Identifying barriers to engaging older adults with primary care sexual health services

# data[].attributes.attachment_link.readable_text
Helen Chilmaid Staff nurse, Darent Valley Hospital, Dartford, Kent, England

Despite the prevalent cultural stereotype that people's sexual activity declines or ceases as they grow older, adults in the UK remain sexually active throughout later life. This review of the literature investigates the factors influencing older adults' engagement with primary care sexual health services and makes recommendations about potential interventions.

Primary Health Care. doi: 10.7748/phc.2019.e1532

Peer review

This article has been subject to external double-blind review and has been checked for plagiarism using automated software

Correspondence

h.chilmaid@gmail.com

Conflict of interest

None declared

Chilmaid H (2019) Identifying barriers to engaging older adults with primary care sexual health services. Primary Health Care. doi: 10.7748/phc.2019.e1532

Published online: 11 September 2019

Want to read more?

or

3-month trial offer for £5.25/month

Subscribe today and save 50% on your first three months

RCNi Plus users have full access to the following benefits:

Unlimited access to all 10 RCNi Journals

RCNi Learning featuring over 175 modules to easily earn CPD time

NMC-compliant RCNi Revalidation Portfolio to stay on track with your progress

Personalised newsletters tailored to your interests

A customisable dashboard with over 200 topics

Subscribe
Alternatively, you can purchase access to this article for the next seven days. Buy now

Are you a student? Our student subscription has content especially for you.
Find out more

# data[].attributes.attachment_link.title
Identifying barriers to engaging older adults with primary care sexual health services

# data[].attributes.attachment_link.description
Identifying barriers to engaging older adults with primary care sexual health services

# data[].attributes.headline
Psychological effects of choosing active surveillance on men with prostate cancer

# data[].attributes.subject
Psychological effects of choosing active surveillance on men with prostate cancer

# data[].attributes.attachment_link.readable_text
Nicola Lancaster Uro-oncology clinical nurse specialist, Darent Valley Hospital, Dartford and Gravesham NHS Trust, Dartford, Kent, England

Greater awareness about prostate cancer has led to an increase in early detection of organ-confined prostate cancers and, as a result, some men are diagnosed with a cancer that may not affect their mortality. These men may be given treatment options including surgery, radiotherapy or active surveillance.

Surgery and radiotherapy can have side effects, such as urinary incontinence and erectile dysfunction, that may affect quality of life. Active surveillance enables urology and oncology teams to monitor the cancer and delay radical treatment until it is necessary, thereby maintaining a good quality of life. However, some men may feel anxious about the idea of not treating a cancer and opt instead for treatment.

This article examines the psychological effects of choosing active surveillance and discusses how nurses can support patients throughout the decision-making process and follow up.

Cancer Nursing Practice. doi: 10.7748/cnp.2019.e1575

Peer review

This article has been subject to external double-blind peer review and has been checked for plagiarism using automated software

Correspondence

n.lancaster@nhs.net

Conflict of interest

None declared

Lancaster N (2019) Psychological effects of choosing active surveillance on men with prostate cancer. Cancer Nursing Practice. doi: 10.7748/cnp.2019.e1575

Published online: 01 April 2019

Want to read more?

or

# data[].attributes.attachment_link.title
Psychological effects of choosing active surveillance on men with prostate cancer

# data[].attributes.attachment_link.description
Psychological effects of choosing active surveillance on men with prostate cancer

# data[].attributes.headline
Large-scale phenotyping of patients with long COVID post-hospitalization reveals mechanistic subtypes of disease

# data[].attributes.subject
Large-scale phenotyping of patients with long COVID post-hospitalization reveals mechanistic subtypes of disease

# data[].attributes.attachment_link.readable_text
Abstract

One in ten severe acute respiratory syndrome coronavirus 2 infections result in prolonged symptoms termed long coronavirus disease (COVID), yet disease phenotypes and mechanisms are poorly understood1. Here we profiled 368 plasma proteins in 657 participants ≥3 months following hospitalization. Of these, 426 had at least one long COVID symptom and 233 had fully recovered. Elevated markers of myeloid inflammation and complement activation were associated with long COVID. IL-1R2, MATN2 and COLEC12 were associated with cardiorespiratory symptoms, fatigue and anxiety/depression; MATN2, CSF3 and C1QA were elevated in gastrointestinal symptoms and C1QA was elevated in cognitive impairment. Additional markers of alterations in nerve tissue repair (SPON-1 and NFASC) were elevated in those with cognitive impairment and SCG3, suggestive of brain-gut axis disturbance, was elevated in gastrointestinal symptoms. Severe acute respiratory syndrome coronavirus 2-specific immunoglobulin G (IgG) was persistently elevated in some individuals with long COVID, but virus was not detected in sputum. Analysis of inflammatory markers in nasal fluids showed no association with symptoms. Our study aimed to understand inflammatory processes that underlie long COVID and was not designed for biomarker discovery. Our findings suggest that specific inflammatory pathways related to tissue damage are implicated in subtypes of long COVID, which might be targeted in future therapeutic trials.

Similar content being viewed by others

Keith Sacco, Riccardo Castagnoli, ... Luigi D. Notarangelo

Michael Maes, Walton Luiz Del Tedesco Junior, ... Andréa Name Colado Simão

Sizhen Su, Yimiao Zhao, ... Lin Lu

Main

One in ten severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections results in post-acute sequelae of coronavirus disease 2019 (PASC) or long coronavirus disease (COVID), which affects 65 million people worldwide1. Long COVID (LC) remains common, even after mild acute infection with recent variants2, and it is likely LC will continue to cause substantial long-term ill health, requiring targeted management based on an understanding of how disease phenotypes relate to underlying mechanisms. Persistent inflammation has been reported in adults with LC1,3, but studies have been limited in size, timing of samples or breadth of immune mediators measured, leading to inconsistent or absent associations with symptoms. Markers of oxidative stress, metabolic disturbance, vasculoproliferative processes and IFN-, NF-κB- or monocyte-related inflammation have been suggested3,4,5,6.

The PHOSP-COVID study, a multicenter United Kingdom study of patients previously hospitalized with COVID-19, has reported inflammatory profiles in 626 adults with health impairment after COVID-19, identified through clustering. Elevated IL-6 and markers of mucosal inflammation were observed in those with severe impairment compared with individuals with milder impairment7. However, LC is a heterogeneous condition that may be a distinct form of health impairment after COVID-19, and it remains unclear whether there are inflammatory changes specific to LC symptom subtypes. Determining whether activated inflammatory pathways underlie all cases of LC or if mechanisms differ according to clinical presentation is essential for developing effective therapies and has been highlighted as a top research priority by patients and clinicians8.

In this Letter, in a prospective multicenter study, we measured 368 plasma proteins in 657 adults previously hospitalized for COVID-19 (Fig. 1a and Table 1). Individuals in our cohort experienced a range of acute COVID-19 severities based on World Health Organization (WHO) progression scores9; WHO 3-4 (no oxygen support, n = 133 and median age of 55 years), WHO 5-6 (oxygen support, n = 353 and median age of 59 years) and WHO 7-9 (critical care, n = 171 and median age of 57 years). Participants were hospitalized for COVID-19 ≥3 months before sample collection (median 6.1 months, interquartile range (IQR) 5.1-6.8 months and range 3.0-8.3 months) and confirmed clinically ( n = 36/657) or by PCR ( n = 621/657). Symptom data indicated 233/657 (35%) felt fully recovered at 6 months (hereafter 'recovered') and the remaining 424 (65%) reported symptoms consistent with the WHO definition for LC (symptoms ≥3 months post infection10). Given the diversity of LC presentations, patients were grouped according to symptom type (Fig. 1b). Groups were defined using symptoms and health deficits that have been commonly reported in the literature1 ( Methods). A multivariate penalized logistic regression model (PLR) was used to explore associations of clinical covariates and immune mediators at 6 months between recovered patients ( n = 233) and each LC group (cardiorespiratory symptoms, cardioresp, n = 398, Fig. 1c; fatigue, n = 384, Fig. 1d; affective symptoms, anxiety/depression, n = 202, Fig. 1e; gastrointestinal symptoms, GI, n = 132, Fig. 1f; and cognitive impairment, cognitive, n = 61, Fig. 1g). Women ( n = 239) were more likely to experience CardioResp (odds ratio (OR 1.14), Fatigue (OR 1.22), GI (OR 1.13) and Cognitive (OR 1.03) outcomes (Fig. 1c,d,f,g). Repeated cross-validation was used to optimize and assess model performance ( Methods and Extended Data Fig. 1). Pre-existing conditions, such as chronic lung disease, neurological disease and cardiovascular disease (Supplementary Table 1), were associated with all LC groups (Fig. 1c-g). Age, C-reactive protein (CRP) and acute disease severity were not associated with any LC group (Table 1).

a, Distribution of time from COVID-19 hospitalization at sample collection. All samples were cross-sectional. The vertical red line indicates the 3 month cutoff used to define our final cohort and samples collected before 3 months were excluded. b, An UpSet plot describing pooled LC groups. The horizontal colored bars represent the number of patients in each symptom group: cardiorespiratory (Cardio_Resp), fatigue, cognitive, GI and anxiety/depression (Anx_Dep). Vertical black bars represent the number of patients in each symptom combination group. To prevent patient identification, where less than five patients belong to a combination group, this has been represented as '<5'. The recovered group ( n = 233) were used as controls. c- g, Forest plots of Olink protein concentrations (NPX) associated with Cardio_Resp ( n = 365) ( c), fatigue (n = 314) ( d), Anx_Dep ( n = 202) ( e), GI ( n = 124) ( f) and cognitive ( n = 60) ( g). Neuro_Psych, neuropsychiatric. The error bars represent the median accuracy of the model. h, i, Distribution of Olink values (NPX) for IL-1R2 ( h) and MATN2, neurofascin and sCD58 ( i) measured between symptomatic and recovered individuals in recovered ( n = 233), Cardio_Resp ( n = 365), fatigue ( n = 314) and Anx_Dep ( n = 202) groups ( h) and MATN2 in GI ( n = 124), neurofascin in cognitive ( n = 60) and sCD58 in Cardio_Resp and recovered groups ( i). The box plot center line represents the median, the boundaries represent IQR and the whisker length represents 1.5× IQR. The median values were compared between groups using two-sided Wilcoxon signed-rank test, * P < 0.05, ** P < 0.01, *** P < 0.001 and **** P  < 0.0001.

Table 1 Cohort demographics

To study the association of peripheral inflammation with symptoms, we analyzed cross-sectional data collected approximately 6 months after hospitalizations. We measured 368 immune mediators from plasma collected contemporaneously with symptom data. Mediators suggestive of myeloid inflammation were associated with all symptoms (Fig. 1c-h). Elevated IL-1R2, an IL-1 receptor expressed by monocytes and macrophages modulating inflammation11 and MATN2, an extracellular matrix protein that modulates tissue inflammation through recruitment of innate immune cells12, were associated with cardioresp (IL-1R2 OR 1.14, Fig. 1c,h), fatigue (IL-1R2 OR 1.45, Fig. 1d,h), anxiety/depression (IL-1R2 OR 1.34. Fig. 1e,h) and GI (MATN2 OR 1.08, Fig. 1f). IL-3RA, an IL-3 receptor, was associated with cardioresp (OR 1.07, Fig. 1c), fatigue (OR 1.21, Fig. 1d), anxiety/depression (OR 1.12, Fig. 1e) and GI (OR 1.06, Fig. 1f) groups, while CSF3, a cytokine promoting neutrophilic inflammation13, was elevated in cardioresp (OR 1.06, Fig. 1c), fatigue (OR 1.12, Fig. 1d) and GI (OR 1.08, Fig. 1f).

Elevated COLEC12, which initiates inflammation in tissues by activating the alternative complement pathway14, associated with cardioresp (OR 1.09, Fig. 1c), fatigue (OR 1.19, Fig. 1d) and anxiety/depression (OR 1.11, Fig. 1e), but not with GI (Fig. 1f) and only weakly with cognitive (OR 1.02, Fig. 1g). C1QA, a degradation product released by complement activation15 was associated with GI (OR 1.08, Fig. 1f) and cognitive (OR 1.03, Fig. 1g). C1QA, which is known to mediate dementia-related neuroinflammation16, had the third strongest association with cognitive (Fig. 1g). These observations indicated that myeloid inflammation and complement activation were associated with LC.

Increased expression of DPP10 and SCG3 was observed in the GI group compared with recovered (DPP10 OR 1.07 and SCG3 OR 1.08, Fig. 1f). DPP10 is a membrane protein that modulates tissue inflammation, and increased DPP10 expression is associated with inflammatory bowel disease17,18, suggesting that GI symptoms may result from enteric inflammation. Elevated SCG3, a multifunctional protein that has been associated with irritable bowel syndrome19, suggested that noninflammatory disturbance of the brain-gut axis or dysbiosis, may occur in the GI group. The cognitive group was associated with elevated CTSO (OR 1.04), NFASC (OR 1.03) and SPON-1 (OR 1.02, Fig. 1g,i). NFASC and SPON-1 regulate neural growth20,21, while CTSO is a cysteine proteinase supporting tissue turnover22. The increased expression of these three proteins as well as C1QA and DPP10 in the cognitive group (Fig. 1g) suggested neuroinflammation and alterations in nerve tissue repair, possibly resulting in neurodegeneration. Together, our findings indicated that complement activation and myeloid inflammation were common to all LC groups, but subtle differences were observed in the GI and cognitive groups, which may have mechanistic importance. Acutely elevated fibrinogen during hospitalization has been reported to be predictive of LC cognitive deficits23. We found elevated fibrinogen in LC relative to recovered (Extended Data Fig. 2a; P = 0.0077), although this was not significant when restricted to the cognitive group ( P = 0.074), supporting our observation of complement pathway activation in LC and in keeping with reports that complement dysregulation and thrombosis drive severe COVID-19 (ref. 24).

Elevated sCD58 was associated with lower odds of all LC symptoms and was most pronounced in cardioresp (OR 0.85, Fig. 1c,i), fatigue (OR 0.80, Fig. 1d) and anxiety/depression (OR 0.83, Fig. 1e). IL-2 was negatively associated with the cardioresp (Fig. 1c, OR 0.87), fatigue (Fig. 1d, OR 0.80), anxiety/depression (Fig. 1e, OR 0.84) and cognitive (Fig. 1g, OR 0.96) groups. Both IL-2 and sCD58 have immunoregulatory functions25,26. Specifically, sCD58 suppresses IL-1- or IL-6-dependent interactions between CD2⁺ monocytes and CD58⁺ T or natural killer cells26. The association of sCD58 with recovered suggests a central role of dysregulated myeloid inflammation in LC. Elevated markers of tissue repair, IDS and DNER27,28, were also associated with recovered relative to all LC groups (Fig. 1c-g). Taken together, our data suggest that suppression of myeloid inflammation and enhanced tissue repair were associated with recovered, supporting the use of immunomodulatory agents in therapeutic trials29 (Supplementary Table 2).

We next sought to validate the experimental and analytical approaches used. Although Olink has been validated against other immunoassay platforms, showing superior sensitivity and specificity30,31, we confirmed the performance of Olink against chemiluminescent immunoassays within our cohort. We performed chemiluminescent immunoassays on plasma from a subgroup of 58 participants (recovered n = 13 and LC n = 45). There were good correlations between results from Olink (normalized protein expression (NPX)) and chemiluminescent immunoassays (pg ml −1) for CSF3, IL-1R2, IL-3RA, TNF and TFF2 (Extended Data Fig. 3). Most samples did not have concentrations of IL-2 detectable using a mesoscale discovery chemiluminescent assay, limiting this analysis to 14 samples (recovered n = 4, LC n = 10, R = 0.55 and P = 0.053, Extended Data Fig. 3). We next repeated our analysis using alternative definitions of LC. The Centers for Disease Control and Prevention and National Institute for Health and Care Excellence definitions for LC include symptoms occurring 1 month post infection32,33. Using the 1 month post-infection definition included 62 additional participants to our analysis (recovered n = 21, 3 females and median age 61 years and LC n = 41, 15 females and median age 60 years, Extended Data Fig. 2c) and found that inflammatory associations with each LC group were consistent with our analysis based on the WHO definition (Extended Data Fig. 2d-h). Finally, to validate the analytical approach (PLR) we examined the distribution of data, prioritizing proteins that were most strongly associated with each LC/recovered group (IL-1R2, MATN2, NFASC and sCD58). Each protein was significantly elevated in the LC group compared with recovered (Fig. 1h,i and Extended Data Fig. 4), consistent with the PLR. Alternative regression approaches (unadjusted regression models and partial least squares, PLS) reported results consistent with the original analysis of protein associations and LC outcome in the WHO-defined cohort (Fig. 1c-g, Supplementary Table 3 and Extended Data Figs. 5 and 6). The standard errors of PLS estimates were wide (Extended Data Fig. 6), consistent with previous demonstrations that PLR is the optimal method to analyze high-dimensional data where variables may have combined effects34. As inflammatory proteins are often colinear, working in-tandem to mediate effects, we prioritized PLR results to draw conclusions.

To explore the relationship between inflammatory mediators associated with different LC symptoms, we performed a network analysis of Olink mediators highlighted by PLR within each LC group. COLEC12 and markers of endothelial and mucosal inflammation (MATN2, PCDH1, ROBO1, ISM1, ANGPTL2, TGF-α and TFF2) were highly correlated within the cardioresp, fatigue and anxiety/depression groups (Fig. 2 and Extended Data Fig. 7). Elevated PCDH1, an adhesion protein modulating airway inflammation35, was highly correlated with other inflammatory proteins associated with the cardioresp group (Fig. 2), suggesting that systemic inflammation may arise from the lung in these individuals. This was supported by increased expression of IL-3RA, which regulates innate immune responses in the lung through interactions with circulating IL-3 (ref. 36), in fatigue (Figs. 1d and 2), which correlated with markers of tissue inflammation, including PCDH1 (Fig. 2). MATN2 and ISM1, mucosal proteins that enhance inflammation37,38, were highly correlated in the GI group (Fig. 2), highlighting the role of tissue-specific inflammation in different LC groups. SCG3 correlated less closely with mediators in the GI group (Fig. 2), suggesting that the brain-gut axis may contribute separately to some GI symptoms. SPON-1, which regulates neural growth21, was the most highly correlated mediator in the cognitive group (Fig. 2 and Extended Data Fig. 7), highlighting that processes within nerve tissue may underlie this group. These observations suggested that inflammation might arise from mucosal tissues and that additional mechanisms may contribute to pathophysiology underlying the GI and cognitive groups.

Network analysis of Olink mediators associated with cardioresp ( n = 365), fatigue ( n = 314), anxiety/depression ( n = 202), GI ( n = 124) and cognitive groups ( n = 60). Each node corresponds to a protein mediator identified by PLR. The edges (blue lines) were weighted according to the size of Spearman's rank correlation coefficient between proteins. All edges represent positive and significant correlations ( P  < 0.05) after FDR adjustment.

Women were more likely to experience LC (Table 1), as found in previous studies1. As estrogen can influence immunological responses39, we investigated whether hormonal differences between men and women with LC in our cohort explained this trend. We grouped men and women with LC symptoms into two age groups (those younger than 50 years and those 50 years and older, using age as a proxy for menopause status in women) and compared mediator levels between men and women in each age group, prioritizing those identified by PLR to be higher in LC compared with recovered. As we aimed to understand whether women with LC had stronger inflammatory responses than men with LC, we did not assess differences in men and women in the recovered group. IL-1R2 and MATN2 were significantly higher in women ≥50 years than men ≥50 years in the cardioresp group (Fig. 3a, IL-1R2 and MATN2) and the fatigue group (Fig. 3b). In the GI group, CSF3 was higher in women ≥50 years compared with men ≥50 years (Fig. 3c), indicating that the inflammatory markers observed in women were not likely to be estrogen-dependent. Women have been reported to have stronger innate immune responses to infection and to be at greater risk of autoimmunity39, possibly explaining why some women in the ≥50 years group had higher inflammatory proteins than men the same group. Proteins associated with the anxiety/depression (IL-1R2 P = 0.11 and MATN2 P = 0.61, Extended Data Fig. 8a) and cognitive groups (CTSO P = 0.64 and NFASC P = 0.41, Extended Data Fig. 8b) were not different between men and women in either age group, consistent with the absent/weak association between sex and these outcomes identified by PLR (Fig. 1e,g). Though our findings suggested that nonhormonal differences in inflammatory responses may explain why some women are more likely to have LC, they require confirmation in adequately powered studies.

a- c, Olink-measured plasma protein levels (NPX) of IL-1R2 and MATN2 ( a and b) and CSF3 ( c) between LC men and LC women divided by age (<50 or ≥50 years) in the cardiorespiratory group (<50 years n = 8 and ≥50 years n = 270) ( a), fatigue group (<50 years n = 81 and ≥50 years n = 227) ( b) and GI group (<50 years n = 34 and ≥50 years n = 82) ( c). the median values were compared between men and women using two-sided Wilcoxon signed-rank test, * P < 0.05, ** P < 0.01, *** P < 0.001 and **** P  < 0.0001. The box plot center line represents the median, the boundaries represent IQR and the whisker length represents 1.5× IQR.

To test whether local respiratory tract inflammation persisted after COVID-19, we compared nasosorption samples from 89 participants (recovered, n = 31; LC, n = 33; and healthy SARS-CoV-2 naive controls, n = 25, Supplementary Tables 4 and 5). Several inflammatory markers were elevated in the upper respiratory tract post COVID (including IL-1α, CXCL10, CXCL11, TNF, VEGF and TFF2) when compared with naive controls, but similar between recovered and LC (Fig. 4a). In the cardioresp group ( n = 29), inflammatory mediators elevated in plasma (for example, IL-6, APO-2, TGF-α and TFF2) were not elevated in the upper respiratory tract (Extended Data Fig. 9a) and there was no correlation between plasma and nasal mediator levels (Extended Data Fig. 9b). This exploratory analysis suggested upper respiratory tract inflammation post COVID was not specifically associated with cardiorespiratory symptoms.

a, Nasal cytokines measured by immunoassay in post-COVID participants ( n = 64) compared with healthy SARS-CoV-2 naive controls ( n = 25), and between the the cardioresp group ( n = 29) and the recovered group ( n = 31). The red values indicate significantly increased cytokine levels after FDR adjustment ( P < 0.05) using two-tailed Wilcoxon signed-rank test. b, SARS-CoV-2 N antigen measured in sputum by electrochemiluminescence from recovered ( n = 17) and pooled LC ( n = 23) groups, compared with BALF from SARS-CoV-2 naive controls ( n = 9). The horizontal dashed line indicates the lower limit of detection of the assay. c, Plasma S- and N-specific IgG responses measured by electrochemiluminescence in the LC ( n = 35) and recovered ( n = 19) groups. The median values were compared using two-sided Wilcoxon signed-rank tests, NS P > 0.05, * P < 0.05, ** P < 0.01, *** P < 0.001 and **** P  < 0.0001. The box plot center lines represent the median, the boundaries represent IQR and the whisker length represents 1.5× IQR.

To explore whether SARS-CoV-2 persistence might explain the inflammatory profiles observed in the cardioresp group, we measured SARS-CoV-2 nucleocapsid (N) antigen in sputum from 40 participants (recovered n = 17 and LC n = 23) collected approximately 6 months post hospitalization (Supplementary Table 6). All samples were compared with prepandemic bronchoalveolar lavage fluid ( n = 9, Supplementary Table 4). Only four samples (recovered n = 2 and LC n = 2) had N antigen above the assay's lower limit of detection, and there was no difference in N antigen concentrations between LC and recovered (Fig. 4b, P = 0.78). These observations did not exclude viral persistence, which might require tissues samples for detection40,41. On the basis of the hypothesis that persistent viral antigen might prevent a decline in antibody levels over time, we examined the titers of SARS-CoV-2-specific antibodies in unvaccinated individuals (recovered n = 19 and LC n = 35). SARS-CoV-2 N-specific ( P = 0.023) and spike (S)-specific ( P = 0.0040) immunoglobulin G (IgG) levels were elevated in LC compared with recovered (Fig. 4c).

Overall, we identified myeloid inflammation and complement activation in the cardioresp, fatigue, anxiety/depression, cognitive and GI groups 6 months after hospitalization (Extended Data Fig. 10). Our findings build on results of smaller studies5,6,42 and are consistent with a genome-wide association study that identified an independent association between LC and FOXP4, which modulates neutrophilic inflammation and immune cell function43,44. In addition, we identified tissue-specific inflammatory elements, indicating that myeloid disturbance in different tissues may result in distinct symptoms. Multiple mechanisms for LC have been suggested, including autoimmunity, thrombosis, vascular dysfunction, SARS-CoV-2 persistence and latent virus reactivation1. All these processes involve myeloid inflammation and complement activation45. Complement activation in LC has been suggested in a proteomic study in 97 mostly nonhospitalized COVID-19 cases42 and a study of 48 LC patients, of which one-third experienced severe acute disease46. As components of the complement system are known to have a short half-life47, ongoing complement activation suggests active inflammation rather than past tissue damage from acute infection.

Despite the heterogeneity of LC and the likelihood of coexisting or multiple etiologies, our work suggests some common pathways that might be targeted therapeutically and supports the rationale for several drugs currently under trial. Our finding of increased sCD58 levels (associated with suppression of monocyte-lymphocyte interactions26) in the recovered group, strengthens our conclusion that myeloid inflammation is central to the biology of LC and that trials of steroids, IL-1 antagonists, JAK inhibitors, naltrexone and colchicine are justified. Although anticoagulants such as apixaban might prevent thrombosis downstream of complement dysregulation, they can also increase the risk of serious bleeding when given after COVID-19 hospitalization48. Thus, clinical trials, already underway, need to carefully assess the risks and benefits of anticoagulants (Supplementary Table 2).

Our finding of elevated S- and N-specific IgG in LC could suggest viral persistence, as found in other studies6,42,49. Our network analysis indicated that inflammatory proteins in the cardioresp group interacted strongly with ISM1 and ROBO1, which are expressed during respiratory tract infection and regulate lung inflammation50,51. Although we were unable to find SARS-CoV-2 antigen in sputum from our LC cases, we did not test for viral persistence in GI tract and lung tissue40,41 or in plasma52. Evidence of SARS-CoV-2 persistence would justify trials of antiviral drugs (singly or in combination) in LC. It is also possible that autoimmune processes could result in an innate inflammatory profile in LC. Autoreactive B cells have been identified in LC patients with higher SARS-CoV-2-specific antibody titers in a study of mostly mild acute COVID cases (59% WHO 2-3)42, a different population from our study of hospitalized cases.

Our observations of distinct protein profiles in GI and cognitive groups support previous reports on distinct associations between Epstein-Barr virus reactivation and neurological symptoms, or autoantibodies and GI symptoms relative to other forms of LC49,53. We did not assess autoantibody induction but found evidence of brain-gut axis disturbance (SCG3) in the GI group, which occurs in many autoimmune diseases54. We found signatures suggestive of neuroinflammation (C1QA) in the cognitive group, consistent with findings of brain abnormalities on magnetic resonance imaging after COVID-19 hospitalization55, as well as findings of microglial activation in mice after COVID-19 (ref. 56). Proinflammatory signatures dominated in the cardioresp, fatigue and anxiety/depression groups and were consistent with those seen in non-COVID depression, suggesting shared mechanisms57. The association between markers of myeloid inflammation, including IL-3RA, and symptoms was greatest for fatigue. Whilst membrane-bound IL-3RA facilitates IL-3 signaling upstream of myelopoesis36 its soluble form (measured in plasma) can bind IL-3 and can act as a decoy receptor, preventing monocyte maturation and enhancing immunopathology58. Monocytes from individuals with post-COVID fatigue are reported to have abnormal expression profiles (including reduced CXCR2), suggestive of altered maturation and migration5,59. Lung-specific inflammation was suggested by the association between PCDH1 (an airway epithelial adhesion molecule35) and cardioresp symptoms.

Our observations do not align with all published observations on LC. One proteomic study of 55 LC cases after generally mild (WHO 2-3) acute disease found that TNF and IFN signatures were elevated in LC3. Vasculoproliferative processes and metabolic disturbance have been reported in LC4,60, but these studies used uninfected healthy individuals for comparison and cannot distinguish between LC-specific phenomena and residual post-COVID inflammation. A study of 63 adults (LC, n = 50 and recovered, n = 13) reported no association between immune cell activation and LC 3 months after infection61, though myeloid inflammation was not directly measured, and 3 months post infection may be too early to detect subtle differences between LC and recovered cases due to residual acute inflammation.

Our study has limitations. We designed the study to identify inflammatory markers identifying pathways underlying LC subgroups rather than diagnostic biomarkers. The ORs we report are small, but associations were consistent across alternative methods of analysis and when using different LC definitions. Small effect sizes can be expected when using PLR, which shrinks correlated mediator coefficients to reflect combined effects and prevent colinear inflation62, and could also result from measurement of plasma mediators that may underestimate tissue inflammation. Although our LC cohort is large compared with most other published studies, some of our subgroups are small (only 60 cases were designated cognitive). Though the performance of the cognitive PLR model was adequate, our findings should be validated in larger studies. It should be noted that our cohort of hospitalized cases may not represent all types of LC, especially those occurring after mild infection. We looked for an effect of acute disease severity within our study and did not find it, and are reassured that the inflammatory profiles we observed were consistent with those seen in smaller studies including nonhospitalized cases42,46. Studies of posthospital LC may be confounded by 'posthospital syndrome', which encompasses general and nonspecific effects of hospitalization (particularly intensive care)63.

In conclusion, we found markers of myeloid inflammation and complement activation in our large prospective posthospital cohort of patients with LC, in addition to distinct inflammatory patterns in patients with cognitive impairment or gastrointestinal symptoms. These findings show the need to consider subphenotypes in managing patients with LC and support the use of antiviral or immunomodulatory agents in controlled therapeutic trials.

Methods

Study design and ethics

After hospitalization for COVID-19, adults who had no comorbidity resulting in a prognosis of less than 6 months were recruited to the PHOSP-COVID study ( n = 719). Patients hospitalized between February 2020 and January 2021 were recruited. Both sexes were recruited and gender was self-reported (female, n = 257 and male, n  = 462). Written informed consent was obtained from all patients. Ethical approvals for the PHOSP-COVID study were given by Leeds West Research Ethics Committee (20/YH/0225).

Symptom data and samples were prospectively collected from individuals approximately 6 months (IQR 5.1-6.8 months and range 3.0-8.3 months) post hospitalization (Fig. 1a), via the PHOSP-COVID multicenter United Kingdom study64. Data relating to patient demographics and acute admission were collected via the International Severe Acute Respiratory and Emerging Infection Consortium World Health Organization Clinical Characterisation Protocol United Kingdom (ISARIC4C study; IRAS260007/IRAS126600) (ref. 65). Adults hospitalized during the SARS-CoV-2 pandemic were systematically recruited into ISARIC4C. Written informed consent was obtained from all patients. Ethical approval was given by the South Central-Oxford C Research Ethics Committee in England (reference 13:/SC/0149), Scotland A Research Ethics Committee (20/SS/0028) and WHO Ethics Review Committee (RPC571 and RPC572l, 25 April 2013).

Data were collected to account for variables affecting symptom outcome, via hospital records and self-reporting. Acute disease severity was classified according to the WHO clinical progression score: WHO class 3-4: no oxygen therapy; class 5: oxygen therapy; class 6: noninvasive ventilation or high-flow nasal oxygen; and class 7-9: managed in critical care9. Clinical data were used to place patients into six categories: 'recovered', 'GI', 'cardiorespiratory', 'fatigue', 'cognitive impairment' and 'anxiety/depression' (Supplementary Table 7). Patient-reported symptoms and validated clinical scores were used when feasible, including Medical Research Council (MRC) breathlessness score, dyspnea-12 score, Functional Assessment of Chronic Illness Therapy (FACIT) score, Patient Health Questionnaire (PHQ)-9 and Generalized Anxiety Disorder (GAD)-7. Cognitive impairment was defined as a Montreal Cognitive Assessment score <26. GI symptoms were defined as answering 'Yes' to the presence of at least two of the listed symptoms. 'Recovered' was defined by self-reporting. Patients were placed in multiple groups if they experienced a combination of symptoms.

Matched nasal fluid and sputum samples were prospectively collected from a subgroup of convalescent patients approximately 6 months after hospitalization via the PHOSP-COVID study. Nasal and bronchoalveolar lavage fluid (BALF) collected from healthy volunteers before the COVID-19 pandemic were used as controls (Supplementary Table 4). Written consent was obtained for all individuals and ethical approvals were given by London-Harrow Research Ethics Committee (13/LO/1899) for the collection of nasal samples and the Health Research Authority London-Fulham Research Ethics Committee (IRAS project ID 154109; references 14/LO/1023, 10/H0711/94 and 11/LO/1826) for BALF samples.

Procedures

Ethylenediaminetetraacetic acid plasma was collected from whole blood taken by venepuncture and frozen at −80 °C as previously described7,66. Nasal fluid was collected using a NasosorptionTM FX·I device (Hunt Developments), which uses a synthetic absorptive matrix to collect concentrated nasal fluid. Samples were eluted and stored as previously described67. Sputum samples were collected via passive expectoration and frozen at −80 °C without the addition of buffers. Sputum samples from convalescent individuals were compared with BALF from healthy SARS-CoV-2-naive controls, collected before the pandemic. BALF samples were used to act as a comparison for lower respiratory tract samples since passively expectorated sputum from healthy SARS-CoV-2-naive individuals was not available. BALF samples were obtained by instillation and recovery of up to 240 ml of normal saline via a fiberoptic bronchoscope. BALF was filtered through 100 µM strainers into sterile 50 ml Falcon tubes, then centrifuged for 10 min at 400  g at 4 °C. The resulting supernatant was transferred into sterile 50 ml Falcon tubes and frozen at −80 °C until use. The full methods for BALF collection and processing have been described previously68,69.

Immunoassays

To determine inflammatory signatures that associated with symptom outcomes, plasma samples were analyzed on an Olink Explore 384 Inflammation panel70. Supplementary Table 8 (Appendix 1) lists all the analytes measured. To ensure the validity of results, samples were run in a single batch with the use of negative controls, plate controls in triplicate and repeated measurement of patient samples between plates in duplicate. Samples were randomized between plates according to site and sample collection date. Randomization between plates was blind to LC/recovered outcome. Data were first normalized to an internal extension control that was included in each sample well. Plates were standardized by normalizing to interplate controls, run in triplicate on each plate. Each plate contained a minimum of four patient samples, which were duplicates on another plate; these duplicate pairs allowed any plate to be linked to any other through the duplicates. Data were then intensity normalized across all cohort samples. Finally, Olink results underwent quality control processing and samples or analytes that did not reach quality control standards were excluded. Final normalized relative protein quantities were reported as log ₂ NPX values.

To further validate our findings, we performed conventional electrochemiluminescence (ECL) assays and enzyme-linked immunosorbent assay for Olink mediators that were associated with symptom outcome ( Supplementary Methods). Contemporaneously collected plasma samples were available from 58 individuals. Like most omics platforms, Olink measures relative quantities, so perfect agreement with conventional assays that measure absolute concentrations is not expected.

Sputum samples were thawed before analysis and sputum plugs were extracted with the addition of 0.1% dithiothreitol creating a one in two sample dilution, as previously described71. SARS-CoV-2 S and N proteins were measured by ECL S-plex assay at a fixed dilution of one in two (Mesoscale Diagnostics), as per the manufacturers protocol72. Control BALF samples were thawed and measured on the same plate, neat. The S-plex assay is highly sensitive in detecting viral antigen in respiratory tract samples73.

Nasal cytokines were measured by ECL (mesoscale discovery) and Luminex bead multiplex assays (Biotechne). The full methods and list of analytes are detailed in Supplementary Methods.

Statistics and reproducibility

Clinical data was collected via the PHOSP REDCap database, to which access is available under reasonable request as per the data sharing statement in the manuscript. All analyses were performed within the Outbreak Data Analysis Platform (ODAP). All data and code can be accessed using information in the 'Data sharing' and 'Code sharing' statements at the end of the manuscript. No statistical method was used to predetermine sample size. Data distribution was assumed to be normal but this was not formally tested. Olink assays and immunoassays were randomized and investigators were blinded to outcomes.

To determine protein signatures that associated with each symptom outcome, a ridge PLR was used. PLR shrinks coefficients to account for combined effects within high-dimensional data, preventing false discovery while managing multicollinearity34. Thus, PLR was chosen a priori as the most appropriate model to assess associations between a large number of explanatory variables (that may work together to mediate effects) and symptom outcome34,62,70,74. In keeping with our aim to perform an unbiased exploration of inflammatory process, the model alpha was set to zero, facilitating regularization without complete penalization of any mediator. This enabled review of all possible mediators that might associate with LC62.

A 50 repeats tenfold nested cross-validation was used to select the optimal lambda for each model and assess its accuracy (Extended Data Fig. 1). The performance of the cognitive impairment model was influenced by the imbalance in size of the symptom group ( n = 60) relative to recovered ( n = 250). The model was weighted to account for this imbalance resulting in a sensitivity of 0.98, indicating its validity. We have expanded on the model performance and validation approaches in Supplementary Information.

Age, sex, acute disease severity and preexisting comorbidities were included as covariates in the PLR analysis (Supplementary Tables 1 and 3). Covariates were selected a priori using features reported to influence the risk of LC and inflammatory responses1,39,64,75. Ethnicity was not included since it has been shown not to predict symptom outcome in this cohort64. Individuals with missing data were excluded from the regression analysis. Each symptom group was compared with the 'recovered' group. The model coefficients of each covariate were converted into ORs for each outcome and visualized in a forest plot, after removing variables associated with regularized OR between 0.98 and 1.02 or in cases where most variables fell outside of this range, using mediators associated with the highest decile of coefficients either side of this range. This enabled exclusion of mediators with effect sizes that were unlikely to have clinical or mechanistic importance since the ridge PLR shrinks and orders coefficients according to their relative importance rather than making estimates with standard error. Thus, confidence intervals cannot be appropriately derived from PLR, and forest plot error bars were calculated using the median accuracy of the model generated by the nested cross-validation. To verify observations made through PLR analysis, we also performed an unadjusted PLR, an unadjusted logistic regression and a PLS analysis. Univariate analyses using Wilcoxon signed-rank test was also performed (Supplementary Table 8, Appendix 1). Analyses were performed in R version 4.2.0 using 'data.table v1.14.2', 'EnvStats v2.7.0' 'tidyverse v1.3.2', 'lme4 v1.1-32', 'caret v6.0-93', 'glmnet v4.1-6', 'mdatools v0.14.0', 'ggpubbr v0.4.0' and 'ggplot2 v3.3.6' packages.

To further investigate the relationship between proteins elevated in each symptom group, we performed a correlation network analysis using Spearman's rank correlation coefficient and false discovery rate (FDR) thresholding. The mediators visualized in the PLR forest plots, which were associated with cardiorespiratory symptoms, fatigue, anxiety/depression GI symptoms and cognitive impairment were used, respectively. Analyses were performed in R version 4.2.0 using 'bootnet v1.5.6 ' and 'qgraph v1.9.8 ' packages.

To determine whether differences in protein levels between men and women related to hormonal differences, we divided each symptom group into premenopausal and postmenopausal groups using an age cutoff of 50 years old. Differences between sexes in each group were determined using the Wilcoxon signed-rank test. To understand whether antigen persistence contributed to inflammation in adults with LC, the median viral antigen concentration from sputum/BALF samples and cytokine concentrations from nasal samples were compared using the Wilcoxon signed-rank test. All tests were two-tailed and statistical significance was defined as a P value < 0.05 after adjustment for FDR ( q-value of 0.05). Analyses were performed in R version 4.2.0 using 'bootnet v1.5.6' and 'qgraph v1.9.8' packages.

Extended Data Fig. 10 was made using Biorender, accessed at www.biorender.com.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

References

1. Klein, J. et al. Distinguishing features of Long COVID identified through immune profiling. Nature https://doi.org/10.1038/s41586-023-06651-y (2023).

2. Woo, W.-M. et al. The C. elegans F-spondin family protein SPON-1 maintains cell adhesion in neural and non-neural tissues. Development 135, 2747-2756 (2008).

3. Taquet, M. et al. Acute blood biomarker profiles predict cognitive deficits 6 and 12 months after COVID-19 hospitalization. Nat. Med. https://doi.org/10.1038/s41591-023-02525-y (2023).

4. Firinguetti, L., Kibria, G. & Araya, R. Study of partial least squares and ridge regression methods. Commun. Stat. Simul. Comput 46, 6631-6644 (2017).

Article Google Scholar

5. Rivera-Torruco, G. et al. Isthmin 1 identifies a subset of lung hematopoietic stem cells and it is associated with systemic inflammation. J. Immunol. 202, 118.18 (2019).

Article Google Scholar

6. Raman, B. et al. Multiorgan MRI findings after hospitalisation with COVID-19 in the UK (C-MORE): a prospective, multicentre, observational cohort study. Lancet Respir. Med 11, 1003-1019 (2023).

Article Google Scholar

Download references

Acknowledgements

This research used data assets made available by ODAP as part of the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation (grant ref. MC_PC_20058). This work is supported by the following grants: the PHOSP-COVD study is jointly funded by UK Research and Innovation and National Institute of Health and Care Research (NIHR; grant references MR/V027859/1 and COV0319). ISARIC4C is supported by grants from the National Institute for Health and Care Research (award CO-CIN-01) and the MRC (grant MC_PC_19059) Liverpool Experimental Cancer Medicine Centre provided infrastructure support for this research (grant reference C18616/A25153). Other grants that have supported this work include the UK Coronavirus Immunology Consortium (funder reference 1257927), the Imperial Biomedical Research Centre (NIHR Imperial BRC, grant IS-BRC-1215-20013), the Health Protection Research Unit in Respiratory Infections at Imperial College London and NIHR Health Protection Research Unit in Emerging and Zoonotic Infections at University of Liverpool, both in partnership with Public Health England, (NIHR award 200907), Wellcome Trust and Department for International Development (215091/Z/18/Z), Health Data Research UK (grant code 2021.0155), MRC (grant code MC_UU_12014/12) and NIHR Clinical Research Network for providing infrastructure support for this research. We also acknowledge the support of the MRC EMINENT Network (MR/R502121/1), which is cofunded by GSK, the Comprehensive Local Research Networks, the MRC HIC-Vac network (MR/R005982/1) and the RSV Consortium in Europe Horizon 2020 Framework Grant 116019. F.L. is supported by an MRC clinical training fellowship (award MR/W000970/1). C.E. is funded by NIHR (grant P91258-4). L.-P.H. is supported by Oxford NIHR Biomedical Research Centre. A.A.R.T. is supported by a British Heart Foundation (BHF) Intermediate Clinical Fellowship (FS/18/13/33281). S.L.R.-J. receives support from UK Research and Innovation (UKRI), Global Challenges Research Fund (GCRF), Rosetrees Trust, British HIV association (BHIVA), European & Developing Countries Clinical Trials Partnership (EDCTP) and Globvac. J.D.C. has grants from AstraZeneca, Boehringer Ingelheim, GSK, Gilead Sciences, Grifols, Novartis and Insmed. R.A.E. holds a NIHR Clinician Scientist Fellowship (CS-2016-16-020). A. Horsley is currently supported by UK Research and Innovation, NIHR and NIHR Manchester BRC. B.R. receives support from BHF Oxford Centre of Research Excellence, NIHR Oxford BRC and MRC. D.G.W. is supported by an NIHR Advanced Fellowship. A. Ho has received support from MRC and for the Coronavirus Immunology Consortium (MR/V028448/1). L.T. is supported by the US Food and Drug Administration Medical Countermeasures Initiative contract 75F40120C00085 and the National Institute for Health Research Health Protection Research Unit in Emerging and Zoonotic Infections (NIHR200907) at the University of Liverpool in partnership with UK Health Security Agency (UK-HSA), in collaboration with Liverpool School of Tropical Medicine and the University of Oxford. L.V.W. has received support from UKRI, GSK/Asthma and Lung UK and NIHR for this study. M.G.S. has received support from NIHR UK, MRC UK and Health Protection Research Unit in Emerging and Zoonotic Infections, University of Liverpool. J.K.B. is supported by the Wellcome Trust (223164/Z/21/Z) and UKRI (MC_PC_20004, MC_PC_19025, MC_PC_1905, MRNO2995X/1 and MC_PC_20029). The funders were not involved in the study design, interpretation of data or writing of this manuscript. The views expressed are those of the authors and not necessarily those of the Department of Health and Social Care (DHSC), the Department for International Development (DID), NIHR, MRC, the Wellcome Trust, UK-HSA, the National Health Service or the Department of Health. P.J.M.O. is supported by a NIHR Senior Investigator Award (award 201385). We thank all the participants and their families. We thank the many research administrators, health-care and social-care professionals who contributed to setting up and delivering the PHOSP-COVID study at all of the 65 NHS trusts/health boards and 25 research institutions across the United Kingdom, as well as those who contributed to setting up and delivering the ISARIC4C study at 305 NHS trusts/health boards. We also thank all the supporting staff at the NIHR Clinical Research Network, Health Research Authority, Research Ethics Committee, Department of Health and Social Care, Public Health Scotland and Public Health England. We thank K. Holmes at the NIHR Office for Clinical Research Infrastructure for her support in coordinating the charities group. The PHOSP-COVID industry framework was formed to provide advice and support in commercial discussions, and we thank the Association of the British Pharmaceutical Industry as well the NIHR Office for Clinical Research Infrastructure for coordinating this. We are very grateful to all the charities that have provided insight to the study: Action Pulmonary Fibrosis, Alzheimer's Research UK, Asthma and Lung UK, British Heart Foundation, Diabetes UK, Cystic Fibrosis Trust, Kidney Research UK, MQ Mental Health, Muscular Dystrophy UK, Stroke Association Blood Cancer UK, McPin Foundations and Versus Arthritis. We thank the NIHR Leicester Biomedical Research Centre patient and public involvement group and Long Covid Support. We also thank G. Khandaker and D. C. Newcomb who provided valuable feedback on this work. Extended Data Fig. 10 was created using Biorender.

Author information

Author notes

These authors contributed equally: Felicity Liew, Claudia Efstathiou, Ryan S. Thwaites, Peter J. M. Openshaw.

Authors and Affiliations

1. National Heart and Lung Institute, Imperial College London, London, UK

Felicity Liew, Claudia Efstathiou, Sara Fontanella, Dawid Swieboda, Jasmin K. Sidhu, Stephanie Ascough, Onn Min Kon, Luke S. Howard, Jennifer K. Quint, Christopher Chiu, Ryan S. Thwaites, Peter J. M. Openshaw, Jake Dunning & Peter J. M. Openshaw

2. Institute for Lung Health, Leicester NIHR Biomedical Research Centre, University of Leicester, Leicester, UK

Matthew Richardson, Ruth Saunders, Olivia C. Leavy, Omer Elneima, Hamish J. C. McAuley, Amisha Singapuri, Marco Sereno, Victoria C. Harris, Neil J. Greening, Rachael A. Evans, Louise V. Wain, Christopher Brightling & Ananga Singapuri

3. NIHR Health Protection Research Unit in Emerging and Zoonotic Infections, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, UK

Shona C. Moore, Daniel G. Wootton, Malcolm G. Semple, Lance Turtle, William A. Paxton & Georgios Pollakis

4. The Imperial Clinical Respiratory Research Unit, Imperial College NHS Trust, London, UK

Noura Mohamed

5. Cardiovascular Research Team, Imperial College Healthcare NHS Trust, London, UK

Jose Nunag & Clara King

6. Department of Population Health Sciences, University of Leicester, Leicester, UK

Olivia C. Leavy, Louise V. Wain & Beatriz Guillen-Guio

7. NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK

Aarti Shikotra

8. Centre for Exercise and Rehabilitation Science, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK

Linzy Houchen-Wolloff

9. Usher Institute, University of Edinburgh, Edinburgh, UK

Nazir I. Lone, Luke Daines, Annemarie B. Docherty, Nazir I. Lone, Matthew Thorpe, Annemarie B. Docherty, Thomas M. Drake, Cameron J. Fairfield, Ewen M. Harrison, Stephen R. Knight, Kenneth A. Mclean, Derek Murphy, Lisa Norman, Riinu Pius & Catherine A. Shaw

10. Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK

Matthew Thorpe, Annemarie B. Docherty, Ewen M. Harrison, J. Kenneth Baillie, Sarah L. Rowland-Jones, A. A. Roger Thompson & Thushan de Silva

11. Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, UK

A. A. Roger Thompson, Sarah L. Rowland-Jones, Thushan I. de Silva & James D. Chalmers

12. University of Dundee, Ninewells Hospital and Medical School, Dundee, UK

James D. Chalmers & Ling-Pei Ho

13. MRC Human Immunology Unit, University of Oxford, Oxford, UK

Ling-Pei Ho & Alexander Horsley

14. Division of Infection, Immunity and Respiratory Medicine, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK

Alexander Horsley & Betty Raman

15. Radcliffe Department of Medicine, University of Oxford, Oxford, UK

Betty Raman & Krisnah Poinasamy

16. Asthma + Lung UK, London, UK

Krisnah Poinasamy & Michael Marks

17. Department of Clinical Research, London School of Hygiene and Tropical Medicine, London, UK

Michael Marks

18. Hospital for Tropical Diseases, University College London Hospital, London, UK

Michael Marks

19. Division of Infection and Immunity, University College London, London, UK

Michael Marks & Mahdad Noursadeghi

20. MRC Centre for Virus Research, School of Infection and Immunity, University of Glasgow, Glasgow, UK

Antonia Ho & William Greenhalf

21. Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK

William Greenhalf & J. Kenneth Baillie

22. The Roslin Institute, University of Edinburgh, Edinburgh, UK

J. Kenneth Baillie, J. Kenneth Baillie, Sara Clohisey, Fiona Griffiths, Ross Hendry, Andrew Law & Wilna Oosthuyzen

23. Pandemic Science Hub, University of Edinburgh, Edinburgh, UK

J. Kenneth Baillie

24. The Pandemic Institute, University of Liverpool, Liverpool, UK

Malcolm G. Semple & Lance Turtle

25. University of Manchester, Manchester, UK

Kathryn Abel, Perdita Barran, H. Chinoy, Bill Deakin, M. Harvie, C. A. Miller, Stefan Stanel & Drupad Trivedi

26. Intensive Care Unit, Royal Infirmary of Edinburgh, Edinburgh, UK

Kathryn Abel & J. Kenneth Baillie

27. North Bristol NHS Trust and University of Bristol, Bristol, UK

H. Adamali, David Arnold, Shaney Barratt, A. Dipper, Sarah Dunn, Nick Maskell, Anna Morley, Leigh Morrison, Louise Stadon, Samuel Waterson & H. Welch

28. University of Edinburgh, Manchester, UK

Davies Adeloye, D. E. Newby, Riinu Pius, Igor Rudan, Manu Shankar-Hari, Catherine Sudlow, Sarah Walmsley & Bang Zheng

29. King's College Hospital NHS Foundation Trust and King's College London, London, UK

Oluwaseun Adeyemi, Rita Adrego, Hosanna Assefa-Kebede, Jonathon Breeze, S. Byrne, Pearl Dulawan, Amy Hoare, Caroline Jolley, Abigail Knighton, M. Malim, Sheetal Patale, Ida Peralta, Natassia Powell, Albert Ramos, K. Shevket, Fabio Speranza & Amelie Te

30. Guy's and St Thomas' NHS Foundation Trust, London, UK

Laura Aguilar Jimenez, Gill Arbane, Sarah Betts, Karen Bisnauthsing, A. Dewar, Nicholas Hart, G. Kaltsakas, Helen Kerslake, Murphy Magtoto, Philip Marino, L. M. Martinez, Marlies Ostermann, Jennifer Rossdale & Teresa Solano

31. Royal Free London NHS Foundation Trust, London, UK

Shanaz Ahmad, Simon Brill, John Hurst, Hannah Jarvis, C. Laing, Lai Lim, S. Mandal, Darwin Matila, Olaoluwa Olaosebikan & Claire Singh

32. University Hospital Birmingham NHS Foundation Trust and University of Birmingham, Birmingham, UK

N. Ahmad Haider, Catherine Atkin, Rhiannon Baggott, Michelle Bates, A. Botkai, Anna Casey, B. Cooper, Joanne Dasgin, Camilla Dawson, Katharine Draxlbauer, N. Gautam, J. Hazeldine, T. Hiwot, Sophie Holden, Karen Isaacs, T. Jackson, Vicky Kamwa, D. Lewis, Janet Lord, S. Madathil, C. McGee, K. Mcgee, Aoife Neal, Alex Newton-Cox, Joseph Nyaboko, Dhruv Parekh, Z. Peterkin, H. Qureshi, Liz Ratcliffe, Elizabeth Sapey, J. Short, Tracy Soulsby, J. Stockley, Zehra Suleiman, Tamika Thompson, Maximina Ventura, Sinead Walder, Carly Welch, Daisy Wilson, S. Yasmin & Kay Por Yip

33. Stroke Association, London, UK

Rubina Ahmed & Richard Francis

34. University College London Hospital and University College London, London, UK

Nyarko Ahwireng, Dongchun Bang, Donna Basire, Jeremy Brown, Rachel Chambers, A. Checkley, R. Evans, M. Heightman, T. Hillman, Joseph Jacob, Roman Jastrub, M. Lipman, S. Logan, D. Lomas, Marta Merida Morillas, Hannah Plant, Joanna Porter, K. Roy & E. Wall

35. Oxford University Hospitals NHS Foundation Trust and University of Oxford, Oxford, UK

Mark Ainsworth, Asma Alamoudi, Angela Bloss, Penny Carter, M. Cassar, Jin Chen, Florence Conneh, T. Dong, Ranuromanana Evans, V. Ferreira, Emily Fraser, John Geddes, F. Gleeson, Paul Harrison, May Havinden-Williams, P. Jezzard, Ivan Koychev, Prathiba Kurupati, H. McShane, Clare Megson, Stefan Neubauer, Debby Nicoll, C. Nikolaidou, G. Ogg, Edmund Pacpaco, M. Pavlides, Yanchun Peng, Nayia Petousi, John Pimm, Najib Rahman, M. J. Rowland, Kathryn Saunders, Michael Sharpe, Nick Talbot, E. M. Tunnicliffe & C. Xie

36. St George's University Hospitals NHS Foundation Trust, London, UK

Mariam Ali, Raminder Aul, A. Dunleavy, D. Forton, Mark Mencias, N. Msimanga, T. Samakomva, Sulman Siddique, Vera Tavoukjian & J. Teixeira

37. University Hospitals of Leicester NHS Trust and University of Leicester, Leicester, UK

M. Aljaroof, Natalie Armstrong, H. Arnold, Hnin Aung, Majda Bakali, M. Bakau, E. Baldry, Molly Baldwin, Charlotte Bourne, Michelle Bourne, Nigel Brunskill, P. Cairns, Liesel Carr, Amanda Charalambou, C. Christie, Melanie Davies, Enya Daynes, Sarah Diver, Rachael Dowling, Sarah Edwards, C. Edwardson, H. Evans, J. Finch, Sarah Glover, Nicola Goodman, Bibek Gooptu, Kate Hadley, Pranab Haldar, Beverley Hargadon, W. Ibrahim, L. Ingram, Kamlesh Khunti, A. Lea, D. Lee, Gerry McCann, P. McCourt, Teresa Mcnally, George Mills, Will Monteiro, Manish Pareek, S. Parker, Anne Prickett, I. N. Qureshi, A. Rowland, Richard Russell, Salman Siddiqui, Sally Singh, J. Skeemer, M. Soares, E. Stringer, T. Thornton, Martin Tobin, T. J. C. Ward, F. Woodhead, Tom Yates & A. J. Yousuf

38. University of Exeter, Exeter, UK

Louise Allan, Clive Ballard & Andrew McGovern

39. University of Leicester, Leicester, UK

Richard Allen, Michelle Bingham, Terry Brugha, Selina Finney, Rob Free, Don Jones, Claire Lawson, Daniel Lozano-Rojas, Gardiner Lucy, Alistair Moss, Elizabeta Mukaetova-Ladinska, Petr Novotny, Kimon Ntotsis, Charlotte Overton, John Pearl, Tatiana Plekhanova, M. Richardson, Nilesh Samani, Jack Sargant, Ruth Saunders, M. Sharma, Mike Steiner, Chris Taylor, Sarah Terry, C. Tong, E. Turner, J. Wormleighton & Bang Zhao

40. Liverpool University Hospitals NHS Foundation Trust and University of Liverpool, Liverpool, UK

Lisa Allerton, Ann Marie Allt, M. Beadsworth, Anthony Berridge, Jo Brown, Shirley Cooper, Andy Cross, Sylviane Defres, S. L. Dobson, Joanne Earley, N. French, Kera Hainey, Hayley Hardwick, Jenny Hawkes, Victoria Highett, Sabina Kaprowska, Angela Key, Lara Lavelle-Langham, N. Lewis-Burke, Gladys Madzamba, Flora Malein, Sophie Marsh, Chloe Mears, Lucy Melling, Matthew Noonan, L. Poll, James Pratt, Emma Richardson, Anna Rowe, Victoria Shaw, K. A. Tripp, Lilian Wajero, S. A. Williams-Howard, Dan Wootton & J. Wyles

41. Sherwood Forest Hospitals NHS Foundation Trust, Nottingham, UK

Lynne Allsop, Kaytie Bennett, Phil Buckley, Margaret Flynn, Mandy Gill, Camelia Goodwin, M. Greatorex, Heidi Gregory, Cheryl Heeley, Leah Holloway, Megan Holmes, John Hutchinson, Jill Kirk, Wayne Lovegrove, Terri Ann Sewell, Sarah Shelton, D. Sissons, Katie Slack, Susan Smith, D. Sowter, Sarah Turner, V. Whitworth & Inez Wynter

42. Nottingham University Hospitals NHS Trust and University of Nottingham, London, UK

Paula Almeida, Akram Hosseini, Robert Needham & Karen Shaw

43. Manchester University NHS Foundation Trust and University of Manchester, London, UK

Bashar Al-Sheklly, Cristina Avram, John Blaikely, M. Buch, N. Choudhury, David Faluyi, T. Felton, T. Gorsuch, Neil Hanley, Tracy Hussell, Zunaira Kausar, Natasha Odell, Rebecca Osbourne, Karen Piper Hanley, K. Radhakrishnan & Sue Stockdale

44. Imperial College London, London, UK

Danny Altmann, Anew Frankel, Luke S. Howard, Desmond Johnston, Liz Lightstone, Anne Lingford-Hughes, William Man, Steve McAdoo, Jane Mitchell, Philip Molyneaux, Christos Nicolaou, D. P. O'Regan, L. Price, Jennifer K. Quint, David Smith, Jonathon Valabhji, Simon Walsh, Martin Wilkins & Michelle Willicombe

45. Hampshire Hospitals NHS Foundation Trust, Basingstoke, UK

Maria Alvarez Corral, Ava Maria Arias, Emily Bevan, Denise Griffin, Jane Martin, J. Owen, Sheila Payne, A. Prabhu, Annabel Reed, Will Storrar, Nick Williams & Caroline Wrey Brown

46. British Heart Foundation, Birmingham, UK

Shannon Amoils

47. NHS Greater Glasgow and Clyde Health Board and University of Glasgow, Glasgow, UK

David Anderson, Neil Basu, Hannah Bayes, Colin Berry, Ammani Brown, Andrew Dougherty, K. Fallon, L. Gilmour, D. Grieve, K. Mangion, I. B. McInnes, A. Morrow, Kathryn Scott & R. Sykes

48. University of Oxford, Oxford, UK

Charalambos Antoniades, A. Bates, M. Beggs, Kamaldeep Bhui, Katie Breeze, K. M. Channon, David Clark, X. Fu, Masud Husain, Lucy Kingham, Paul Klenerman, Hanan Lamlum, X. Li, E. Lukaschuk, Celeste McCracken, K. McGlynn, R. Menke, K. Motohashi, T. E. Nichols, Godwin Ogbole, S. Piechnik, I. Propescu, J. Propescu, A. A. Samat, Z. B. Sanders, Louise Sigfrid & M. Webster

49. Belfast Health and Social Care Trust and Queen's University Belfast, Belfast, UK

Cherie Armour, Vanessa Brown, John Busby, Bronwen Connolly, Thelma Craig, Stephen Drain, Liam Heaney, Bernie King, Nick Magee, E. Major, Danny McAulay, Lorcan McGarvey, Jade McGinness, Tunde Peto & Roisin Stone

50. Airedale NHS Foundation Trust, Keighley, UK

Lisa Armstrong, Brigid Hairsine, Helen Henson, Claire Kurasz, Alison Shaw & Liz Shenton

51. Wrightington Wigan and Leigh NHS Trust, Wigan, UK

A. Ashish, Josh Cooper & Emma Robinson

52. Leeds Teaching Hospitals and University of Leeds, Leeds, UK

Andrew Ashworth, Paul Beirne, Jude Clarke, C. Coupland, Matthhew Dalton, Clair Favager, Jodie Glossop, John Greenwood, Lucy Hall, Tim Hardy, Amy Humphries, Jennifer Murira, Dan Peckham, S. Plein, Jade Rangeley, Gwen Saalmink, Ai Lyn Tan, Elaine Wade, Beverley Whittam, Nicola Window & Janet Woods

53. University of Liverpool, Liverpool, UK

M. Ashworth, D. Cuthbertson, G. Kemp, Anne McArdle, Benedict Michael, Will Reynolds, Lisa Spencer, Ben Vinson, Katie A. Ahmed, Jane A. Armstrong, Milton Ashworth, Innocent G. Asiimwe, Siddharth Bakshi, Samantha L. Barlow, Laura Booth, Benjamin Brennan, Katie Bullock, Nicola Carlucci, Emily Cass, Benjamin W. A. Catterall, Jordan J. Clark, Emily A. Clarke, Sarah Cole, Louise Cooper, Helen Cox, Christopher Davis, Oslem Dincarslan, Alejandra Doce Carracedo, Chris Dunn, Philip Dyer, Angela Elliott, Anthony Evans, Lorna Finch, Lewis W. S. Fisher, Lisa Flaherty, Terry Foster, Isabel Garcia-Dorival, Philip Gunning, Catherine Hartley, Karl Holden, Anthony Holmes, Rebecca L. Jensen, Christopher B. Jones, Trevor R. Jones, Shadia Khandaker, Katharine King, Robyn T. Kiy, Chrysa Koukorava, Annette Lake, Suzannah Lant, Diane Latawiec, Lara Lavelle-Langham, Daniella Lefteri, Lauren Lett, Lucia A. Livoti, Maria Mancini, Hannah Massey, Nicole Maziere, Sarah McDonald, Laurence McEvoy, John McLauchlan, Soeren Metelmann, Nahida S. Miah, Joanna Middleton, Joyce Mitchell, Ellen G. Murphy, Rebekah Penrice-Randal, Jack Pilgrim, Tessa Prince, P. Matthew Ridley, Debby Sales, Rebecca K. Shears, Benjamin Small, Krishanthi S. Subramaniam, Agnieska Szemiel, Aislynn Taggart, Jolanta Tanianis-Hughes, Jordan Thomas, Erwan Trochu, Libby van Tonder, Eve Wilcock & J. Eunice Zhang

54. University College London, London, UK

Shahab Aslani, Amita Banerjee, R. Batterham, Gabrielle Baxter, Robert Bell, Anthony David, Emma Denneny, Alun Hughes, W. Lilaonitkul, P. Mehta, Ashkan Pakzad, Bojidar Rangelov, B. Williams, James Willoughby & Moucheng Xu

55. Hull University Teaching Hospitals NHS Trust and University of Hull, Hull, UK

Paul Atkin, K. Brindle, Michael Crooks, Katie Drury, Nicholas Easom, Rachel Flockton, L. Holdsworth, A. Richards, D. L. Sykes, Susannah Thackray-Nocera & C. Wright

56. East Kent Hospitals University NHS Foundation Trust, Canterbury, UK

Liam Austin, Eva Beranova, Tracey Cosier, Joanne Deery, Tracy Hazelton, Carly Price, Hazel Ramos, Reanne Solly, Sharon Turney & Heather Weston

57. Baillie Gifford Pandemic Science Hub, Centre for Inflammation Research, The Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK

Nikos Avramidis, J. Kenneth Baillie, Erola Pairo-Castineira & Konrad Rawlik

58. Roslin Institute, University of Edinburgh, Edinburgh, UK

Nikos Avramidis, J. Kenneth Baillie & Erola Pairo-Castineira

59. Newcastle upon Tyne Hospitals NHS Foundation Trust and University of Newcastle, Newcastle upon Tyne, UK

A. Ayoub, J. Brown, G. Burns, Gareth Davies, Anthony De Soyza, Carlos Echevarria, Helen Fisher, C. Francis, Alan Greenhalgh, Philip Hogarth, Joan Hughes, Kasim Jiwa, G. Jones, G. MacGowan, D. Price, Avan Sayer, John Simpson, H. Tedd, S. Thomas, Sophie West, M. Witham, S. Wright & A. Young

60. East Cheshire NHS Trust, Macclesfield, UK

Marta Babores, Maureen Holland, Natalie Keenan, Sharlene Shashaa & Helen Wassall

61. Sheffield Teaching NHS Foundation Trust and University of Sheffield, Sheffield, UK

J. Bagshaw, M. Begum, K. Birchall, Robyn Butcher, H. Carborn, Flora Chan, Kerry Chapman, Yutung Cheng, Luke Chetham, Cameron Clark, Zach Coburn, Joby Cole, Myles Dixon, Alexandra Fairman, J. Finnigan, H. Foot, David Foote, Amber Ford, Rebecca Gregory, Kate Harrington, L. Haslam, L. Hesselden, J. Hockridge, Ailsa Holbourn, B. Holroyd-Hind, L. Holt, Alice Howell, E. Hurditch, F. Ilyas, Claire Jarman, Allan Lawrie, Ju Hee Lee, Elvina Lee, Rebecca Lenagh, Alison Lye, Irene Macharia, M. Marshall, Angeline Mbuyisa, J. McNeill, Sharon Megson, J. Meiring, L. Milner, S. Misra, Helen Newell, Tom Newman, C. Norman, Lorenza Nwafor, Dibya Pattenadk, Megan Plowright, Julie Porter, Phillip Ravencroft, C. Roddis, J. Rodger, Peter Saunders, J. Sidebottom, Jacqui Smith, Laurie Smith, N. Steele, G. Stephens, R. Stimpson, B. Thamu, N. Tinker, Kim Turner, Helena Turton, Phillip Wade, S. Walker, James Watson, Imogen Wilson & Amira Zawia

62. University of Nottingham, Nottingham, UK

David Baguley, Chris Coleman, E. Cox, Laura Fabbri, Susan Francis, Ian Hall, E. Hufton, Simon Johnson, Fasih Khan, Paaig Kitterick, Richard Morriss, Nick Selby, Iain Stewart & Louise Wright

63. Wirral University Teaching Hospital, Wirral, UK

Elisabeth Bailey, Anne Reddington & Andrew Wight

64. MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, UK

J. Kenneth Baillie

65. University of Swansea, Swansea, UK

Steve Bain

66. University of Southampton, London, UK

David Baldwin, P. C. Calder, Nathan Huneke & Gemma Simons

67. Royal Brompton and Harefield Clinical Group, Guy's and St Thomas' NHS Foundation Trust, London, UK

R. E. Barker, Daniele Cristiano, N. Dormand, P. George, Mahitha Gummadi, S. Kon, Kamal Liyanage, C. M. Nolan, B. Patel, Suhani Patel, Oliver Polgar, L. Price, P. Shah, Suver Singh & J. A. Walsh

68. York and Scarborough NHS Foundation Trust, York, UK

Laura Barman, Claire Brookes, K. Elliott, L. Griffiths, Zoe Guy, Kate Howard, Diana Ionita, Heidi Redfearn, Carol Sarginson & Alison Turnbull

69. NHS Highland, Inverness, UK

Fiona Barrett, A. Donaldson & Beth Sage

70. Royal Papworth Hospital NHS Foundation Trust, Cambridge, UK

Helen Baxendale, Lucie Garner, C. Johnson, J. Mackie, Alice Michael, J. Newman, Jamie Pack, K. Paques, H. Parfrey, J. Parmar & A. Reddy

71. University Hospitals of Derby and Burton, Derby, UK

Paul Beckett, Caroline Dickens & Uttam Nanda

72. NHS Lanarkshire, Hamilton, UK

Murdina Bell, Angela Brown, M. Brown, R. Hamil, Karen Leitch, L. Macliver, Manish Patel, Jackie Quigley, Andrew Smith & B. Welsh

73. Cambridge University Hospitals NHS Foundation Trust, NIHR Cambridge Clinical Research Facility and University of Cambridge, Cambridge, UK

Areti Bermperi, Isabel Cruz, K. Dempsey, Anne Elmer, Jonathon Fuld, H. Jones, Sherly Jose, Stefan Marciniak, M. Parkes, Carla Ribeiro, Jessica Taylor, Mark Toshner, L. Watson & J. Worsley

74. Loughborough University, Loughborough, UK

Lettie Bishop & David Stensel

75. Betsi Cadwallader University Health Board, Bangor, UK

Annette Bolger, Ffyon Davies, Ahmed Haggar, Joanne Lewis, Arwel Lloyd, R. Manley, Emma McIvor, Daniel Menzies, K. Roberts, W. Saxon, David Southern, Christian Subbe & Victoria Whitehead

76. Nottingham University Hospitals NHS Trust and University of Nottingham, Nottingham, UK

Charlotte Bolton, J. Bonnington, Melanie Chrystal, Catherine Dupont, Paul Greenhaff, Ayushman Gupta, W. Jang, S. Linford, Laura Matthews, Athanasios Nikolaidis, Sabrina Prosper & Andrew Thomas

77. King's College London, London, UK

Kate Bramham, M. Brown, Khalida Ismail, Tim Nicholson, Carmen Pariante, Claire Sharpe, Simon Wessely & J. Whitney

78. Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK

Lucy Brear, Karen Regan, Dinesh Saralaya & Kim Storton

79. South London and Maudsley NHS Foundation Trust and King's College London, London, UK

G. Breen & M. Hotopf

80. London School of Hygiene and Tropical Medicine, London, UK

Andrew Briggs

81. Whittington Health NHS Trust, London, UK

E. Bright, P. Crisp, Ruvini Dharmagunawardena & M. Stern

82. Cardiff and Vale University Health Board, Cardiff, UK

Lauren Broad, Teriann Evans, Matthew Haynes, L. Jones, Lucy Knibbs, Alison McQueen, Catherine Oliver, Kerry Paradowski, Ramsey Sabit & Jenny Williams

83. Yeovil District Hospital NHS Foundation Trust, Yeovil, UK

Andrew Broadley

84. University of Birmingham, Birmingham, UK

Mattew Broome, Paul McArdle, Paul Moss, David Thickett, Rachel Upthegrove, Dan Wilkinson, David Wraith & Erin L. Aldera

85. BHF Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK

Anda Bularga

86. University of Cambridge, Cambridge, UK

Ed Bullmore, Jonathon Heeney, Claudia Langenberg, William Schwaeble, Charlotte Summers & J. Weir McCall

87. NIHR Leicester Biomedical Research Centre-Respiratory Patient and Public Involvement Group, Leicester, UK

Jenny Bunker, Rhyan Gill & Rashmita Nathu

88. Imperial College Healthcare NHS Trust and Imperial College London, London, UK

L. Burden, Ellen Calvelo, Bethany Card, Caitlin Carr, Edwin Chilvers, Donna Copeland, P. Cullinan, Patrick Daly, Lynsey Evison, Tamanah Fayzan, Hussain Gordon, Sulaimaan Haq, Gisli Jenkins, Clara King, Onn Min Kon, Katherine March, Myril Mariveles, Laura McLeavey, Silvia Moriera, Unber Munawar, Uchechi Nwanguma, Lorna Orriss-Dib, Alexandra Ross, Maura Roy, Emily Russell, Katherine Samuel, J. Schronce, Neil Simpson, Lawrence Tarusan, David Thomas, Chloe Wood & Najira Yasmin

89. Harrogate and District NHD Foundation Trust, Harrogate, UK

Tracy Burdett, James Featherstone, Cathy Lawson, Alison Layton, Clare Mills & Lorraine Stephenson

90. Newcastle University/Chair of NIHR Dementia TRC, Newcastle, UK

David Burn

91. Oxford University Hospitals NHS Foundation Trust, Oxford, UK

A. Burns & N. Kanellakis

92. Tameside and Glossop Integrated Care NHS Foundation Trust, Ashton-under-Lyne, UK

Al-Tahoor Butt, Martina Coulding, Heather Jones, Susan Kilroy, Jacqueline McCormick, Jerome McIntosh, Heather Savill, Victoria Turner & Joanne Vere

93. University of Oxford, Nuffield Department of Medicine, Oxford, UK

G. Carson

94. University of Glasgow, Glasgow, UK

Jonathon Cavanagh, S. MacDonald, Kate O'Donnell, John Petrie, Naveed Sattar & Mark Spears

95. United Lincolnshire Hospitals NHS Trust, Grantham, UK

Manish Chablani & Lynn Osborne

96. Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK

Trudie Chalder

97. University Hospital of South Manchester NHS Foundation Trust, Manchester, UK

N. Chaudhuri

98. University Hospital Southampton NHS Foundation Trust and University of Southampton, Southampton, UK

Caroline Childs, R. Djukanovic, S. Fletcher, Matt Harvey, Mark Jones, Elizabeth Marouzet, B. Marshall, Reena Samuel, T. Sass, Tim Wallis & Helen Wheeler

99. King's College Hospital/Guy's and St Thomas' NHS FT, London, UK

A. Chiribiri & C. O'Brien

100. Barts Health NHS Trust, London, UK

K. Chong-James, C. David, W. Y. James, Paul Pfeffer & O. Zongo

101. NHS Lothian and University of Edinburgh, Edinburgh, UK

Gaunab Choudhury, S. Clohisey, Andrew Deans, J. Furniss, Ewen Harrison, S. Kelly & Aziz Sheikh

102. School of Cardiovascular Medicine and Sciences. King's College London, London, UK

Phillip Chowienczyk

103. Lewisham and Greenwich NHS Trust, London, UK

G. Coakley

104. Hywel Dda University Health Board, Haverfordwest, UK

S. Coetzee, Kim Davies, Rachel Ann Hughes, Ronda Loosley, Heather McGuinness, Abdelrahman Mohamed, Linda O'Brien, Zohra Omar, Emma Perkins, Janet Phipps, Gavin Ross, Abigail Taylor, Helen Tench & Rebecca Wolf-Roberts

105. NHS Tayside and University of Dundee, Dundee, UK

David Connell, C. Deas, Anne Elliott, J. George, S. Mohammed, J. Rowland, A. R. Solstice, Debbie Sutherland & Caroline Tee

106. Swansea Bay University Health Board, Port Talbot, UK

Lynda Connor, Amanda Cook, Gwyneth Davies, Tabitha Rees, Favas Thaivalappil & Caradog Thomas

107. Faculty of Medicine, Nursing and Health Sciences, School of Biomedical Sciences, Monash University, Melbourne, Victoria, Australia

Eamon Coughlan

108. Rotherham NHS Foundation Trust, Rotherham, UK

Alison Daniels, Anil Hormis, Julie Ingham & Lisa Zeidan

109. Salford Royal NHS Foundation Trust, Salford, UK

P. Dark, Nawar Diar-Bakerly, D. Evans, E. Hardy, Alice Harvey, D. Holgate, Sean Knight, N. Mairs, N. Majeed, L. McMorrow, J. Oxton, Jessica Pendlebury, C. Summersgill, R. Ugwuoke & S. Whittaker

110. Cwm Taf Morgannwg University Health Board, Mountain Ash, UK

Ellie Davies, Cerys Evenden, Alyson Hancock, Kia Hancock, Ceri Lynch, Meryl Rees, Lisa Roche, Natalie Stroud & T. Thomas-Woods

111. Borders General Hospital, NHS Borders, Melrose, UK

Joy Dawson, Hosni El-Taweel & Leanne Robinson

112. Aneurin Bevan University Health Board, Caerleon, UK

Amanda Dell, Sara Fairbairn, Nancy Hawkings, Jill Haworth, Michaela Hoare, Victoria Lewis, Alice Lucey, Georgia Mallison, Heeah Nassa, Chris Pennington, Andrea Price, Claire Price, Andrew Storrie, Gemma Willis & Susan Young

113. University of Exeter Medical School, Exeter, UK

J. Dennis

114. London North West University Healthcare NHS Trust, London, UK

Shalin Diwanji, Sambasivarao Gurram, Padmasayee Papineni, Sheena Quaid, Gerlynn Tiongson & Ekaterina Watson

115. Alzheimer's Research UK, Cambridge, UK

Hannah Dobson

116. Health and Care Research Wales, Cardiff, UK

Yvette Ellis

117. University of Bristol, Bristol, UK

Jonathon Evans

118. University of Sheffield, Sheffield, UK

L. Finnigan, Laura Saunders & James Wild

119. Great Western Hospital Foundation Trust, Swindon, UK

Eva Fraile & Jacinta Ugoji

120. Royal Devon and Exeter NHS Trust, Barnstaple, UK

Michael Gibbons

121. Kettering General Hospital NHS Trust, Kettering, UK

Anne-Marie Guerdette, Melanie Hewitt, R. Reddy, Katie Warwick & Sonia White

122. NIHR Leicester Biomedical Research Centre, Leicester, UK

Beatriz Guillen-Guio

123. University of Leeds, Leeds, UK

Elspeth Guthrie & Max Henderson

124. Royal Surrey NHS Foundation Trust, Cranleigh, UK

Mark Halling-Brown & Katherine McCullough

125. Chesterfield Royal Hospital NHS Trust, Calow, UK

Edward Harris & Claire Sampson

126. Long Covid Support, London, UK

Claire Hastie, Natalie Rogers & Nikki Smith

127. King's College Hospital, NHS Foundation Trust and King's College London, London, UK

A. Hayday

128. Department of Oncology and Metabolism, University of Sheffield, Sheffield, UK

Simon Heller

129. NIHR Office for Clinical Research Infrastructure, London, UK

Katie Holmes

130. Asthma UK and British Lung Foundation Partnership, London, UK

Ian Jarrold & Samantha Walker

131. North Middlesex University Hospital NHS Trust, London, UK

Bhagy Jayaraman & Tessa Light

132. Action for Pulmonary Fibrosis, Peterborough, UK

S. Jones

133. Cardiff University, National Centre for Mental Health, Cardiff, UK

Ian Jones

134. McPin Foundation, London, UK

Thomas Kabir

135. Roslin Institute, The University of Edinburgh, Edinburgh, UK

Steven Kerr

136. The Hillingdon Hospitals NHS Foundation Trust, London, UK

Samantha Kon, G. Landers, Harpreet Lota, Mariam Nasseri & Sofiya Portukhay

137. Queen Mary University of London, London, UK

Ania Korszun

138. Swansea University, Swansea Welsh Network, Hywel Dda University Health Board, Swansea, UK

Keir Lewis

139. Royal Infirmary of Edinburgh, NHS Lothian, Edinburgh, UK

Nazir I. Lone

140. Barts Heart Centre, London, UK

C. Manisty

141. Barts Health NHS Trust and Queen Mary University of London, London, UK

Adrian Martineau

142. Salisbury NHS Foundation Trust, Salisbury, UK

Wadzanai Matimba-Mupaya & Sophia Strong-Sheldrake

143. University of Newcastle, Newcastle, UK

Hamish McAllister-Williams, Stella-Maria Paddick, Anthony Rostron & John Paul Taylor

144. Gateshead NHS Trust, Gateshead, UK

W. McCormick, Lorraine Pearce, S. Pugmire, Wendy Stoker & Ann Wilson

145. Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, Manchester, UK

Katherine McIvor

146. Kidney Research UK, Peterborough, UK

Aisling McMahon

147. NHS Dumfries and Galloway, Dumfries, UK

Michael McMahon & Paula Neill

148. Swansea University, Swansea, UK

M. McNarry

149. MQ Mental Health Research, London, UK

Lea Milligan

150. BHF Centre for Cardiovascular Science, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK

Nicholas Mills

151. Shropshire Community Health NHS Trust, Shropshire, UK

Sharon Painter, Johanne Tomlinson & Louise Warburton

152. Somerset NHS Foundation Trust, Taunton, UK

Sue Palmer, Dawn Redwood, Jo Tilley, Carinna Vickers & Tania Wainwright

153. Francis Crick Institute, London, UK

Markus Ralser

154. Manchester University NHD Foundation Trust, Manchester, UK

Pilar Rivera-Ortega

155. Diabetes UK, University of Glasgow, Glasgow, UK

Elizabeth Robertson

156. Barnsley Hospital NHS Foundation Trust, Barnsley, UK

Amy Sanderson

157. MRC-University of Glasgow Centre for Virus Research, Glasgow, UK

Janet Scott

158. Diabetes UK, London, UK

Kamini Shah

159. British Heart Foundation Centre, King's College London, London, UK

Ajay Shah

160. King's College Hospital NHS Foundation Trust, London, UK

Ajay Shah

161. University Hospitals Birmingham NHS Foundation Trust and University of Birmingham, Birmingham, UK

R. Steeds

162. Institute of Cardiovascular and Medical Sciences, BHF Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, UK

R. Touyz

163. University College London NHS Foundation Trust, London and Barts Health NHS Trust, London, UK

T. Treibel

164. Northumbria University, Newcastle upon Tyne, UK

Ioannis Vogiatzis

165. Swansea University and Swansea Welsh Network, Swansea, UK

N. Williams

166. DUK | NHS Digital, Salford Royal Foundation Trust, Salford, UK

Bob Young

167. Queen Alexandra Hospital, Portsmouth, UK

Kayode Adeniji

168. Princess Royal Hospital, Haywards Heath, UK

Daniel Agranoff & Chi Eziefula

169. Bassetlaw Hospital, Bassetlaw, UK

Ken Agwuh

170. Darent Valley Hospital, Dartford, UK

Dhiraj Ail

171. Queen Elizabeth the Queen Mother Hospital, Margate, UK

Ana Alegria

172. School of Informatics, University of Edinburgh, Edinburgh, UK

Beatrice Alex, Benjamin Bach & James Scott-Brown

173. North East and North Cumbria Ingerated, Newcastle upon Tyne, UK

Sam Allen

174. Section of Biomolecular Medicine, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK

Petros Andrikopoulos, Kanta Chechi, Marc-Emmanuel Dumas, Julian Griffin, Sonia Liggi & Zoltan Takats

175. Section of Genomic and Environmental Medicine, Respiratory Division, National Heart and Lung Institute, Imperial College London, London, UK

Petros Andrikopoulos, Marc-Emmanuel Dumas, Michael Olanipekun & Anthonia Osagie

176. John Radcliffe Hospital, Oxford, UK

Brian Angus

177. Royal Albert Edward Infirmary, Wigan, UK

Abdul Ashish

178. Manchester Royal Infirmary, Manchester, UK

Dougal Atkinson

179. MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, UK

J. Kenneth Baillie

180. Section of Molecular Virology, Imperial College London, London, UK

Wendy S. Barclay

181. Furness General Hospital, Barrow-in-Furness, UK

Shahedal Bari

182. Hull University Teaching Hospital Trust, Kingston upon Hull, UK

Gavin Barlow

183. Hillingdon Hospital, Hillingdon, UK

Stella Barnass

184. St Thomas' Hospital, London, UK

Nicholas Barrett

185. Coventry and Warwickshire, Coventry, UK

Christopher Bassford

186. St Michael's Hospital, Bristol, UK

Sneha Basude

187. Stepping Hill Hospital, Stockport, UK

David Baxter

188. Royal Liverpool University Hospital, Liverpool, UK

Michael Beadsworth

189. Bristol Royal Hospital Children's, Bristol, UK

Jolanta Bernatoniene

190. Scarborough Hospital, Scarborough, UK

John Berridge

191. Golden Jubilee National Hospital, Clydebank, UK

Colin Berry

192. Liverpool Heart and Chest Hospital, Liverpool, UK

Nicola Best

193. Centre for Inflammation Research, The Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK

Debby Bogaert & Clark D. Russell

194. James Paget University Hospital, Great Yarmouth, UK

Pieter Bothma & Darell Tupper-Carey

195. Aberdeen Royal Infirmary, Aberdeen, UK

Robin Brittain-Long

196. Adamson Hospital, Cupar, UK

Naomi Bulteel

197. Royal Devon and Exeter Hospital, Exeter, UK

Tom Burden

198. Worcestershire Royal Hospital, Worcester, UK

Andrew Burtenshaw

199. ISARIC Global Support Centre, Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK

Gail Carson, Laura Merson & Louise Sigfrid

200. Conquest Hospital, Hastings, UK

Vikki Caruth

201. The James Cook University Hospital, Middlesbrough, UK

David Chadwick

202. Dorset County Hospital, Dorchester, UK

Duncan Chambler

203. Antimicrobial Resistance and Hospital Acquired Infection Department, Public Health England, London, UK

Meera Chand

204. Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London, London, UK

Kanta Chechi

205. Royal Bournemouth General Hospital, Bournemouth, UK

Nigel Chee

206. Harrogate Hospital, Harrogate, UK

Jenny Child

207. Royal Blackburn Teaching Hospital, Blackburn, UK

Srikanth Chukkambotla

208. Edinburgh Clinical Research Facility, University of Edinburgh, Edinburgh, UK

Richard Clark, Audrey Coutts, Lorna Donelly, Angie Fawkes, Tammy Gilchrist, Katarzyna Hafezi, Louise MacGillivray, Alan Maclean, Sarah McCafferty, Kirstie Morrice, Lee Murphy & Nicola Wrobel

209. Torbay Hospital, Torquay, UK

Tom Clark

210. Northern General Hospital, Sheffield, UK

Paul Collini, Cariad Evans & Gary Mills

211. Liverpool Clinical Trials Centre, University of Liverpool, Liverpool, UK

Marie Connor, Jo Dalton, Chloe Donohue, Carrol Gamble, Michelle Girvan, Sophie Halpin, Janet Harrison, Clare Jackson, Laura Marsh, Stephanie Roberts & Egle Saviciute

212. Department of Infectious Disease, Imperial College London, London, UK

Graham S. Cooke & Shiranee Sriskandan

213. St Georges Hospital (Tooting), London, UK

Catherine Cosgrove

214. Blackpool Victoria Hospital, Blackpool, UK

Jason Cupitt & Joanne Howard

215. The Royal London Hospital, London, UK

Maria-Teresa Cutino-Moguel

216. MRC-University of Glasgow Centre for Virus Research, Glasgow, UK

Ana da Silva Filipe, Antonia Y. W. Ho, Sarah E. McDonald, Massimo Palmarini, David L. Robertson, Janet T. Scott & Emma C. Thomson

217. Salford Royal Hospital, Salford, UK

Paul Dark

218. University Hospital of North Durham, Durham, UK

Chris Dawson

219. Norfolk and Norwich University Hospital, Norwich, UK

Samir Dervisevic

220. Intensive Care Unit, Royal Infirmary Edinburgh, Edinburgh, UK

Annemarie B. Docherty & Seán Keating

221. Institute of Infection, Veterinary and Ecological Sciences, Faculty of Health and Life Sciences, University of Liverpool, Liverpool, UK

Cara Donegan & Rebecca G. Spencer

222. Salisbury District Hospital, Salisbury, UK

Phil Donnison

223. National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK

Gonçalo dos Santos Correia, Matthew Lewis, Lynn Maslen, Caroline Sands, Zoltan Takats & Panteleimon Takis

224. Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK

Gonçalo dos Santos Correia, Matthew Lewis, Lynn Maslen, Caroline Sands & Panteleimon Takis

225. Guy's and St Thomas', NHS Foundation Trust, London, UK

Sam Douthwaite, Michael MacMahon, Marlies Ostermann & Manu Shankar-Hari

226. The Royal Oldham Hospital, Oldham, UK

Andrew Drummond

227. European Genomic Institute for Diabetes, Institut Pasteur de Lille, Lille University Hospital, University of Lille, Lille, France

Marc-Emmanuel Dumas

228. McGill University and Genome Quebec Innovation Centre, Montreal, Qeubec, Canada

Marc-Emmanuel Dumas

229. National Infection Service, Public Health England, London, UK

Jake Dunning & Maria Zambon

230. Hereford Count Hospital, Hereford, UK

Ingrid DuRand

231. Southampton General Hospital, Southampton, UK

Ahilanadan Dushianthan

232. Northampton General Hospital, Northampton, UK

Tristan Dyer

233. University Hospital of Wales, Cardiff, UK

Chrisopher Fegan

234. University Hospitals Bristol NHS Foundation Trust, Bristol, UK

Adam Finn

235. Liverpool School of Tropical Medicine, Liverpool, UK

Tom Fletcher

236. Leighton Hospital, Crewe, UK

Duncan Fullerton & Elijah Matovu

237. Manor Hospital, Walsall, UK

Atul Garg

238. Scunthorpe Hospital, Scunthorpe, UK

Sanjeev Garg

239. Cambridge University Hospital, Cambridge, UK

Effrossyni Gkrania-Klotsas

240. West Suffolk NHS Foundation Trust, Bury St Edmunds, UK

Jo Godden

241. Basingstoke and North Hampshire Hospital, Basingstoke, UK

Arthur Goldsmith

242. North Cumberland Infirmary, Carlisle, UK

Clive Graham

243. Paediatric Liver, GI and Nutrition Centre and MowatLabs, King's College Hospital, London, UK

Tassos Grammatikopoulos

244. Institute of Liver Studies, King's College London, London, UK

Tassos Grammatikopoulos

245. Institute of Microbiology and Infection, University of Birmingham, Birmingham, UK

Christopher A. Green

246. Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool, UK

William Greenhalf

247. Institute for Global Health, University College London, London, UK

Rishi K. Gupta

248. NIHR Health Protection Research Unit, Institute of Infection, Veterinary and Ecological Sciences, Faculty of Health and Life Sciences, University of Liverpool, Liverpool, UK

Hayley Hardwick, Malcolm G. Semple, Tom Solomon & Lance C. W. Turtle

249. Warwick Hospital, Warwick, UK

Elaine Hardy

250. Birmingham Children's Hospital, Birmingham, UK

Stuart Hartshorn

251. Nottingham City Hospital, Nottingham, UK

Daniel Harvey

252. Glangwili Hospital Child Health Section, Carmarthen, UK

Peter Havalda

253. Alder Hey Children's Hospital, Liverpool, UK

Daniel B. Hawcutt

254. Department of Infectious Diseases, Queen Elizabeth University Hospital, Glasgow, UK

Antonia Y. W. Ho

255. Bronglais General Hospital, Aberystwyth, UK

Maria Hobrok

256. Worthing Hospital, Worthing, UK

Luke Hodgson

257. Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK

Peter W. Horby

258. Rotheram District General Hospital, Rotheram, UK

Anil Hormis

259. Virology Reference Department, National Infection Service, Public Health England, Colindale Avenue, London, UK

Samreen Ijaz

260. Royal Free Hospital, London, UK

Michael Jacobs & Padmasayee Papineni

261. Homerton Hospital, London, UK

Susan Jain

262. Airedale Hospital, Airedale, UK

Paul Jennings

263. Basildon Hospital, Basildon, UK

Agilan Kaliappan

264. The Christie NHS Foundation Trust, Manchester, UK

Vidya Kasipandian

265. University Hospital Lewisham, London, UK

Stephen Kegg

266. The Whittington Hospital, London, UK

Michael Kelsey

267. Southmead Hospital, Bristol, UK

Jason Kendall

268. Sheffield Childrens Hospital, Sheffield, UK

Caroline Kerrison

269. Royal United Hospital, Bath, UK

Ian Kerslake

270. Department of Pharmacology, University of Liverpool, Liverpool, UK

Say Khoo

271. Nuffield Department of Medicine, Peter Medawar Building for Pathogen Research, University of Oxford, Oxford, UK

Paul Klenerman

272. Translational Gastroenterology Unit, Nuffield Department of Medicine, University of Oxford, Oxford, UK

Paul Klenerman

273. Public Health Scotland, Edinburgh, UK

Susan Knight, Eva Lahnsteiner & Sarah Tait

274. Western General Hospital, Edinburgh, UK

Oliver Koch

275. Southend University Hospital NHS Foundation Trust, Southend-on-Sea, UK

Gouri Koduri

276. Hinchingbrooke Hospital, Huntingdon, UK

George Koshy & Tamas Leiner

277. Royal Preston Hospital, Fulwood, UK

Shondipon Laha

278. University Hospital (Coventry), Coventry, UK

Steven Laird

279. The Walton Centre, Liverpool, UK

Susan Larkin

280. ISARIC, Global Support Centre, COVID-19 Clinical Research Resources, Epidemic diseases Research Group, Oxford (ERGO), University of Oxford, Oxford, UK

James Lee & Daniel Plotkin

281. Centre for Health Informatics, Division of Informatics, Imaging and Data Science, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK

Gary Leeming

282. Hull Royal Infirmary, Hull, UK

Patrick Lillie

283. Nottingham University Hospitals NHS Trust:, Nottingham, UK

Wei Shen Lim

284. Darlington Memorial Hospital, Darlington, UK

James Limb

285. Queen Elizabeth Hospital (Gateshead), Gateshead, UK

Vanessa Linnett

286. Warrington Hospital, Warrington, UK

Jeff Little

287. Bristol Royal Hospital for Children, Bristol, UK

Mark Lyttle

288. St Mary's Hospital (Isle of Wight), Isle of Wight, UK

Emily MacNaughton

289. The Tunbridge Wells Hospital, Royal Tunbridge Wells, UK

Ravish Mankregod

290. Huddersfield Royal, Huddersfield, UK

Huw Masson

291. Countess of Chester Hospital, Liverpool, UK

Ruth McEwen & Lawrence Wilson

292. Frimley Park Hospital, Frimley, UK

Manjula Meda

293. Nuffield Department of Medicine, John Radcliffe Hospital, Oxford, UK

Alexander J. Mentzer

294. Department of Microbiology/Infectious Diseases, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford, UK

Alexander J. Mentzer

295. MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK

Alison M. Meynert & Murray Wham

296. St James University Hospital, Leeds, UK

Jane Minton

297. Arrowe Park Hospital, Birkenhead, UK

Kavya Mohandas

298. Great Ormond Street Hospital, London, UK

Quen Mok

299. Royal Shrewsbury Hospital, Shrewsbury, UK

James Moon

300. Addenbrookes Hospital, Cambridge, UK

Elinoor Moore

301. Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, UK

Shona C. Moore, William A. Paxton & Georgios Pollakis

302. East Surrey Hospital (Redhill), Redhill, UK

Patrick Morgan

303. Burton Hospital, Burton, UK

Craig Morris & Tim Reynolds

304. Peterborough City Hospital, Peterborough, UK

Katherine Mortimore

305. Kent and Canterbury Hospital, Canterbury, UK

Samuel Moses

306. Weston Area General Trust, Bristol, UK

Mbiye Mpenge

307. Bedfordshire Hospital, Bedfordshire, UK

Rohinton Mulla

308. Glasgow Royal Infirmary, Glasgow, UK

Michael Murphy

309. Macclesfield General Hospital, Macclesfield, UK

Thapas Nagarajan

310. Derbyshire Healthcare, Derbyshire, UK

Megan Nagel

311. Chelsea and Westminster Hospital, London, UK

Mark Nelson & Matthew K. O'Shea

312. Watford General Hospital, Watford, UK

Lillian Norris & Tom Stambach

313. EPCC, University of Edinburgh, Edinburgh, UK

Lucy Norris

314. Section of Biomolecular Medicine, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, London, UK

Michael Olanipekun

315. Imperial College Healthcare NHS Trust: London, London, UK

Peter J. M. Openshaw

316. Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK

Anthonia Osagie

317. Prince Philip Hospital, Llanelli, UK

Igor Otahal & Andrew Workman

318. George Eliot Hospital - Acute Services, Nuneaton, UK

Mark Pais

319. Molecular and Clinical Cancer Medicine, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK

Carlo Palmieri

320. Clatterbridge Cancer Centre NHS Foundation Trust, Liverpool, UK

Carlo Palmieri

321. Kettering General Hospital, Kettering, UK

Selva Panchatsharam

322. University Hospitals of North Midlands NHS Trust, North Midlands, UK

Danai Papakonstantinou

323. Russells Hall Hospital, Dudley, UK

Hassan Paraiso

324. Harefield Hospital, Harefield, UK

Brij Patel

325. Lister Hospital, Lister, UK

Natalie Pattison

326. Musgrove Park Hospital, Taunton, UK

Justin Pepperell

327. Kingston Hospital, Kingston, UK

Mark Peters

328. Queen's Hospital, Romford, UK

Mandeep Phull

329. Southport and Formby District General Hospital, Southport, UK

Stefania Pintus

330. St George's University of London, London, UK

Tim Planche

331. King's College Hospital (Denmark Hill), London, UK

Frank Post

332. Centre for Clinical Infection and Diagnostics Research, Department of Infectious Diseases, School of Immunology and Microbial Sciences, King's College London, London, UK

Nicholas Price

333. Department of Infectious Diseases, Guy's and St Thomas' NHS Foundation Trust, London, UK

Nicholas Price

334. The Clatterbridge Cancer Centre NHS Foundation, Bebington, UK

David Price

335. The Great Western Hospital, Swindon, UK

Rachel Prout

336. Ninewells Hospital, Dundee, UK

Nikolas Rae

337. Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK

Andrew Rambaut

338. Poole Hospital NHS Trust, Poole, UK

Henrik Reschreiter

339. William Harvey Hospital, Ashford, UK

Neil Richardson

340. King's Mill Hospital, Sutton-in-Ashfield, UK

Mark Roberts

341. Liverpool Women's Hospital, Liverpool, UK

Devender Roberts

342. Pinderfields Hospital, Wakefield, UK

Alistair Rose

343. North Devon District Hospital, Barnstaple, UK

Guy Rousseau

344. Queen Elizabeth Hospital, Birmingham, UK

Bobby Ruge

345. Tameside General Hospital, Ashton-under-Lyne, UK

Brendan Ryan

346. City Hospital (Birmingham), Birmingham, UK

Taranprit Saluja

347. Department of Pediatrics and Virology, St Mary's Medical School Bldg, Imperial College London, London, UK

Vanessa Sancho-Shimizu

348. The Newcastle Upon Tyne Hospitals NHS Foundation Trust, Newcastle Upon Tyne, UK

Matthias Schmid

349. NHS Greater Glasgow and Clyde, Glasgow, UK

Janet T. Scott

350. Respiratory Medicine, Institute in The Park, University of Liverpool, Alder Hey Children's Hospital, Liverpool, UK

Malcolm G. Semple

351. Broomfield Hospital, Broomfield, UK

Aarti Shah

352. Stoke Mandeville, UK

Prad Shanmuga

353. University Hospital of North Tees, Stockton-on-Tees, UK

Anil Sharma

354. Institute of Translational Medicine, University of, Liverpool, Merseyside, UK

Victoria E. Shaw

355. Royal Manchester Children's Hospital, Manchester, UK

Anna Shawcross

356. New Cross Hospital, Wolverhampton, UK

Jagtur Singh Pooni

357. Bedford Hospital, Bedford, UK

Jeremy Sizer

358. Colchester General Hospital, Colchester, UK

Richard Smith

359. University Hospital Birmingham NHS Foundation Trust, Birmingham, UK

Catherine Snelson & Tony Whitehouse

360. Walton Centre NHS Foundation Trust, Liverpool, UK

Tom Solomon

361. Chesterfield Royal Hospital, Calow, UK

Nick Spittle

362. MRC Centre for Molecular Bacteriology and Infection, Imperial College London, London, UK

Shiranee Sriskandan

363. Princess Alexandra Hospital, Harlow, UK

Nikki Staines & Shico Visuvanathan

364. Milton Keynes Hospital, Eaglestone, UK

Richard Stewart

365. Division of Structural Biology, The Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK

David Stuart

366. Royal Bolton Hopital, Farnworth, UK

Pradeep Subudhi

367. Department of Medicine, University of Cambridge, Cambridge, UK

Charlotte Summers

368. Department of Child Life and Health, University of Edinburgh, Edinburgh, UK

Olivia V. Swann

369. Royal Gwent (Newport), Newport, UK

Tamas Szakmany

370. The Royal Marsden Hospital (London), London, UK

Kate Tatham

371. Blood Borne Virus Unit, Virus Reference Department, National Infection Service, Public Health England, London, UK

Richard S. Tedder

372. Transfusion Microbiology, National Health Service Blood and Transplant, London, UK

Richard S. Tedder

373. Department of Medicine, Imperial College London, London, UK

Richard S. Tedder

374. Queen Victoria Hospital (East Grinstead), East Grinstead, UK

Jo Thomas

375. Leeds Teaching Hospitals NHS Trust, Leeds, UK

Robert Thompson

376. Royal Stoke University Hospital, Stoke-on-Trent, UK

Chris Thompson

377. Whiston Hospital, Rainhill, UK

Ascanio Tridente

378. Tropical and Infectious Disease Unit, Royal Liverpool University Hospital, Liverpool, UK

Lance C. W. Turtle

379. Croydon University Hospital, Thornton Heath, UK

Mary Twagira

380. Gloucester Royal, Gloucester, UK

Nick Vallotton

381. West Hertfordshire Teaching Hospitals NHS Trust, Hertfordshire, UK

Rama Vancheeswaran

382. North Middlesex Hospital, London, UK

Rachel Vincent

383. Medway Maritime Hospital, Gillingham, UK

Lisa Vincent-Smith

384. Royal Papworth Hospital Everard, Cambridge, UK

Alan Vuylsteke

385. Derriford (Plymouth), Plymouth, UK

Sam Waddy

386. St Helier Hospital, Sutton, UK

Rachel Wake

387. Royal Berkshire Hospital, Reading, UK

Andrew Walden

388. Royal Liverpool Hospital, Liverpool, UK

Ingeborg Welters

389. Bradford Royal infirmary, Bradford, UK

Paul Whittaker

390. Central Middlesex, London, UK

Ashley Whittington

391. Royal Cornwall Hospital (Tresliske), Truro, UK

Meme Wijesinghe

392. North Bristol NHS Trust, Bristol, UK

Martin Williams

393. St. Peter's Hospital, Runnymede, UK

Stephen Winchester

394. Leicester Royal Infirmary, Leicester, UK

Martin Wiselka

395. Grantham and District Hospital, Grantham, UK

Adam Wolverson

396. Aintree University Hospital, Liverpool, UK

Daniel G. Wootton

397. North Tyneside General Hospital, North Shields, UK

Bryan Yates

398. Queen Elizabeth Hospital, King's Lynn, UK

Peter Young

Consortia

PHOSP-COVID collaborative group

Kathryn Abel

, H. Adamali

, Davies Adeloye

, Oluwaseun Adeyemi

, Rita Adrego

, Laura Aguilar Jimenez

, Shanaz Ahmad

, N. Ahmad Haider

, Rubina Ahmed

, Nyarko Ahwireng

, Mark Ainsworth

, Asma Alamoudi

, Mariam Ali

, M. Aljaroof

, Louise Allan

, Richard Allen

, Lisa Allerton

, Lynne Allsop

, Ann Marie Allt

, Paula Almeida

, Bashar Al-Sheklly

, Danny Altmann

, Maria Alvarez Corral

, Shannon Amoils

, David Anderson

, Charalambos Antoniades

, Gill Arbane

, Ava Maria Arias

, Cherie Armour

, Lisa Armstrong

, Natalie Armstrong

, David Arnold

, H. Arnold

, A. Ashish

, Andrew Ashworth

, M. Ashworth

, Shahab Aslani

, Hosanna Assefa-Kebede

, Paul Atkin

, Catherine Atkin

, Raminder Aul

, Hnin Aung

, Liam Austin

, Cristina Avram

, Nikos Avramidis

, A. Ayoub

, Marta Babores

, Rhiannon Baggott

, J. Bagshaw

, David Baguley

, Elisabeth Bailey

, J. Kenneth Baillie

, Steve Bain

, Majda Bakali

, M. Bakau

, E. Baldry

, Molly Baldwin

, David Baldwin

, Clive Ballard

, Amita Banerjee

, Dongchun Bang

, R. E. Barker

, Laura Barman

, Perdita Barran

, Shaney Barratt

, Fiona Barrett

, Donna Basire

, Neil Basu

, Michelle Bates

, A. Bates

, R. Batterham

, Helen Baxendale

, Gabrielle Baxter

, Hannah Bayes

, M. Beadsworth

, Paul Beckett

, M. Beggs

, M. Begum

, Paul Beirne

, Murdina Bell

, Robert Bell

, Kaytie Bennett

, Eva Beranova

, Areti Bermperi

, Anthony Berridge

, Colin Berry

, Sarah Betts

, Emily Bevan

, Kamaldeep Bhui

, Michelle Bingham

, K. Birchall

, Lettie Bishop

, Karen Bisnauthsing

, John Blaikely

, Angela Bloss

, Annette Bolger

, Charlotte Bolton

, J. Bonnington

, A. Botkai

, Charlotte Bourne

, Michelle Bourne

, Kate Bramham

, Lucy Brear

, G. Breen

, Jonathon Breeze

, Katie Breeze

, Andrew Briggs

, E. Bright

, Christopher Brightling

, Simon Brill

, K. Brindle

, Lauren Broad

, Andrew Broadley

, Claire Brookes

, Mattew Broome

, Vanessa Brown

, M. Brown

, Jo Brown

, J. Brown

, Ammani Brown

, Angela Brown

, M. Brown

, Jeremy Brown

, Terry Brugha

, Nigel Brunskill

, M. Buch

, Phil Buckley

, Anda Bularga

, Ed Bullmore

, Jenny Bunker

, L. Burden

, Tracy Burdett

, David Burn

, G. Burns

, A. Burns

, John Busby

, Robyn Butcher

, Al-Tahoor Butt

, S. Byrne

, P. Cairns

, P. C. Calder

, Ellen Calvelo

, H. Carborn

, Bethany Card

, Caitlin Carr

, Liesel Carr

, G. Carson

, Penny Carter

, Anna Casey

, M. Cassar

, Jonathon Cavanagh

, Manish Chablani

, Trudie Chalder

, James D. Chalmers

, Rachel Chambers

, Flora Chan

, K. M. Channon

, Kerry Chapman

, Amanda Charalambou

, N. Chaudhuri

, A. Checkley

, Jin Chen

, Yutung Cheng

, Luke Chetham

, Caroline Childs

, Edwin Chilvers

, H. Chinoy

, A. Chiribiri

, K. Chong-James

, N. Choudhury

, Gaunab Choudhury

, Phillip Chowienczyk

, C. Christie

, Melanie Chrystal

, Cameron Clark

, David Clark

, Jude Clarke

, S. Clohisey

, G. Coakley

, Zach Coburn

, S. Coetzee

, Joby Cole

, Chris Coleman

, Florence Conneh

, David Connell

, Bronwen Connolly

, Lynda Connor

, Amanda Cook

, Shirley Cooper

, B. Cooper

, Josh Cooper

, Donna Copeland

, Tracey Cosier

, Eamon Coughlan

, Martina Coulding

, C. Coupland

, E. Cox

, Thelma Craig

, P. Crisp

, Daniele Cristiano

, Michael Crooks

, Andy Cross

, Isabel Cruz

, P. Cullinan

, D. Cuthbertson

, Luke Daines

, Matthhew Dalton

, Patrick Daly

, Alison Daniels

, P. Dark

, Joanne Dasgin

, C. David

, Anthony David

, Ffyon Davies

, Ellie Davies

, Kim Davies

, Gareth Davies

, Gwyneth Davies

, Melanie Davies

, Joy Dawson

, Camilla Dawson

, Enya Daynes

, Anthony De Soyza

, Bill Deakin

, Andrew Deans

, C. Deas

, Joanne Deery

, Sylviane Defres

, Amanda Dell

, K. Dempsey

, Emma Denneny

, J. Dennis

, A. Dewar

, Ruvini Dharmagunawardena

, Nawar Diar-Bakerly

, Caroline Dickens

, A. Dipper

, Sarah Diver

, Shalin Diwanji

, Myles Dixon

, R. Djukanovic

, Hannah Dobson

, S. L. Dobson

, Annemarie B. Docherty

, A. Donaldson

, T. Dong

, N. Dormand

, Andrew Dougherty

, Rachael Dowling

, Stephen Drain

, Katharine Draxlbauer

, Katie Drury

, Pearl Dulawan

, A. Dunleavy

, Sarah Dunn

, Catherine Dupont

, Joanne Earley

, Nicholas Easom

, Carlos Echevarria

, Sarah Edwards

, C. Edwardson

, Claudia Efstathiou

, Anne Elliott

, K. Elliott

, Yvette Ellis

, Anne Elmer

, Omer Elneima

, Hosni El-Taweel

, Teriann Evans

, Ranuromanana Evans

, D. Evans

, R. Evans

, H. Evans

, Rachael A. Evans

, Jonathon Evans

, Cerys Evenden

, Lynsey Evison

, Laura Fabbri

, Sara Fairbairn

, Alexandra Fairman

, K. Fallon

, David Faluyi

, Clair Favager

, Tamanah Fayzan

, James Featherstone

, T. Felton

, V. Ferreira

, J. Finch

, Selina Finney

, J. Finnigan

, L. Finnigan

, Helen Fisher

, S. Fletcher

, Rachel Flockton

, Margaret Flynn

, H. Foot

, David Foote

, Amber Ford

, D. Forton

, Eva Fraile

, C. Francis

, Richard Francis

, Susan Francis

, Anew Frankel

, Emily Fraser

, Rob Free

, N. French

, X. Fu

, Jonathon Fuld

, J. Furniss

, Lucie Garner

, N. Gautam

, John Geddes

, J. George

, P. George

, Michael Gibbons

, Rhyan Gill

, Mandy Gill

, L. Gilmour

, F. Gleeson

, Jodie Glossop

, Sarah Glover

, Nicola Goodman

, Camelia Goodwin

, Bibek Gooptu

, Hussain Gordon

, T. Gorsuch

, M. Greatorex

, Paul Greenhaff

, William Greenhalf

, Alan Greenhalgh

, Neil J. Greening

, John Greenwood

, Rebecca Gregory

, Heidi Gregory

, D. Grieve

, Denise Griffin

, L. Griffiths

, Anne-Marie Guerdette

, Beatriz Guillen-Guio

, Mahitha Gummadi

, Ayushman Gupta

, Sambasivarao Gurram

, Elspeth Guthrie

, Zoe Guy

, Kate Hadley

, Ahmed Haggar

, Kera Hainey

, Brigid Hairsine

, Pranab Haldar

, Lucy Hall

, Ian Hall

, Mark Halling-Brown

, R. Hamil

, Alyson Hancock

, Kia Hancock

, Neil Hanley

, Sulaimaan Haq

, Hayley Hardwick

, Tim Hardy

, E. Hardy

, Beverley Hargadon

, Kate Harrington

, Edward Harris

, Victoria C. Harris

, Ewen Harrison

, Paul Harrison

, Nicholas Hart

, Alice Harvey

, Matt Harvey

, M. Harvie

, L. Haslam

, Claire Hastie

, May Havinden-Williams

, Jenny Hawkes

, Nancy Hawkings

, Jill Haworth

, A. Hayday

, Matthew Haynes

, J. Hazeldine

, Tracy Hazelton

, Liam Heaney

, Cheryl Heeley

, Jonathon Heeney

, M. Heightman

, Simon Heller

, Max Henderson

, Helen Henson

, L. Hesselden

, Melanie Hewitt

, Victoria Highett

, T. Hillman

, T. Hiwot

, Ling-Pei Ho

, Michaela Hoare

, Amy Hoare

, J. Hockridge

, Philip Hogarth

, Ailsa Holbourn

, Sophie Holden

, L. Holdsworth

, D. Holgate

, Maureen Holland

, Leah Holloway

, Katie Holmes

, Megan Holmes

, B. Holroyd-Hind

, L. Holt

, Anil Hormis

, Alexander Horsley

, Akram Hosseini

, M. Hotopf

, Linzy Houchen-Wolloff

, Luke S. Howard

, Kate Howard

, Alice Howell

, E. Hufton

, Rachel Ann Hughes

, Joan Hughes

, Alun Hughes

, Amy Humphries

, Nathan Huneke

, E. Hurditch

, John Hurst

, Masud Husain

, Tracy Hussell

, John Hutchinson

, W. Ibrahim

, F. Ilyas

, Julie Ingham

, L. Ingram

, Diana Ionita

, Karen Isaacs

, Khalida Ismail

, T. Jackson

, Joseph Jacob

, W. Y. James

, W. Jang

, Claire Jarman

, Ian Jarrold

, Hannah Jarvis

, Roman Jastrub

, Bhagy Jayaraman

, Gisli Jenkins

, P. Jezzard

, Kasim Jiwa

, C. Johnson

, Simon Johnson

, Desmond Johnston

, Caroline Jolley

, S. Jones

, H. Jones

, L. Jones

, Ian Jones

, G. Jones

, Heather Jones

, Mark Jones

, Don Jones

, Sherly Jose

, Thomas Kabir

, G. Kaltsakas

, Vicky Kamwa

, N. Kanellakis

, Sabina Kaprowska

, Zunaira Kausar

, Natalie Keenan

, S. Kelly

, G. Kemp

, Steven Kerr

, Helen Kerslake

, Angela Key

, Fasih Khan

, Kamlesh Khunti

, Susan Kilroy

, Bernie King

, Clara King

, Lucy Kingham

, Jill Kirk

, Paaig Kitterick

, Paul Klenerman

, Lucy Knibbs

, Sean Knight

, Abigail Knighton

, Onn Min Kon

, S. Kon

, Samantha Kon

, Ania Korszun

, Ivan Koychev

, Claire Kurasz

, Prathiba Kurupati

, C. Laing

, Hanan Lamlum

, G. Landers

, Claudia Langenberg

, Lara Lavelle-Langham

, Allan Lawrie

, Cathy Lawson

, Claire Lawson

, Alison Layton

, A. Lea

, Olivia C. Leavy

, Ju Hee Lee

, Elvina Lee

, D. Lee

, Karen Leitch

, Rebecca Lenagh

, Victoria Lewis

, Joanne Lewis

, Keir Lewis

, D. Lewis

, N. Lewis-Burke

, X. Li

, Felicity Liew

, Tessa Light

, Liz Lightstone

, W. Lilaonitkul

, Lai Lim

, S. Linford

, Anne Lingford-Hughes

, M. Lipman

, Kamal Liyanage

, Arwel Lloyd

, S. Logan

, D. Lomas

, Nazir I. Lone

, Ronda Loosley

, Janet Lord

, Harpreet Lota

, Wayne Lovegrove

, Daniel Lozano-Rojas

, Alice Lucey

, Gardiner Lucy

, E. Lukaschuk

, Alison Lye

, Ceri Lynch

, S. MacDonald

, G. MacGowan

, Irene Macharia

, J. Mackie

, L. Macliver

, S. Madathil

, Gladys Madzamba

, Nick Magee

, Murphy Magtoto

, N. Mairs

, N. Majeed

, E. Major

, Flora Malein

, M. Malim

, Georgia Mallison

, William Man

, S. Mandal

, K. Mangion

, C. Manisty

, R. Manley

, Katherine March

, Stefan Marciniak

, Philip Marino

, Myril Mariveles

, Michael Marks

, Elizabeth Marouzet

, Sophie Marsh

, M. Marshall

, B. Marshall

, Jane Martin

, Adrian Martineau

, L. M. Martinez

, Nick Maskell

, Darwin Matila

, Wadzanai Matimba-Mupaya

, Laura Matthews

, Angeline Mbuyisa

, Steve McAdoo

, Hamish McAllister-Williams

, Paul McArdle

, Anne McArdle

, Danny McAulay

, Hamish J. C. McAuley

, Gerry McCann

, W. McCormick

, Jacqueline McCormick

, P. McCourt

, Celeste McCracken

, Lorcan McGarvey

, C. McGee

, K. Mcgee

, Jade McGinness

, K. McGlynn

, Andrew McGovern

, Heather McGuinness

, I. B. McInnes

, Jerome McIntosh

, Emma McIvor

, Katherine McIvor

, Laura McLeavey

, Aisling McMahon

, Michael McMahon

, L. McMorrow

, Teresa Mcnally

, M. McNarry

, J. McNeill

, Alison McQueen

, H. McShane

, Chloe Mears

, Clare Megson

, Sharon Megson

, P. Mehta

, J. Meiring

, Lucy Melling

, Mark Mencias

, R. Menke

, Daniel Menzies

, Marta Merida Morillas

, Alice Michael

, Benedict Michael

, C. A. Miller

, Lea Milligan

, Nicholas Mills

, Clare Mills

, George Mills

, L. Milner

, S. Misra

, Jane Mitchell

, Abdelrahman Mohamed

, Noura Mohamed

, S. Mohammed

, Philip Molyneaux

, Will Monteiro

, Silvia Moriera

, Anna Morley

, Leigh Morrison

, Richard Morriss

, A. Morrow

, Paul Moss

, Alistair Moss

, K. Motohashi

, N. Msimanga

, Elizabeta Mukaetova-Ladinska

, Unber Munawar

, Jennifer Murira

, Uttam Nanda

, Heeah Nassa

, Mariam Nasseri

, Rashmita Nathu

, Aoife Neal

, Robert Needham

, Paula Neill

, Stefan Neubauer

, D. E. Newby

, Helen Newell

, J. Newman

, Tom Newman

, Alex Newton-Cox

, T. E. Nichols

, Tim Nicholson

, Christos Nicolaou

, Debby Nicoll

, Athanasios Nikolaidis

, C. Nikolaidou

, C. M. Nolan

, Matthew Noonan

, C. Norman

, Petr Novotny

, Kimon Ntotsis

, Jose Nunag

, Lorenza Nwafor

, Uchechi Nwanguma

, Joseph Nyaboko

, Linda O'Brien

, C. O'Brien

, Natasha Odell

, Kate O'Donnell

, Godwin Ogbole

, G. Ogg

, Olaoluwa Olaosebikan

, Catherine Oliver

, Zohra Omar

, Peter J. M. Openshaw

, D. P. O'Regan

, Lorna Orriss-Dib

, Lynn Osborne

, Rebecca Osbourne

, Marlies Ostermann

, Charlotte Overton

, J. Owen

, J. Oxton

, Jamie Pack

, Edmund Pacpaco

, Stella-Maria Paddick

, Sharon Painter

, Erola Pairo-Castineira

, Ashkan Pakzad

, Sue Palmer

, Padmasayee Papineni

, K. Paques

, Kerry Paradowski

, Manish Pareek

, Dhruv Parekh

, H. Parfrey

, Carmen Pariante

, S. Parker

, M. Parkes

, J. Parmar

, Sheetal Patale

, Manish Patel

, B. Patel

, Suhani Patel

, Dibya Pattenadk

, M. Pavlides

, Sheila Payne

, Lorraine Pearce

, John Pearl

, Dan Peckham

, Jessica Pendlebury

, Yanchun Peng

, Chris Pennington

, Ida Peralta

, Emma Perkins

, Z. Peterkin

, Tunde Peto

, Nayia Petousi

, John Petrie

, Paul Pfeffer

, Janet Phipps

, S. Piechnik

, John Pimm

, Karen Piper Hanley

, Riinu Pius

, Hannah Plant

, S. Plein

, Tatiana Plekhanova

, Megan Plowright

, Krisnah Poinasamy

, Oliver Polgar

, L. Poll

, Julie Porter

, Joanna Porter

, Sofiya Portukhay

, Natassia Powell

, A. Prabhu

, James Pratt

, Andrea Price

, Claire Price

, Carly Price

, L. Price

, D. Price

, L. Price

, Anne Prickett

, I. Propescu

, J. Propescu

, Sabrina Prosper

, S. Pugmire

, Sheena Quaid

, Jackie Quigley

, Jennifer K. Quint

, H. Qureshi

, I. N. Qureshi

, K. Radhakrishnan

, Najib Rahman

, Markus Ralser

, Betty Raman

, Hazel Ramos

, Albert Ramos

, Jade Rangeley

, Bojidar Rangelov

, Liz Ratcliffe

, Phillip Ravencroft

, Konrad Rawlik

, Anne Reddington

, R. Reddy

, A. Reddy

, Heidi Redfearn

, Dawn Redwood

, Annabel Reed

, Meryl Rees

, Tabitha Rees

, Karen Regan

, Will Reynolds

, Carla Ribeiro

, A. Richards

, Emma Richardson

, M. Richardson

, Pilar Rivera-Ortega

, K. Roberts

, Elizabeth Robertson

, Leanne Robinson

, Emma Robinson

, Lisa Roche

, C. Roddis

, J. Rodger

, Natalie Rogers

, Gavin Ross

, Alexandra Ross

, Jennifer Rossdale

, Anthony Rostron

, Anna Rowe

, J. Rowland

, M. J. Rowland

, A. Rowland

, Sarah L. Rowland-Jones

, Maura Roy

, K. Roy

, Igor Rudan

, Richard Russell

, Emily Russell

, Gwen Saalmink

, Ramsey Sabit

, Beth Sage

, T. Samakomva

, Nilesh Samani

, A. A. Samat

, Claire Sampson

, Katherine Samuel

, Reena Samuel

, Z. B. Sanders

, Amy Sanderson

, Elizabeth Sapey

, Dinesh Saralaya

, Jack Sargant

, Carol Sarginson

, T. Sass

, Naveed Sattar

, Kathryn Saunders

, Peter Saunders

, Ruth Saunders

, Laura Saunders

, Heather Savill

, W. Saxon

, Avan Sayer

, J. Schronce

, William Schwaeble

, Janet Scott

, Kathryn Scott

, Nick Selby

, Malcolm G. Semple

, Marco Sereno

, Terri Ann Sewell

, Kamini Shah

, Ajay Shah

, P. Shah

, Manu Shankar-Hari

, M. Sharma

, Claire Sharpe

, Michael Sharpe

, Sharlene Shashaa

, Alison Shaw

, Victoria Shaw

, Karen Shaw

, Aziz Sheikh

, Sarah Shelton

, Liz Shenton

, K. Shevket

, Aarti Shikotra

, J. Short

, Sulman Siddique

, Salman Siddiqui

, J. Sidebottom

, Louise Sigfrid

, Gemma Simons

, Neil Simpson

, John Simpson

, Ananga Singapuri

, Suver Singh

, Claire Singh

, Sally Singh

, D. Sissons

, J. Skeemer

, Katie Slack

, David Smith

, Nikki Smith

, Andrew Smith

, Jacqui Smith

, Laurie Smith

, Susan Smith

, M. Soares

, Teresa Solano

, Reanne Solly

, A. R. Solstice

, Tracy Soulsby

, David Southern

, D. Sowter

, Mark Spears

, Lisa Spencer

, Fabio Speranza

, Louise Stadon

, Stefan Stanel

, R. Steeds

, N. Steele

, Mike Steiner

, David Stensel

, G. Stephens

, Lorraine Stephenson

, M. Stern

, Iain Stewart

, R. Stimpson

, Sue Stockdale

, J. Stockley

, Wendy Stoker

, Roisin Stone

, Will Storrar

, Andrew Storrie

, Kim Storton

, E. Stringer

, Sophia Strong-Sheldrake

, Natalie Stroud

, Christian Subbe

, Catherine Sudlow

, Zehra Suleiman

, Charlotte Summers

, C. Summersgill

, Debbie Sutherland

, D. L. Sykes

, R. Sykes

, Nick Talbot

, Ai Lyn Tan

, Lawrence Tarusan

, Vera Tavoukjian

, Jessica Taylor

, Abigail Taylor

, Chris Taylor

, John Paul Taylor

, Amelie Te

, H. Tedd

, Caroline Tee

, J. Teixeira

, Helen Tench

, Sarah Terry

, Susannah Thackray-Nocera

, Favas Thaivalappil

, B. Thamu

, David Thickett

, David Thomas

, S. Thomas

, Caradog Thomas

, Andrew Thomas

, T. Thomas-Woods

, A. A. Roger Thompson

, Tamika Thompson

, T. Thornton

, Matthew Thorpe

, Ryan S. Thwaites

, Jo Tilley

, N. Tinker

, Gerlynn Tiongson

, Martin Tobin

, Johanne Tomlinson

, C. Tong

, Mark Toshner

, R. Touyz

, T. Treibel

, K. A. Tripp

, Drupad Trivedi

, E. M. Tunnicliffe

, Alison Turnbull

, Kim Turner

, Sarah Turner

, Victoria Turner

, E. Turner

, Sharon Turney

, Lance Turtle

, Helena Turton

, Jacinta Ugoji

, R. Ugwuoke

, Rachel Upthegrove

, Jonathon Valabhji

, Maximina Ventura

, Joanne Vere

, Carinna Vickers

, Ben Vinson

, Ioannis Vogiatzis

, Elaine Wade

, Phillip Wade

, Louise V. Wain

, Tania Wainwright

, Lilian Wajero

, Sinead Walder

, Samantha Walker

, S. Walker

, E. Wall

, Tim Wallis

, Sarah Walmsley

, Simon Walsh

, J. A. Walsh

, Louise Warburton

, T. J. C. Ward

, Katie Warwick

, Helen Wassall

, Samuel Waterson

, L. Watson

, Ekaterina Watson

, James Watson

, M. Webster

, J. Weir McCall

, H. Welch

, Carly Welch

, B. Welsh

, Simon Wessely

, Sophie West

, Heather Weston

, Helen Wheeler

, Sonia White

, Victoria Whitehead

, J. Whitney

, S. Whittaker

, Beverley Whittam

, V. Whitworth

, Andrew Wight

, James Wild

, Martin Wilkins

, Dan Wilkinson

, Nick Williams

, N. Williams

, B. Williams

, Jenny Williams

, S. A. Williams-Howard

, Michelle Willicombe

, Gemma Willis

, James Willoughby

, Ann Wilson

, Imogen Wilson

, Daisy Wilson

, Nicola Window

, M. Witham

, Rebecca Wolf-Roberts

, Chloe Wood

, F. Woodhead

, Janet Woods

, Dan Wootton

, J. Wormleighton

, J. Worsley

, David Wraith

, Caroline Wrey Brown

, C. Wright

, S. Wright

, Louise Wright

, J. Wyles

, Inez Wynter

, C. Xie

, Moucheng Xu

, Najira Yasmin

, S. Yasmin

, Tom Yates

, Kay Por Yip

, Susan Young

, Bob Young

, A. Young

, A. J. Yousuf

, Amira Zawia

, Lisa Zeidan

, Bang Zhao

, Bang Zheng

& O. Zongo

ISARIC investigators

Kayode Adeniji

, Daniel Agranoff

, Ken Agwuh

, Katie A. Ahmed

, Dhiraj Ail

, Erin L. Aldera

, Ana Alegria

, Beatrice Alex

, Sam Allen

, Petros Andrikopoulos

, Brian Angus

, Jane A. Armstrong

, Abdul Ashish

, Milton Ashworth

, Innocent G. Asiimwe

, Dougal Atkinson

, Benjamin Bach

, J. Kenneth Baillie

, Siddharth Bakshi

, Wendy S. Barclay

, Shahedal Bari

, Gavin Barlow

, Samantha L. Barlow

, Stella Barnass

, Nicholas Barrett

, Christopher Bassford

, Sneha Basude

, David Baxter

, Michael Beadsworth

, Jolanta Bernatoniene

, John Berridge

, Colin Berry

, Nicola Best

, Debby Bogaert

, Laura Booth

, Pieter Bothma

, Benjamin Brennan

, Robin Brittain-Long

, Katie Bullock

, Naomi Bulteel

, Tom Burden

, Andrew Burtenshaw

, Nicola Carlucci

, Gail Carson

, Vikki Caruth

, Emily Cass

, Benjamin W. A. Catterall

, David Chadwick

, Duncan Chambler

, Meera Chand

, Kanta Chechi

, Nigel Chee

, Jenny Child

, Srikanth Chukkambotla

, Richard Clark

, Tom Clark

, Jordan J. Clark

, Emily A. Clarke

, Sara Clohisey

, Sarah Cole

, Paul Collini

, Marie Connor

, Graham S. Cooke

, Louise Cooper

, Catherine Cosgrove

, Audrey Coutts

, Helen Cox

, Jason Cupitt

, Maria-Teresa Cutino-Moguel

, Ana da Silva Filipe

, Jo Dalton

, Paul Dark

, Christopher Davis

, Chris Dawson

, Thushan de Silva

, Samir Dervisevic

, Oslem Dincarslan

, Alejandra Doce Carracedo

, Annemarie B. Docherty

, Cara Donegan

, Lorna Donelly

, Phil Donnison

, Chloe Donohue

, Gonçalo dos Santos Correia

, Sam Douthwaite

, Thomas M. Drake

, Andrew Drummond

, Marc-Emmanuel Dumas

, Chris Dunn

, Jake Dunning

, Ingrid DuRand

, Ahilanadan Dushianthan

, Tristan Dyer

, Philip Dyer

, Angela Elliott

, Cariad Evans

, Anthony Evans

, Chi Eziefula

, Cameron J. Fairfield

, Angie Fawkes

, Chrisopher Fegan

, Lorna Finch

, Adam Finn

, Lewis W. S. Fisher

, Lisa Flaherty

, Tom Fletcher

, Terry Foster

, Duncan Fullerton

, Carrol Gamble

, Isabel Garcia-Dorival

, Atul Garg

, Sanjeev Garg

, Tammy Gilchrist

, Michelle Girvan

, Effrossyni Gkrania-Klotsas

, Jo Godden

, Arthur Goldsmith

, Clive Graham

, Tassos Grammatikopoulos

, Christopher A. Green

, William Greenhalf

, Julian Griffin

, Fiona Griffiths

, Philip Gunning

, Rishi K. Gupta

, Katarzyna Hafezi

, Sophie Halpin

, Hayley Hardwick

, Elaine Hardy

, Ewen M. Harrison

, Janet Harrison

, Catherine Hartley

, Stuart Hartshorn

, Daniel Harvey

, Peter Havalda

, Daniel B. Hawcutt

, Ross Hendry

, Antonia Y. W. Ho

, Maria Hobrok

, Luke Hodgson

, Karl Holden

, Anthony Holmes

, Peter W. Horby

, Anil Hormis

, Joanne Howard

, Samreen Ijaz

, Clare Jackson

, Michael Jacobs

, Susan Jain

, Paul Jennings

, Rebecca L. Jensen

, Christopher B. Jones

, Trevor R. Jones

, Agilan Kaliappan

, Vidya Kasipandian

, Seán Keating

, Stephen Kegg

, Michael Kelsey

, Jason Kendall

, Caroline Kerrison

, Ian Kerslake

, Shadia Khandaker

, Say Khoo

, Katharine King

, Robyn T. Kiy

, Paul Klenerman

, Stephen R. Knight

, Susan Knight

, Oliver Koch

, Gouri Koduri

, George Koshy

, Chrysa Koukorava

, Shondipon Laha

, Eva Lahnsteiner

, Steven Laird

, Annette Lake

, Suzannah Lant

, Susan Larkin

, Diane Latawiec

, Lara Lavelle-Langham

, Andrew Law

, James Lee

, Gary Leeming

, Daniella Lefteri

, Tamas Leiner

, Lauren Lett

, Matthew Lewis

, Sonia Liggi

, Patrick Lillie

, Wei Shen Lim

, James Limb

, Vanessa Linnett

, Jeff Little

, Lucia A. Livoti

, Mark Lyttle

, Louise MacGillivray

, Alan Maclean

, Michael MacMahon

, Emily MacNaughton

, Maria Mancini

, Ravish Mankregod

, Laura Marsh

, Lynn Maslen

, Hannah Massey

, Huw Masson

, Elijah Matovu

, Nicole Maziere

, Sarah McCafferty

, Katherine McCullough

, Sarah E. McDonald

, Sarah McDonald

, Laurence McEvoy

, Ruth McEwen

, John McLauchlan

, Kenneth A. Mclean

, Manjula Meda

, Alexander J. Mentzer

, Laura Merson

, Soeren Metelmann

, Alison M. Meynert

, Nahida S. Miah

, Joanna Middleton

, Gary Mills

, Jane Minton

, Joyce Mitchell

, Kavya Mohandas

, Quen Mok

, James Moon

, Elinoor Moore

, Shona C. Moore

, Patrick Morgan

, Kirstie Morrice

, Craig Morris

, Katherine Mortimore

, Samuel Moses

, Mbiye Mpenge

, Rohinton Mulla

, Derek Murphy

, Lee Murphy

, Michael Murphy

, Ellen G. Murphy

, Thapas Nagarajan

, Megan Nagel

, Mark Nelson

, Lisa Norman

, Lillian Norris

, Lucy Norris

, Mahdad Noursadeghi

, Michael Olanipekun

, Wilna Oosthuyzen

, Peter J. M. Openshaw

, Anthonia Osagie

, Matthew K. O'Shea

, Marlies Ostermann

, Igor Otahal

, Mark Pais

, Massimo Palmarini

, Carlo Palmieri

, Selva Panchatsharam

, Danai Papakonstantinou

, Padmasayee Papineni

, Hassan Paraiso

, Brij Patel

, Natalie Pattison

, William A. Paxton

, Rebekah Penrice-Randal

, Justin Pepperell

, Mark Peters

, Mandeep Phull

, Jack Pilgrim

, Stefania Pintus

, Riinu Pius

, Tim Planche

, Daniel Plotkin

, Georgios Pollakis

, Frank Post

, Nicholas Price

, David Price

, Tessa Prince

, Rachel Prout

, Nikolas Rae

, Andrew Rambaut

, Henrik Reschreiter

, Tim Reynolds

, Will Reynolds

, Neil Richardson

, P. Matthew Ridley

, Mark Roberts

, Stephanie Roberts

, Devender Roberts

, David L. Robertson

, Alistair Rose

, Guy Rousseau

, Bobby Ruge

, Clark D. Russell

, Brendan Ryan

, Debby Sales

, Taranprit Saluja

, Vanessa Sancho-Shimizu

, Caroline Sands

, Egle Saviciute

, Matthias Schmid

, Janet T. Scott

, James Scott-Brown

, Malcolm G. Semple

, Aarti Shah

, Manu Shankar-Hari

, Prad Shanmuga

, Anil Sharma

, Catherine A. Shaw

, Victoria E. Shaw

, Anna Shawcross

, Rebecca K. Shears

, Louise Sigfrid

, Jagtur Singh Pooni

, Jeremy Sizer

, Benjamin Small

, Richard Smith

, Catherine Snelson

, Tom Solomon

, Rebecca G. Spencer

, Nick Spittle

, Shiranee Sriskandan

, Nikki Staines

, Tom Stambach

, Richard Stewart

, David Stuart

, Krishanthi S. Subramaniam

, Pradeep Subudhi

, Charlotte Summers

, Olivia V. Swann

, Tamas Szakmany

, Agnieska Szemiel

, Aislynn Taggart

, Sarah Tait

, Zoltan Takats

, Panteleimon Takis

, Jolanta Tanianis-Hughes

, Kate Tatham

, Richard S. Tedder

, Jo Thomas

, Jordan Thomas

, A. A. Roger Thompson

, Robert Thompson

, Chris Thompson

, Emma C. Thomson

, Ryan S. Thwaites

, Ascanio Tridente

, Erwan Trochu

, Darell Tupper-Carey

, Lance C. W. Turtle

, Mary Twagira

, Nick Vallotton

, Libby van Tonder

, Rama Vancheeswaran

, Rachel Vincent

, Lisa Vincent-Smith

, Shico Visuvanathan

, Alan Vuylsteke

, Sam Waddy

, Rachel Wake

, Andrew Walden

, Ingeborg Welters

, Murray Wham

, Tony Whitehouse

, Paul Whittaker

, Ashley Whittington

, Meme Wijesinghe

, Eve Wilcock

, Martin Williams

, Lawrence Wilson

, Stephen Winchester

, Martin Wiselka

, Adam Wolverson

, Daniel G. Wootton

, Andrew Workman

, Nicola Wrobel

, Bryan Yates

, Peter Young

, Maria Zambon

& J. Eunice Zhang

Contributions

F.L. recruited participants, acquired clinical samples, analyzed and interpreted data and cowrote the manuscript, including all drafting and revisions. C.E. analyzed and interpreted data and cowrote this manuscript, including all drafting and revisions. S.F. and M.R. supported the analysis and interpretation of data as well as drafting and revisions. D.S., J.K.S., S.C.M., S.A., N.M., J.N., C.K., O.C.L., O.E., H.J.C.M., A. Shikotra, A. Singapuri, M.S., V.C.H., M.T., N.J.G., N.I.L. and C.C. contributed to acquisition of data underlying this study. L.H.-W., A.A.R.T., S.L.R.-J., L.S.H., O.M.K., D.G.W., T.I.d.S. and A. Ho made substantial contributions to conception/design and implementation of this work and/or acquisition of clinical samples for this work. They have supported drafting and revisions of the manuscript. E.M.H., J.K.Q. and A.B.D. made substantial contributions to the study design as well as data access, linkage and analysis. They have supported drafting and revisions of this work. J.D.C., L.-P.H., A. Horsley, B.R., K.P., M.M. and W.G. made substantial contributions to the conception and design of this work and have supported drafting and revisions of this work. J.K.B. obtained funding for ISARIC4C, is ISARIC4C consortium co-lead, has made substantial contributions to conception and design of this work and has supported drafting and revisions of this work. M.G.S. obtained funding for ISARIC4C, is ISARIC4C consortium co-lead, sponsor/protocol chief investigator, has made substantial contributions to conception and design of this work and has supported drafting and revisions of this work. R.A.E. and L.V.W. are co-leads of PHOSP-COVID, made substantial contributions to conception and design of this work, the acquisition and analysis of data, and have supported drafting and revisions of this work. C.B. is the chief investigator of PHOSP-COVID and has made substantial contributions to conception and design of this work. R.S.T. and L.T. made substantial contributions to the acquisition, analysis and interpretation of the data underlying this study and have contributed to drafting and revisions of this work. P.J.M.O. obtained funding for ISARIC4C, is ISARIC4C consortium co-lead, sponsor/protocol chief investigator and has made substantial contributions to conception and design of this work. R.S.T. and P.J.M.O. have also made key contributions to interpretation of data and have co-written this manuscript. All authors have read and approve the final version to be published. All authors agree to accountability for all aspects of this work. All investigators within ISARIC4C and the PHOSP-COVID consortia have made substantial contributions to the conception or design of this study and/or acquisition of data for this study. The full list of authors within these groups is available in Supplementary Information.

Corresponding authors

Correspondence to Ryan S. Thwaites or Peter J. M. Openshaw.

Ethics declarations

Competing interests

F.L., C.E., D.S., J.K.S., S.C.M., C.D., C.K., N.M., L.N., E.M.H., A.B.D., J.K.Q., L.-P.H., K.P., L.S.H., O.M.K., S.F., T.I.d.S., D.G.W., R.S.T. and J.K.B. have no conflicts of interest. A.A.R.T. receives speaker fees and support to attend meetings from Janssen Pharmaceuticals. S.L.R.-J. is on the data safety monitoring board for Bexero trial in HIV+ adults in Kenya. J.D.C. is the deputy chief editor of the European Respiratory Journal and receives consulting fees from AstraZeneca, Boehringer Ingelheim, Chiesi, GSK, Insmed, Janssen, Novartis, Pfizer and Zambon. A. Horsley is deputy chair of NIHR Translational Research Collaboration (unpaid role). B.R. receives honoraria from Axcella therapeutics. R.A.E. is co-lead of PHOSP-COVID and receives fees from AstraZenaca/Evidera for consultancy on LC and from AstraZenaca for consultancy on digital health. R.A.E. has received speaker fees from Boehringer in June 2021 and has held a role as European Respiratory Society Assembly 01.02 Pulmonary Rehabilitation secretary. R.A.E. is on the American Thoracic Society Pulmonary Rehabilitation Assembly program committee. L.V.W. also receives funding from Orion pharma and GSK and holds contracts with Genentech and AstraZenaca. L.V.W. has received consulting fees from Galapagos and Boehringer, is on the data advisory board for Galapagos and is Associate Editor for the European Respiratory Journal. A. Ho is a member of NIHR Urgent Public Health Group (June 2020-March 2021). M.M. is an applicant on the PHOSP study funded by NIHR/DHSC. M.G.S. acts as an independent external and nonremunerated member of Pfizer's External Data Monitoring Committee for their mRNA vaccine program(s), is Chair of Infectious Disease Scientific Advisory Board of Integrum Scientific LLC, and is director of MedEx Solutions Ltd. and majority owner of MedEx Solutions Ltd. and minority owner of Integrum Scientific LLC. M.G.S.'s institution has been in receipt of gifts from Chiesi Farmaceutici S.p.A. of Clinical Trial Investigational Medicinal Product without encumbrance and distribution of same to trial sites. M.G.S. is a nonrenumerated member of HMG UK New Emerging Respiratory Virus Threats Advisory Group and has previously been a nonrenumerated member of the Scientific Advisory Group for Emergencies (SAGE). C.B. has received consulting fees and/or grants from GSK, AstraZeneca, Genentech, Roche, Novartis, Sanofi, Regeneron, Chiesi, Mologic and 4DPharma. L.T. has received consulting fees from MHRA, AstraZeneca and Synairgen and speakers' fees from Eisai Ltd., and support for conference attendance from AstraZeneca. L.T. has a patent pending with ZikaVac. P.J.M.O. reports grants from the EU Innovative Medicines Initiative 2 Joint Undertaking during the submitted work; grants from UK Medical Research Council, GSK, Wellcome Trust, EU Innovative Medicines Initiative, UK National Institute for Health Research and UK Research and Innovation-Department for Business, Energy and Industrial Strategy; and personal fees from Pfizer, Janssen and Seqirus, outside the submitted work.

Peer review

Peer review information

Nature Immunology thanks Ziyad Al-Aly and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Ioana Staicu was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

Additional information

Publisher's note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Graphs show classification error and Area under curve (AUC) from the 50 repeats tenfold nested cross-validation used to optimise and assess the performance of PLR testing associations with each LC outcome relative to Recovered (n = 233): Cardio_Resp (n = 398), Fatigue (n = 384), Anxiety/Depression (n = 202), GI (n = 132), ( e) Cognitive (n = 6). The distributions of classification error and area under curve (AUC) from the nested cross-validation are shown. Box plot centre line represents the Median and boundaries of the box represent interquartile range (IQR), the whisker length represent 1.5xIQR.

( a) Fibrinogen levels at 6 months were compared between pooled LC cases (n = 295) and Recovered (n = 233) and between the Cognitive group (n = 41) and Recovered (n = 233). Box plot centre line represent the Median and boundaries of the box represent interquartile range (IQR), the whisker length represents 1.5xIQR, any outliers beyond the whisker range are shown as individual dots. Median differences were compared using two-sided Wilcoxon signed-rank test *= p < 0·05, **= p < 0·01, ***= p < 0·001, ****= p < 0·0001. Unadjusted p-values are reported. b) Distribution of time from COVID-19 hospitalisation at sample collection applying CDC and NICE definitions of LC (n = 719) ( c) Upset plot of symptom groups. Horizontal coloured bars represent the number of patients in each symptom group: Cardiorespiratory (Cardio_Resp), Fatigue, Cognitive, Gastrointestinal (GI) and Anxiety/Depression (Anx_Dep). Vertical black bars represent the number of patients in each symptom combination group. To prevent patient identification, where less than 5 patients belong to a combination group, this has been represented as '<5'. The Recovered group (n = 250) were used as controls. Forest plots show Olink protein concentrations (NPX) associated with ( d) Cardio_Resp (n = 398), ( e) Fatigue (n = 342), ( f) Anx_Dep (n = 219), ( g) GI (n = 134), and ( h) Cognitive (n = 65). Error bars represent the median accuracy of the model.

Olink measured protein (NPX) were compared to chemiluminescence assays (ECL or ELISA, log2[pg/mL]) to validate our findings, where contemporaneously collected plasma samples were available (n = 58). Results from key mediators associated with LC groups were validated: CSF3, IL1R2, IL2, IL3RA, TNFa, TFF2. R= spearman rank correlation coefficient and shaded areas indicated the 95% confidence interval. Samples that fell below the lower limit of detection for a given assay were excluded and the 'n' value on each panel indicates the number of samples above this limit.

Olink measured plasma protein levels (NPX) between men and women with symptoms, divided by age (<50 or >=50years): (a) shows IL1R2 and MATN2 in the Anxiety/Depression group (<50 n = 55, >=50 n = 133), (b) shows CTSO and NFASC in the Cognitive group (<50 n = 11, >=50 n = 50). Median values were compared between men and women using two-sided Wilcoxon signed-rank test. Box plot centre line represent the Median and boundaries represent interquartile range (IQR), the whisker length represents 1.5xIQR.

Nasal cytokines measured by immunoassay in the CardioResp Group (n = 29) and Recovered (n = 31): ( a) shows IL1a, IL1b, IL-6, APO-2, TGFa, TFF2. Median differences were compared using two-sided Wilcoxon signed-rank test. Box plot centre line represents the Median and boundaries of the box represent interquartile range (IQR), the whisker length represent 1.5xIQR. ( b) Shows cytokines measured by immunoassay in paired plasma and nasal (n = 70). Correlations between IL1a, IL1b, IL-6, APO-2, TGFa and TFF2 in nasal and plasma samples were compared using Spearman's rank correlation coefficient ( R). Shaded areas indicated the 95% confidence interval of R.

Supplementary information

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Reprints and permissions

About this article

# data[].attributes.attachment_link.title
Large-scale phenotyping of patients with long COVID post-hospitalization reveals mechanistic subtypes of disease - Nature Immunology

# data[].attributes.attachment_link.description
One in ten severe acute respiratory syndrome coronavirus 2 infections result in prolonged symptoms termed long coronavirus disease (COVID), yet disease phenotypes and mechanisms are poorly understood1. Here we profiled 368 plasma proteins in 657 participants ≥3 months following hospitalization. Of these, 426 had at least one long COVID symptom and 233 had fully recovered.

# data[].attributes.headline
Factors associated with increased radiation exposure in the fixation of proximal femoral fractures

# data[].attributes.subject
Factors associated with increased radiation exposure in the fixation of proximal femoral fractures

# data[].attributes.attachment_link.readable_text
The .gov means it's official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you're on a federal government site.

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Abstract

Introduction: When using radiation intraoperatively, a surgeon should aim to keep the radiation dose as low as is reasonably achievable to obtain the therapeutic goal. We aimed to investigate factors associated with increased radiation exposure in fixation of proximal femur fractures.

Methods: We assessed 369 neck of femur fractures over a 1-year period in a district general hospital. All hip fracture subtypes that had undergone surgical fixation were included. We assessed the relationship between type of fracture, implants used and surgeon level of experience with the dose-area product (DAP; cGy/cm ²) and screening time (dS). We also looked at the quality of reduction and fixation and its effect on the radiation exposure.

Results: A total of 184 patients were included in our analysis; 185 patients who were treated with hip arthroplasty were excluded. There was a significant association between higher DAP and fracture subtype ( p = 0.001), fracture complexity ( p < 0.001), if an additional implant was used ( p = 0.001), if fixation was satisfactory ( p = 0.002) and operative time ( p < 0.001). DAP was higher with a proximal femoral nail than with a dynamic hip screw, especially when a long nail was used. There was some evidence of an association between the surgeon's level of experience and DAP exposure, although this was not statistically significant ( p = 0.069).

Conclusions: Increased radiation in proximal femur fractures is seen in the fixation of complex fractures, some subtypes, with certain types of implants used and if an additional implant was required. Surgeon seniority did not result in less radiation exposure, which is in contrast to other published studies.

Keywords: Fixation; Fluoroscopy; Proximal femur fracture; Radiation; Reduction.

PubMed Disclaimer

# data[].attributes.attachment_link.keywords[]
national center for biotechnology information

# data[].attributes.attachment_link.title
Factors associated with increased radiation exposure in the fixation of proximal femoral fractures - PubMed

# data[].attributes.attachment_link.description
Increased radiation in proximal femur fractures is seen in the fixation of complex fractures, some subtypes, with certain types of implants used and if an additional implant was required. Surgeon seniority did not result in less radiation exposure, which is in contrast to other published studies.

# data[].attributes.headline
Surgical trainee experiences from 2013 to 2023 within the United Kingdom as reported by the General Medical Council National Training Survey

# data[].attributes.subject
Surgical trainee experiences from 2013 to 2023 within the United Kingdom as reported by the General Medical Council National Training Survey

# data[].attributes.attachment_link.readable_text
The .gov means it's official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you're on a federal government site.

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

doi: 10.1016/j.surge.2023.11.005.

Affiliations

¹ Department of Surgery, Dartford and Gravesham NHS Trust, Darenth Wood Road, Dartford, DA2 8DA, UK. Electronic address: n.donald@doctors.org.uk.

² Department of Trauma and Orthopaedics, London North West University Hospitals NHS Trust, UK; Imperial College London, UK.

Free article

Free article

doi: 10.1016/j.surge.2023.11.005.

Affiliations

¹ Department of Surgery, Dartford and Gravesham NHS Trust, Darenth Wood Road, Dartford, DA2 8DA, UK. Electronic address: n.donald@doctors.org.uk.

² Department of Trauma and Orthopaedics, London North West University Hospitals NHS Trust, UK; Imperial College London, UK.

Abstract

Introduction: The General Medical Council (GMC) issues annual surveys to all doctors within the United Kingdom (UK) in a formal postgraduate training scheme. This facilitates the monitoring of experiences for quality assurance purposes. Low job satisfaction has been associated with heightened levels of burnout and staff turnover, alongside deteriorating clinical care and productivity levels.

Methods: We gathered and extracted data from the publicly available online GMC reporting tool. Data ranged from 2013 to 2023 and spanned 12 postgraduate surgical training programmes across all 18 indicators available. In total, 198 individual metrics were recorded, in addition to burnout. We conducted trend analysis and yearly average mean scores for individual metrics, burnout and geographical differences for 141 individual training programmes within the 16 training regions.

Results: Of the 198 metrics analysed, 83 (42 ​%) were found to have statistically significant negative trends (P ​< ​0.05), in comparison to 24 (12 ​%) with positive trends. 5 specialities had over 50 ​% of metrics showing a significant negative trend. Overall satisfaction was negative in all 12 programmes, with eight reaching significance (P ​< ​0.05). Of 141 individual training programmes, 29 ​% showed a significantly negative trend in overall satisfaction, with 1 ​% demonstrating a significant positive trend (P ​< ​0.05).

Conclusion: Our study is the first to explore long-term trends in trainee reported surgical training experiences within the UK. Our data have revealed widespread worsening trainee reported experiences and dissatisfaction across multiple specialities and geographical regions, especially in key areas of overall satisfaction, self-development, and clinical supervision.

Keywords: Burnout; Job satisfaction; Medical education; Personal satisfaction; Physicians; Productivity; Psychology; Surgery; Surveys and questionnaires; Training; United Kingdom.

PubMed Disclaimer

Conflict of interest statement

Declaration of competing interest The authors declare no conflict of interest.

Similar articles

Satisfaction of doctors with their training: evidence from UK.

Gregory S, Demartini C. Gregory S, et al. BMC Health Serv Res. 2017 Dec 29;17(1):851. doi: 10.1186/s12913-017-2792-0. BMC Health Serv Res. 2017. PMID: 29284467 Free PMC article.

Building a sustainable rural physician workforce.

Ostini R, McGrail MR, Kondalsamy-Chennakesavan S, Hill P, O'Sullivan B, Selvey LA, Eley DS, Adegbija O, Boyle FM, Dettrick Z, Jennaway M, Strasser S. Ostini R, et al. Med J Aust. 2021 Jul;215 Suppl 1:S5-S33. doi: 10.5694/mja2.51122. Med J Aust. 2021. PMID: 34218436

A new tool to evaluate postgraduate training posts: the Job Evaluation Survey Tool (JEST).

Wall D, Goodyear H, Singh B, Whitehouse A, Hughes E, Howes J. Wall D, et al. BMC Med Educ. 2014 Oct 2;14:210. doi: 10.1186/1472-6920-14-210. BMC Med Educ. 2014. PMID: 25277827 Free PMC article.

Appropriate Medical Staffing Improves Patient Safety, Training and Doctor Wellbeing.

Hunter C, Thorne A, Fallon J, Stevenson AJ. Hunter C, et al. Cureus. 2022 Nov 30;14(11):e32071. doi: 10.7759/cureus.32071. eCollection 2022 Nov. Cureus. 2022. PMID: 36600851 Free PMC article.

Evidence Brief: The Quality of Care Provided by Advanced Practice Nurses [Internet].

McCleery E, Christensen V, Peterson K, Humphrey L, Helfand M. McCleery E, et al. Washington (DC): Department of Veterans Affairs (US); 2014 Sep. Washington (DC): Department of Veterans Affairs (US); 2014 Sep. PMID: 27606392 Free Books & Documents. Review.

# data[].attributes.attachment_link.keywords[]
national center for biotechnology information

# data[].attributes.attachment_link.title
Surgical trainee experiences from 2013 to 2023 within the United Kingdom as reported by the General Medical Council National Training Survey - PubMed

# data[].attributes.attachment_link.description
Our study is the first to explore long-term trends in trainee reported surgical training experiences within the UK. Our data have revealed widespread worsening trainee reported experiences and dissatisfaction across multiple specialities and geographical regions, especially in key areas of overall s ...

# data[].attributes.headline
Conference Abstract - 424 Enhancing patient satisfaction in outpatient hysteroscopy: a comprehensive audit at east kent hospitals

# data[].attributes.subject
Conference Abstract - 424 Enhancing patient satisfaction in outpatient hysteroscopy: a comprehensive audit at east kent hospitals

# data[].attributes.attachment_link.provider_name
International Journal of Gynecologic Cancer

# data[].attributes.attachment_link.title
424 Enhancing patient satisfaction in outpatient hysteroscopy: a comprehensive audit at east kent hospitals

# data[].attributes.attachment_link.description
Introduction/Background This quality improvement project endeavors to evaluate and enhance patient satisfaction in outpatient hysteroscopy procedures at East Kent Hospitals. Our primary objectives include benchmarking against national standards, identifying areas for improvement, and fostering evidence-based decision-making in gynecological care. Methodology We conducted a meticulous audit encompassing outpatient hysteroscopy clinics at WHH, BHD, KCH, and QEQM, involving a diverse sample of 100 patients. The audit spanned from February 2023 to September 2023. Results Pre-Procedure Information: 73% of patients received written information before the procedure, slightly below the national average of 87%. Waiting Area and Facilities: 40% of patients rated our facilities as excellent, while 16% perceived them as poor/fair. Pain Management: 60% received painkillers before their appointments. 12% expressed a wish for painkillers, surpassing the 7% national figure. The mean pain score for our patients was 4.8, indicating a favorable experience compared to the national average of 5.2. Pain Perception: Despite favorable scores, patients reported pain as more intense than their typical menstrual experience. Service Satisfaction: An impressive 83% rated our service 10/10. 5% scored it as 9/10. 5% scored it as 8/10. 7% did not provide a response. Conclusion Our findings reveal commendable patient consultation practices, yet opportunities for improvement in pain management and facility communication. With a focus on personalized care, increased communication regarding painkillers, and addressing facility concerns, we aim to elevate the outpatient hysteroscopy experience for our patients. We believe that sharing these insights at an international medical conference will contribute to the broader discourse on optimizing patient satisfaction in gynecological care. Disclosures .

# data[].attributes.headline
30-day Morbidity and Mortality after Cholecystectomy for Benign Gallbladder Disease (AMBROSE): A Prospective, International Collaborative Cohort Study

# data[].attributes.subject
30-day Morbidity and Mortality after Cholecystectomy for Benign Gallbladder Disease (AMBROSE): A Prospective, International Collaborative Cohort Study

# data[].attributes.attachment_link.readable_text
* Geoffrey Yuet Mun WONG, Royal North Shore Hospital, St Leonards, Australia

† Himanshu WADHAWAN, Forth Valley Royal Hospital, Larbert, United Kingdom

‡ Victor ROTH CARDOSO, University of Birmingham, Birmingham, United Kingdom

§ Laura BRAVO MERODIO, University of Birmingham, Birmingham, United Kingdom

∥ Yashasvi RAJEEV, Royal Brompton Hospital, Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom

¶ Ricardo David MALDONADO, Power Stats Statistical Consulting, West Ryde, Australia

# Alessandro MARTININO, University of Illinois Chicago, Chicago, Illinois, United States of America

** Vignesh BALASUBRAMANIAM, Ysbyty Gwynedd Hospital, Bangor, United Kingdom

†† Aabid ASHRAF, Maharishi Markandeshwar Medical College And Hospital, Solan, India

‡‡ Adeela SIDDIQUI, Patel Hospital Karachi, Karachi, Pakistan

§§ Ahmad Ghassan AL-SHKIRAT, Jordan University Hospital, Amman, Jordan

∥∥ Ahmed MOHAMMED ABU-ELFATTH, Assiut University Hospital, Assiut, Egypt

¶¶ Ajay GUPTA, Queen Elizabeth Hospital, Gateshead, United Kingdom

## Akram ALKASEEK, Gharyan Central Hospital, Gharyan, Libya

*** Amel OUYAHIA, Medical Research Institute Hospital, Université Ferhat Abbas, Setif, Algeria

††† Amira SAID, Darent Valley Hospital, Dartford, United Kingdom

‡‡‡ Anshuman PANDEY, Dr Ram Manohar Lohia Institute of Medical Sciences, Lucknow, India

§§§ Ashwani KUMAR, Government Medical College, Patiala, India

∥∥∥ Baila MAQBOOL, University of New Mexico, Albuquerque, United States of America

¶¶¶ Carlos A. MILLÁN, Hospital San José, Bogota, Colombia

### Cheena SINGH, Maharishi Markandeshwar Medical College And Hospital, Solan, India

**** Diana Alejandra PANTOJA PACHAJOA, Clinica Universitaria Reina Fabiola, Córdoba, Argentina

†††† Dmitry Mikhailovich ADAMOVICH, Gomel State Medical University, Gomel, Belarus

‡‡‡‡ Enrique PETRACCHI, Hospital Dr. Cosme Argerich, Buenos Aires, Argentina

§§§§ Fariha ASHRAF, Patel Hospital, Karachi, Pakistan

∥∥∥∥ Marco CLEMENTI, San Salvatore L'Aquila, University of L'Aquila, L'Aquila, Italy

¶¶¶¶ Francesk MULITA, General University Hospital of Patras, Patras, Greece

#### Gad Amram MAROM, Department of General Surgery, Hadassah Hebrew University Medical Center, Jerusalem, Israel

***** Gamaleldeen ABDULAAL, Southend University Hospital, Southend-on-Sea, United Kingdom

††††† Georgios-Ioannis VERRAS, General Hospital of Patras, Patras, Greece

‡‡‡‡‡ Giacomo CALINI, University Hospital of Udine - Santa Maria della Misericordia, Udine, Italy

§§§§§ Gianluigi MORETTO, Pederzoli Hospital, Peschiera del Garda, Italy

∥∥∥∥∥ Hossam ELFEKI, Mansoura University Hospital, Mansoura, Egypt

¶¶¶¶¶ Hui LIANG, Second Affiliated Hospital of Nanchang University, Nanchang, China

##### Humam JALAAWIY, Ad Dewania Teaching Hospital, Ad Dewania, Iraq

****** Ibrahim ELZAYAT, Aswan University Hospital, Aswan, Egypt

†††††† Jayanta Kumar DAS, Nazareth Hospital, Shillong, India

‡‡‡‡‡‡ Jose Miguel ACEVES-AYALA, Hospital Civil de Guadalajara Dr. Juan I. Menchaca, Guadalajara, Mexico

§§§§§§ Kazi Taslima AHMED, Darent Valley Hospital, Dartford, United Kingdom

∥∥∥∥∥∥ Luca DEGRATE, Fondazione IRCCS San Gerardo dei Tintori, Monza, Italy

¶¶¶¶¶¶ Manisha AGGARWAL, Jain Multispeciality Hospital, Khanna, India

###### Mohammed Ahmed OMAR, Qena University Hospital, Qena, Egypt

******* Mounira RAIS, CHU Saadna Abdenour De Sétif, Setif, Algeria

††††††† Muhammed ELHADI, Tripoli University Hospital, Tripoli, Libya

‡‡‡‡‡‡‡ Nasser SAKRAN, Faculty of Medicine, Bar-Ilan University, Ramat Gan, Israel

§§§§§§§ Rajesh BHOJWANI, Santokba Durlabhji Memorial Hospital, Jaipur, India

∥∥∥∥∥∥∥ Ramesh AGARWALLA, Fortis Hospital, West Bengal, India

¶¶¶¶¶¶¶ Samir KANAAN, Tishreen University Hospital, Latakia, Syria

####### Sarnai ERDENE, Mongolian National University of Medical Sciences, Ulaanbaatar, Mongolia

******** Serge CHOOKLIN, Lviv Regional Clinical Hospital, Lviv, Ukraine

†††††††† Suhail KHUROO, SMVD Narayana Superspeciality Hospital, Katra, India

‡‡‡‡‡‡‡‡ Surrendar DAWANI, Dr. Ziauddin Hospital Clifton campus, Karachi, Pakistan

§§§§§§§§ Syed Tanseer ASGHAR, Kulsum International Hospital, Islamabad, Pakistan

∥∥∥∥∥∥∥∥ Tak Kwan James FUNG, John Radcliffe Hospital, Oxford, United Kingdom

¶¶¶¶¶¶¶¶ Taryel OMAROV, Azerbaijan Medical University, Baku, Azerbaijan

######## Valentin Titus GRIGOREAN, Bagdasar Arseni Emergency Clinical Hospital, Bucharest, Romania

********* Zdenko BORAS, Clinical Hospital Osijek, Osijek, Croatia

††††††††† Georgios V. GKOUTOS, Centre for Health Data Science, University of Birmingham, United Kingdom

‡‡‡‡‡‡‡‡‡ Rishi SINGHAL, University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom

§§§§§§§§§ Kamal MAHAWAR, South Tyneside and Sunderland NHS Trust, Sunderland, United Kingdom

Funding Statement: Upper GI Unit, Birmingham Heartlands Hospital, University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom.

Data Access Statement: The anonymized data for this study can be made available upon request.

Author Contributions

Conflict of Interest Declaration: The authors declare that they have no affiliations with or involvement in any organization or entity with any financial interests in the subject matter or materials discussed in this manuscript.

Supplemental Digital Content is available for this article. Direct URL citations are provided in the HTML and PDF versions of this article on the journal's website, www.annalsofsurgery.com.

# data[].attributes.attachment_link.title
30-day Morbidity and Mortality after Cholecystectomy for... : Annals of Surgery

# data[].attributes.attachment_link.description
a gap in the knowledge of the current practice and variations on a global level. Methods: A prospective, international, observational collaborative cohort study of consecutive patients undergoing cholecystectomy for benign gallbladder disease from participating hospitals in 57 countries between January 1 and June 30, 2022, was performed.

# data[].attributes.headline
Real‐world data of a digitally enabled, time‐restricted eating weight management program in public sector workers living with overweight and obesity in the United Kingdom: A service evaluation of the Roczen program

# data[].attributes.subject
Real‐world data of a digitally enabled, time‐restricted eating weight management program in public sector workers living with overweight and obesity in the United Kingdom: A service evaluation of the Roczen program

# data[].attributes.body
weight management program in public sector workers living

with overweight and obesity in the United Kingdom: A

service evaluation of the Roczen program

# data[].attributes.headline
Use of Temporally Validated Machine Learning Models To Predict Outcomes of Percutaneous Nephrolithotomy Using Data from the British Association of Urological Surgeons Percutaneous Nephrolithotomy Audit

# data[].attributes.subject
Use of Temporally Validated Machine Learning Models To Predict Outcomes of Percutaneous Nephrolithotomy Using Data from the British Association of Urological Surgeons Percutaneous Nephrolithotomy Audit

# data[].attributes.attachment_link.description
We have developed a machine learning–based decision aid to provide patient-specific
predictions for counselling patients and perioperative planning before percutaneous
nephrolithotomy. The application is available online at https://endourology.shinyapps.io/PCNL_Demographics/.

# data[].attributes.headline
Strengthening TikTok Content Analysis in Academia Using Follower Count and Engagement

# data[].attributes.subject
Strengthening TikTok Content Analysis in Academia Using Follower Count and Engagement

# data[].attributes.attachment_link.readable_text
Letter to the Editor

¹ Urology Department, Darent Valley Hospital, Dartford, United Kingdom

² Dermatology Department, Barts Health NHS Trust, London, United Kingdom

Corresponding Author:

Serena Ramjee, MBBS

Urology Department

Darent Valley Hospital

Darenth Wood Road

Dartford, DA2 8DA

United Kingdom

Phone: 44 1322 428100

Email: serena.ramjee1@nhs.net

We read with great interest Abdelnour et al's paper titled "Skin of color representation for atopic dermatitis on TikTok: cross-sectional analysis" [] and express our gratitude for the findings.

Using the search term #eczema in July 2022, the study evaluated the representation of patients with skin of color (SoC) and the quality of atopic dermatitis videos on TikTok. A review of 119 eligible videos revealed that physicians produced significantly higher-quality content than nonphysicians but may underrepresent SoC. Viewer count was a secondary measure, with its mean value lower for physicians compared to nonphysicians, though the difference was not significant. The authors noted that this lower viewer count may limit the impact of better SoC representation in physicians' videos. However, we believe that this conclusion cannot be made without further analysis.

Using the viewer count, one may infer that physician content is less popular. However, in instances where there is an insignificant difference in viewer count between sources, this measure alone provides limited information. On TikTok, a view is "counted" within the 3 seconds of playback, meaning a user does not have to view the entire video. Additionally, the viewer count corresponds to the number of times a video has been played rather than unique views []. These factors, coupled with TikTok automatically replaying its videos once they finish, mean the viewer count does not reflect the number of individuals that have viewed a video.

Follower count and engagement (likes, saves, shares, and comments) provide additional context. These measures, alongside viewer count, enable the calculation of a video's engagement rate and reach percentage (view rate). Engagement rate estimates the percentage of viewers that engage with a video (engagement×100/viewer count) [], whereas reach percentage estimates the percentage of a source's followers that view a video (viewer count×100/followers) []. Marketing companies suggest a "good" engagement rate lies between 1% to 5% [] and define the average reach percentage as 14.49% []. To demonstrate the application of these formulas, we reviewed the results from Pagani et al [] below.

This cross-sectional study screened the top 50 videos when searching "slugging" (defined as thickly coating the skin with a petrolatum-based ointment like Vaseline and can form the final step of a nighttime skincare routine []) on TikTok and analyzed their upload source, content, and quality. Videos were categorized by source into health care providers, influencers, and others. Assessing follower count and engagement (likes and comments) revealed that although influencers have a nonsignificantly lower median viewer count than health care providers (94,500 vs 102,150), their videos had a greater reach percentage (65.3% vs 24.9%) and engagement rate (8.1% vs 4.3%). These values suggest that influencers created more engaging content, which may be better promoted by TikTok's algorithm and result in a higher viewer count long term.

We observe that TikTok content analysis is becoming a prevailing means of understanding public dermatology-related information, an unsurprising trend since the platform's video-based format favors dermatology's visual nature, and believe follower count and engagement aid this analysis. Regarding the work of Abdelnour et al [], these measures may assist in determining the impact of improved SoC representation in physician-produced atopic dermatitis videos. If these measures are low, targeted recommendations for improving engagement and reach can be suggested, such as integrating popular trends or cross-promoting content.

Conflicts of Interest

None declared.
Editorial Notice
The corresponding author of "Skin of Color Representation for Atopic Dermatitis on TikTok: Cross-Sectional Analysis" declined to respond to this letter.

‎

Edited by T Leung; This is a non-peer-reviewed article. submitted 05.12.23; accepted 11.01.24; published 30.01.24

©Serena Ramjee, Zeeshaan-ul Hasan. Originally published in JMIR Dermatology (http://derma.jmir.org), 30.01.2024.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Dermatology, is properly cited. The complete bibliographic information, a link to the original publication on http://derma.jmir.org, as well as this copyright and license information must be included.

We read with great interest Abdelnour et al's paper titled "Skin of color representation for atopic dermatitis on TikTok: cross-sectional analysis" [] and express our gratitude for the findings.

Using the search term #eczema in July 2022, the study evaluated the representation of patients with skin of color (SoC) and the quality of atopic dermatitis videos on TikTok. A review of 119 eligible videos revealed that physicians produced significantly higher-quality content than nonphysicians but may underrepresent SoC. Viewer count was a secondary measure, with its mean value lower for physicians compared to nonphysicians, though the difference was not significant. The authors noted that this lower viewer count may limit the impact of better SoC representation in physicians' videos. However, we believe that this conclusion cannot be made without further analysis.

Using the viewer count, one may infer that physician content is less popular. However, in instances where there is an insignificant difference in viewer count between sources, this measure alone provides limited information. On TikTok, a view is "counted" within the 3 seconds of playback, meaning a user does not have to view the entire video. Additionally, the viewer count corresponds to the number of times a video has been played rather than unique views []. These factors, coupled with TikTok automatically replaying its videos once they finish, mean the viewer count does not reflect the number of individuals that have viewed a video.

Follower count and engagement (likes, saves, shares, and comments) provide additional context. These measures, alongside viewer count, enable the calculation of a video's engagement rate and reach percentage (view rate). Engagement rate estimates the percentage of viewers that engage with a video (engagement×100/viewer count) [], whereas reach percentage estimates the percentage of a source's followers that view a video (viewer count×100/followers) []. Marketing companies suggest a "good" engagement rate lies between 1% to 5% [] and define the average reach percentage as 14.49% []. To demonstrate the application of these formulas, we reviewed the results from Pagani et al [] below.

This cross-sectional study screened the top 50 videos when searching "slugging" (defined as thickly coating the skin with a petrolatum-based ointment like Vaseline and can form the final step of a nighttime skincare routine []) on TikTok and analyzed their upload source, content, and quality. Videos were categorized by source into health care providers, influencers, and others. Assessing follower count and engagement (likes and comments) revealed that although influencers have a nonsignificantly lower median viewer count than health care providers (94,500 vs 102,150), their videos had a greater reach percentage (65.3% vs 24.9%) and engagement rate (8.1% vs 4.3%). These values suggest that influencers created more engaging content, which may be better promoted by TikTok's algorithm and result in a higher viewer count long term.

We observe that TikTok content analysis is becoming a prevailing means of understanding public dermatology-related information, an unsurprising trend since the platform's video-based format favors dermatology's visual nature, and believe follower count and engagement aid this analysis. Regarding the work of Abdelnour et al [], these measures may assist in determining the impact of improved SoC representation in physician-produced atopic dermatitis videos. If these measures are low, targeted recommendations for improving engagement and reach can be suggested, such as integrating popular trends or cross-promoting content.

# data[].attributes.attachment_link.title
Strengthening TikTok Content Analysis in Academia Using Follower Count and Engagement

# data[].attributes.attachment_link.description
Letter to the Editor 1 Urology Department, Darent Valley Hospital, Dartford, United Kingdom 2 Dermatology Department, Barts Health NHS Trust, London, United Kingdom Serena Ramjee, MBBS Urology Department Darent Valley Hospital Darenth Wood Road Dartford, DA2 8DA United Kingdom Phone: 44 1322 428100 Email: serena.ramjee1@nhs.net We read with great interest Abdelnour et al's paper titled "Skin of color representation for atopic dermatitis on TikTok: cross-sectional analysis" [] and express our gratitude for the findings.

# data[].attributes.headline
Acute Pancreatitis Masquerading as ST-elevation Myocardial Infarction (STEMI)

# data[].attributes.subject
Acute Pancreatitis Masquerading as ST-elevation Myocardial Infarction (STEMI)

# data[].attributes.body
Infarction (STEMI)

# data[].attributes.headline
Telemedicine Clinics in General and Colorectal Surgery During the COVID-19 Pandemic: Patient Reported Outcomes

# data[].attributes.subject
Telemedicine Clinics in General and Colorectal Surgery During the COVID-19 Pandemic: Patient Reported Outcomes

# data[].attributes.body
Surgery During the COVID-19 Pandemic: PatientReported Outcomes

# data[].attributes.headline
Step forward towards treat-to-target management of giant cell arteritis: patients stratification aiming to targeted remission – updated guidelines

# data[].attributes.subject
Step forward towards treat-to-target management of giant cell arteritis: patients stratification aiming to targeted remission – updated guidelines

# data[].attributes.attachment_link.readable_text
Step forward towards treat-to-target management of giant cell arteritis: patients stratification aiming to targeted remission - updated guidelines

Abstract

Background

The aim of this work is to develop guidelines for health care professionals in the giant cell arteritis diagnosis and management, based on patients' stratification and targeted outcome measures.

Results

Fourteen expert panel had completed the two rounds surveys. After the end of round two, twenty three recommendations were released distributed on 8 domains. The percentage of the agreement on the recommendations was 76.9% to 100%. All 23 key questions were answered at the end of the second round with agreement upon.

Conclusion

Patient stratification facilitate the initiation of an appropriate management approach for patients with giant cell arteritis aiming at achieving targeted disease remission state and prevention of visual loss and/or development of ischaemic events. Treat to Target approach is a new concept in giant cell arteritis management which aims to provide tight control to achieve and maintain disease remission. This work defined the treatment targets in relation to the disease stage.

Background

GCA is a medical emergency as it poses a risk of sudden irreversible loss of vision, stroke, tongue or scalp necrosis or other peripheral limb ischaemic events. However, there has been a misconception by the medical healthcare professionals that GCA is a headache disease of older adults which shows swift and good response to glucocorticoid therapy [ 5]. Such imposing impression of the disease made it less appealing to the medical community particularly the rheumatologists [ 4]. In clinical practice GCA can be multifaceted. This has been attributed to the acute onset and seriousness of the disease, diagnostic obscurity, particularly as the patients tend to seek advice from variable medical specialities, as well as the morbidity associated with GCA treatment [ 5]. Emerging evidence suggests that this naive concept of GCA should be dumped. This has been supported by the advances in the investigation and management of the disease. The definition of a specific ultrasonography (US) pattern in GCA has transformed the management approach of this disease in day-to-day standard practice [ 6, 7, 8].

Over the past decade there has been an increased awareness of GCA. Recent studies have broadened both the GCA diagnostic and treatment spectrum [ 9, 10]. However, despite these fundamental developments, many critical clinical questions remain unanswered for GCA which has affected the key areas of management. Furthermore, there is large heterogeneity in treatment strategies of GCA in clinical practice. These critical gaps in knowledge and medical care highlighted the imperative need to update the current management recommendation and develop improved diagnostic pathways, aiming to set up individualized and targeted management approach for GCA patients. The objective of this guideline is to provide up-to-date, evidence-based recommendations for the targeted assessment and management of GCA.

Methods

Design

Using a multi-step process strategy, the GCA consensus treatment guidelines were produced based on study. The Clinical, Evidence-based, Guidelines (CEG) guideline development methodology, which entails reaching a consensus based on the majority of available scientific data and clinical experience, served as the basis for the study design. With the ultimate aim of offering an expert opinion, the objective is to ascertain the degree of agreement among experts regarding a specific topic. The work complied with the meta-analyses and recommended publishing items for systematic reviews reporting requirements [ 11].

Study teams

Core team

To supervise, plan, and support the development of the project's scope and preliminary clinical questions, as well as the appointment of the expert panel and article drafting. The project's original PICOT clinical questions and project scope were developed with support from the core team. Using the PICOT process helps develop a careful and thoughtful question that makes the search for evidence easier, Formulate the PICOT question in general terms: Based on the EBSCO Health example, while P = GCA patients, I = making consensus via online survey rounds, C = the well-known evidence based previous studies, and O = development of GCA Treat-to-Target management guidelines.

Key questions used to develop the guidelines

A set of structured key questions (supplement 1) that identify the target population, the approach taken in the investigation, the comparison(s) employed, the outcomes used to quantify efficacy, effectiveness, or risk, as well as time (PICOT), served as the focal point of these guidelines [ 12]. The following procedures were followed in order to gather the evidence needed to respond to the clinical questions: developing the clinical questions, organising the questions, looking for evidence, critically assessing and selecting the evidence, presenting the findings, and formulating recommendations. The questions served as the foundation for the methodical literature search, which led to the development of the clinical treatment guidelines.

Literature review team

The extraction of data and the quality of evidence assessment must be completed in order to perform the literature search. The team was guided by an experienced consultant for literature reviews, and an expert in methodology assisted in conducting the study of the literature based on the particular research questions that were selected to centre on GCA management.

Data sources

Using the PubMed/MEDLINE, EMBASE, and Cochrane databases, a systematic literature search was conducted to obtain appropriate evidence-based background knowledge for deliberations. The experts in charge of the literature review revised the data abstraction, published recommendations, and quality of evidence rating [ 13, 14]. They performed this review by providing a comprehensive list of recommendations for the management of GCA, which was based on both their own clinical expertise and the available research evidence. The Oxford Centre for Evidence-based Medicine (CEBM) approach was used to determine the level of evidence for each component (supplement 2) [ 14].

Study selection

Relevant studies were selected by applying inclusion and exclusion criteria to the literature retrieved with the search strategies.

Inclusion criteria

Systematic reviews, uncontrolled trials, randomised controlled trials (RCTs), observational studies (cohort, case control, and cross-sectional), and articles with economic evaluations were among the articles that were included. Trials were considered eligible if participants with GCA from any type of healthcare setting and therapy were included, independent of gender. The classification evidence and recommendations utilised in the included research should be clearly specified. Additionally, the formal procedure (Delphi exercise, panel conference) for formulating recommendations was described.

Exclusion criteria

Editorials, commentary, conference abstracts, narrative/personal reviews that do not rely on evidence, and submissions without an English translation were excluded.

Expert panel

Those are going to be chosen by the core team. In addition to actively participating in GCA-related scientific research, participants should possess professional expertise, training, and experience..

Target audience

The purpose of these guidelines is to support medical professionals who monitor and treat patients with GCA. Additionally, patients and those in charge of commissioning care for patients with GCA in the National Health Service should find the guidelines to be a useful resource.

Delphi

The Delphi procedure is a tried-and-true method designed to find consensus views among experts in the field in order to address research question(s). Its system is built around a sequence of expert-addressed questionnaires, or "rounds" [ 15].

Consensus process

To reach a consensus on the GCA's T2T (Treat to Target) strategy, two Delphi rounds were conducted. The structured Delphi method guarantees that each participant's opinion is given equal weight. Online surveys were used to carry out the Delphi process. Ten items related to the GCA treatment plan were included in the first round of the electronic questionnaire.

Voting process

Voting was conducted in two time-limited rounds via live online delivering. Every task force member received an invitation to participate and advance notice of the start and end times of each voting session. Votes were collected and processed anonymously, and special access links were distributed. During the voting process, feedback on possible ambiguity, unidentified overlaps, and rephrasing of each statement was received. Voting on the statements was restricted to task force members alone.

Chronogram of Delphi rounds

The first round took place between 3rd Feb -8th Feb 2023 (6 days). The aspects about which respondents did not reach consensus in this first round were revised in view of the comments and included in the second round. The second round took place on 19th of Feb 2023 (11 days after the first round) and lasted for 6 days (till 24th of Feb 2023).

Rating

Every statement received a score ranging from 1 to 9, where 1 denoted "complete disagreement" and 9 represented "complete agreement." In general, the numbers 1-3, 4-6, and 7-9 stand for disagreement, uncertainty, and agreement, in that order. No statement required voting, and participants were urged not to vote if they thought a statement was outside their purview. "Uncertainty" in one's vote indicates "discomfort regarding the accuracy of the recommendation." Following each voting session, the scientific committee evaluated the comments that were added to all of the statements. Throughout each vote round, members were encouraged to voice their opinions, especially when there was a disagreement. Because of this, the panel was able to determine when the statement was misunderstood and to remove the vote on it.

Definition of consensus

Developing the clinical care standards framework

In assisting in the standardised identification of guideline components, a structured template was created based on the responses to the structured key questions and the literature research. The information extraction and provision formats for each guideline component have been specified.

Ethical aspects

This study was performed in accordance with the Helsinki Declaration. This was a multistep process which followed the "Clinical, Evidence-based, Guidelines" (CEG) initiative protocol (ethical approval code: 34842/8/21, ethical board Tanta University).

Results

Literature research and evidence selection:

After removing the duplicates, 607 of the 788 records that the search produced were examined (171). We obtained the whole texts of 145 possible documents after filtering. The literature review contained thirty-three documents. The findings were compiled, summarised, and developed into recommendations for the treatment of GCA patients. After that, they were debated, changed, and submitted to a vote.

Expert panel characteristics

The Delphi form was sent to expert panel ( n  = 14), of whom 13 (92.8%) completed the two rounds. The participants were 2 from the USA, 6 from Europe, and 5 from Africa (Egypt). 11 of the experts' panel were rheumatologists in addition to 2 patients.

Delphi round 1

The 23 items in this round, which addressed the major clinical questions, included: all of the clinical questions that were addressed in the rounds that followed. Every domain and question was accepted (all respondents strongly agreed or agreed), and no questions were removed from the list.

Delphi round 2

Based on the literature search, a list of 23 sectioned recommendations were generated using the input from round 1. The response rate for round 2 was 92.8% from the experts' panel (13/14). Wording modifications were suggested for 14 statements. The statements were modified and amended. For all statements the consensus was reached (as ≥ 80% of respondents strongly agreed or agreed). There were no significant differences between the grading of the patients and healthcare professionals. The main differences were regarding the priority of ultrasound scanning (favoured by the European and Egyptian teams) Vs temporal artery biopsy (favoured by the American team).

Statements and grade of recommendations (GOR) for the management of GCA

These are a list of the recommendations made in order to address the main clinical questions. Under each part, there is information on the mean degree of agreement among the expert panel members, the percentage of agreement, the level of evidence (LOE), and the grades of recommendations. A suggestion of an algorithm for the stratification of patients with GCA and the recommended management approach is demonstrated in Table 1. Table 2 shows the Treat to Target proposal for GCA.

Table 1 Suggested algorithm for the GCA patients' stratification

Table 2 Treat to target of giant cell arteritis

Overarching principles

Diagnosis: Q. what is the recommended approach to GCA diagnosis?

Level of evidence: 4C, level of agreement: Mean ± SD: 8.15 ± 1.2, percentage of agreement: 92.3%, Level of agreement: High.

Clinical symptoms (Red Flags)

Key symptoms

New-onset of persistent localised headache, often in the temporal area.

Constitutional symptoms (e.g. weight loss > 2 kg, low-grade fever, fatigue, night sweats).

Jaw pain and/or tongue claudication.

Acute visual symptoms such as amaurosis fugax, acute visual loss, diplopia.

Symptoms of polymyalgia rheumatica.

Limb claudication.

Signs: clinical examination

Cranial disease

Extra-cranial disease

Non-specific manifestations: without evidence of infection or neoplastic disease:

Older age, history of transient visual loss and jaw claudication were independent predictors of visual loss, while fever and rheumatic symptoms were protective [ 21].

Hypertension and ischaemic heart disease were also identified as potential risk factors for cranial ischaemic complications [ 22, 23].

Risk factors for aortic aneurysms:

Diagnostic work-up

Fast Track GCA pathway: Q. is there a role for GCA fast track approach?

Level of evidence: 5D, level of agreement: Mean±SD: 8.07±2.2, percentage of agreement: 92.3%, Level of agreement: High

Immediate treatment of GCA implies that the diagnosis is also confirmed rapidly.

The fast track GCA pathway offers timely evaluation of cranial GCA and has become the gold standard method of assessment and treatment of patients referred with suspected GCA.

Fast track US clinics for GCA offer the suspected GCA patients prompt chance for clinical and sonographic assessment, facilitating immediate initiation of high-dose glucocorticoids (GC), consequently reducing the symptom-to-therapy lag. Therefore, it aims to lessen numbers of negative outcomes as sight loss and subsequently loss of independence and mobility which is associated with increase health care use and cost.

The role of imaging: Q. what is the role of imaging in the diagnosis of GCA?

Level of evidence: 3C, level of agreement: Mean±SD: 8.0±1.2, percentage of agreement: 84.6%, Level of agreement: High

Imaging in clinically suspected cases

Level of evidence: 3C, level of agreement: Mean±SD: 8.15±0.89, percentage of agreement: 92.3%, Level of agreement: High

Imaging modalities

Ultrasound: Q. Should a suspected diagnosis of GCA be confirmed by US imaging?

Level of evidence: 2B, level of agreement: Mean±SD: 7.69±1.6, percentage of agreement: 76.9%, Level of agreement: high

Other imaging modalities: Q. Is there a room for other imaging modalities in the diagnosis of GCA?

Level of evidence: 4C, level of agreement Mean±SD: 7.85±1.63, percentage of agreement: 84.6%, Level of agreement: High

Temporal Artery Biopsy (TAB): Q. Shall Temporal Artery biopsy be considered in every patient with suspected GCA?

Level of evidence: 5, level of agreement Mean±SD: 7.69±1.93, percentage of agreement: 76.9%, Level of agreement: high

Patients' stratification: Q. Can the GCA patients be stratified according to their disease status or the presence of comorbidities?

Level of evidence: 4C, level of agreement: Mean±SD: 8.23±1.1, percentage of agreement: 84.6%, Level of agreement: High

There is not "one size fit all" glucocorticoids regimen for all newly diagnosed GCA patients, with empirical disease-modifying agents added only to patients with an increased risk of steroid-related adverse effects or when a flare occurs.

GCA varies in extent and severity, therefore management should be guided by disease stratification and target the prevention of poor treatment outcomes.

Patients' stratification facilitates the achievement of treatment targets, tailoring the medical management approach and prediction of the disease outcomes.

Patient can be stratified according to: Disease activity, disease severity, chances of accrual damage and the presence of comorbidities (Table 1).

Treat to Target: Q. Can GCA be treated to a target? What are the treatment targets?

Level of evidence: 5D, level of agreement: Mean ± SD: 8.15 ± 1.2, percentage of agreement: 84.6%, Level of agreement: High

Treatment

Can the treatment of GCA be splitted into phases?

Level of evidence: 5D, level of agreement: Mean+SD: 8.31±1.1, percentage of agreement: 84.6%, Level of agreement: High

Induction phase

Maintenance phase

A regimen for glucocorticoids tapering should start once the disease is controlled.

The glucocorticoids tapering regimen must weigh the risk of relapse against the risk of glucocorticoids-related adverse events.

There are several plans for tapering of the glucocorticoids dose. General plan is cut the steroids dose down to a target dose of 15-20 mg/day within 2-3 months and after one year to ≤ 5 mg/day (Table 1).

There is no data available regarding the optimal length of glucocorticoids therapy, it usually takes about two years or more before GCs can be stopped.

In patients receiving GC-sparing therapy, faster glucocorticoids tapering and earlier withdrawal of GCs should be considered on an individual basis.

GCA "patients at risk": Q. Is it important to identify GCA patients who are at risk?

Level of evidence: 5D, level of agreement: Mean±SD: 8.31±0.95, percentage of agreement: 92.3%, Level of agreement: High

Patients at high risk of glucocorticoid toxicity or who have relapsing or refractory disease. These are the:

Patients with a persisting high burden of inflammatory disease, multiple relapses with an inability to wean glucocorticoids, non-response to methotrexate, co‑morbidities or the presence of other factors that increase glucocorticoid-related adverse events, as well as resistance to glucocorticoid therapy.

"Patients at risk" of disease complications and/or treatment-related adverse events.

Management of Relapse: Q. How to manage relapses in GCA?

Level of evidence: 5D, level of agreement: Mean±SD: 8.38±0.77, percentage of agreement: 100%, Level of agreement: High

Relapse rates in the range of 34%-75% may occur in GCA patients treated with glucocorticoids therapy [ 35].

Relapse risk is high particularly after early taper and/or reduction of the glucocorticoids dose below 5 mg/day.

Relapse can be either:

Major Relapse: Recurrence of active disease with either of the following:

Clinical features of ischaemia (including jaw claudication, visual symptoms, visual loss attributable to GCA, scalp necrosis, stroke, limb claudication).

Evidence of active aortic inflammation resulting in progressive aortic or large vessel dilatation, stenosis or dissection.

Minor Relapse:

Recurrence of active disease, not fulfilling the criteria for a major relapse

-Initial treatment is reinstitution or a dose-increase of glucocorticoids which may differ according to whether it is minor (increase GC to last effective dose) or major (increase GC to 40-60mg/day) relapse.

Relapses should warrant the assessment of glucocorticoids benefit: risk ratio as high cumulative GC exposure may lead to an increased risk of glucocorticoids-related adverse events.

Adjunctive therapy, combined with increasing the glucocorticoids dose, should be considered in selected GCA patients (refractory* or relapsing disease, the presence comorbidities or an increased risk of glucocorticoids associated adverse effects or complications). Adding tocilizumab and increasing the dose of glucocorticoids is preferable over methotrexate combined with increasing the glucocorticoids dose for GCA patients who experience disease relapse with cranial or new extra-cranial symptoms while receiving glucocorticoids. Methotrexate can be considered for patients who are unable to tolerate or have limited access to tocilizumab.

Patients who are treated with methotrexate adjunctive therapy: 'treatment failure', is defined as having two or more relapses or having a relapse that was not controlled by an increment of prednisone dose [ 36, 37, 38, 39].

Relapses with symptoms of polymyalgia rheumatica may be controlled by increasing the dose of glucocorticoids alone. If no response, PMR can be considered as a relapse of the GCA.

Refractory GCA: Inability to induce remission (with evidence of reactivation of disease) despite the use of standard care therapy

Glucocorticoids tapering: Q. How to plan for glucocorticoids tapering?

Table 3 shows a suggested regimen for tapering glucocorticoids.

Table 3 Suggested glucocorticoids tapering regimen

Treatment discontinuation: Q. How to plan for treatment discontinuation?

Level of evidence: 5D, level of agreement: Mean+SD: 7.46±1.5, percentage of agreement: 76.9%, Level of agreement: high

Drug-free remission: what is meant by remission?

*Remission

Absence of all clinical signs and symptoms attributable to active LVV and normalisation of ESR and CRP; in addition, for patients with extracranial disease there should be no evidence of progressive vessel narrowing or dilatation (frequency of repeat imaging to be decided on an individual basis)

*Sustained Remission

1. 1.
Remission for at least 6 months.

2. 2.
Achievement of the individual target GC dose.

*Glucocorticoids free remission

1. 1.
Sustained remission

2. 2.
Discontinued GC therapy (but could still be receiving other immunosuppressive therapy)

3. 3.
Drug free remission may be achieved in some patients.

4. 4.
Drug free remission was reported in a cohort of patients treated with Tocilizumab [ 22].

Adjunctive therapy: Q. what is the impact of oral glucocorticoids with non-glucocorticoid immunosuppressive therapy versus oral glucocorticoids alone?

Level of evidence: 4C, level of agreement: Mean±SD: 8.07±1.3, percentage of agreement: 76.9%, Level of agreement: high

Management of patients with comorbidities: Q. What is the impact of identifying the individual patient's comorbidity(ies) at baseline?

Level of evidence: 5D, level of agreement: Mean+SD: 8.15±1.1, percentage of agreement: 84.6%, Level of agreement: High

Diabetes mellitus

Patients with Diabetes Mellitus: use of oral glucocorticoids with methotrexate or tocilizumab can be considered as first line therapy.

Osteoporosis

Consider starting osteoprotective therapy, if the patient has not already started treatment.

Cardiovascular (CVS)

48 who are managing GCA patients should be aware of the increased risk of CVD events, attributable to both disease pathophysiology and glucocorticoid treatment.

GCA patients, should be monitored not only to maintain clinical remission but also to monitor and attempt to prevent CVD events, including strokes, thoracic aortic aneurysms and dissections, ischemic heart disease, and peripheral vascular disease.

Consider imaging to evaluate for active disease and/or development of thoracic aortic aneurysm.

Consider statin and aspirin therapy whenever indicated

If patient is unable to tolerate steroids, consider switching to tocilizumab weekly SC injection.

Infection

The association between high-dose glucocorticoid therapy and opportunistic infections, particularly pneumocystis jirovecii pneumonia (PJP), is now well established in both non-rheumatological and rheumatological diseases. Trimethoprim/sulfamethoxazole (TMP-SMX) has been proved to be effective as a primary prophylaxis for PJP in patients suffering from rheumatological diseases treated with high dose (⩾30 mg/day prednisone) glucocorticoid therapy, with an overall favourable safety profile.

Improving the Benefit: Risk ratio of glucocorticoids: Q. How important is it to optimize the benefit: risk ratio of glucocorticoids?

Level of evidence: 5, level of agreement: Mean±SD: 8.15±0.9, percentage of agreement: 92.3%, Level of agreement: High

Optimizing the benefit: risk ratio of glucocorticoids to minimize adverse events while achieving sustained remission is a vital challenge to be considered whilst treating GCA patients.

Implementation of current treatment recommendations for the optimal use of glucocorticoids could reduce the burden of this treatment

The risk of glucocorticoid-related harm for the majority of patients taking glucocorticoids for a prolonged period (that is, for 3-6 months or more) is:

Low if doses of ≤ 5 mg per day prednisone equivalent are prescribed,

High if doses > 10 mg per day are used.

At doses between 5 and 10 mg per day, patient-specific risk factors determine the probability of harm.

Monitoring: Q. How to monitor GCA patients in standard practice?

Level of evidence: 5D, level of agreement: Mean+SD: 8.23±1.1, percentage of agreement: 84.6%, Level of agreement: High

Baseline assessment

Assessment of medical status

Determination of pre-existing comorbidities such as hypertension, diabetes mellitus, cataract, cardiovascular disease, peptic ulcer disease, osteoporosis and glaucoma is important as the treatment can initiate or worsen disease status.

Assessment of current medications

Checking the list of current medications the patient is taking. Co-medication with non-steroidal anti-inflammatory drugs (NSAIDs) and anti-coagulants is important both for immediate and long-term care in GCA.

Baseline investigations

Consider performing a screen for infection including dipstick urinalysis and chest X-ray (CXR); and a search for mimicking diseases with protein electrophoresis, thyroid function tests, and anti-cytoplasmic neutrophil antibodies. Baseline CXR, echocardiogram or large-vessel imaging are advocated by some centres to assess for large-vessel complications at baseline, in higher risk groups. Occasionally a contrast-enhanced MRI head and orbits may be indicated examining the anterior visual pathways where the cause of an optic neuropathy is not clear.

Frequency of clinical/laboratory monitoring

Imaging monitoring

Level of evidence: 5D, level of agreement: Mean+SD: 8.0±0.8, percentage of agreement: 100%, Level of agreement: High

Surgical management of GCA: Q. what is the role of surgery in the management of GCA?

Level of evidence: 5D, level of agreement: Mean ± SD: 8.53 ± 0.8, percentage of agreement: 92.3%, Level of agreement: High

For any patient requiring surgical vascular intervention for GCA, the type and timing of intervention should be a collaborative decision between the vascular surgeon and rheumatologist.

Patients with severe GCA and worsening signs of limb/organ ischemia who are receiving immunosuppressive therapy, it is advisable to escalate immunosuppressive therapy over surgical intervention.

For GCA patients undergoing vascular surgical intervention (for a GCA associated complication e.g., aneurysm or stenosis), high-dose glucocorticoids should be administered during the periprocedural period, if the patient has active disease.

Elective endovascular interventions or reconstructive surgery should be performed during stable remission. However, arterial vessel dissection or critical vascular ischaemia requires urgent referral to a vascular team.

Disease activity: how to define the disease activity status of GCA?

Level of evidence: 5D, level of agreement: Mean ± SD: 8.07 ± 1.1, percentage of agreement: 84.6%, Level of agreement: High

Definitions for GCA disease activity states:

Defining the specific disease activity states is important for framing this guideline. These are listed in Table 4.

Table 4 Important definitions for GCA diseasea

PROMs: Q. What are the patient reported outcomes important for the assessment and monitoring of GCA patients?

Outcomes: Q. what are the outcome measures for assessment of treatment outcomes in GCA?

Discussion

GCA remains a disease that represents a challenge to both healthcare professionals as well as patients for its ambiguous presentation, approach to diagnosis, or its remarkable risk of flares and chronic damage in the long term. Over the past decade several RCTs and a good number of high-quality diagnostic studies have changed the view of GCA as a short-term steroid responsive illness [ 40, 41, 42, 43]. Such expansion in methodology, understanding of the disease pathogenesis as well as extent and severity of its outcomes highlighted the need for up-to-date recommendations for GCA management. This work was carried out to provide evidence-based recommendations for the evaluation and management of GCA.

The real challenge of giant cell arteritis is not to control the acute inflammatory process, but to ensure long-term, safe prevention of disease relapses and incipient damage. Both the EULAR recommendations [ 35] and the 2021 ACR recommendations for large vessel vasculitis [ 42] suggest treating all newly diagnosed GCA patients in the same strategy, i.e. with the same glucocorticoid regimen, and the option of empirically adding disease-modifying agents to patients with an increased risk of steroid-related adverse effects or when a flare occurs. Such management approach which is based simply on one-size-fits-all strategy leads to overreliance on glucocorticoids and high chance of development of glucocorticoid-associated complications. This recommendation suggests patients' stratification as a new approach to identify and manage the patients tailored to their potential risks. Several patients may have pre-existing, or develop, comorbidities during the course of glucocorticoids therapy, which warrant individualized approach of management. Furthermore, the high likelihood of symptomatic relapse in GCA (34-62%) make these patients prone to longer periods and higher doses of glucocorticoid therapy [ 37]. Furthermore, adding adjunctive therapy such as tocilizumab or methotrexate was reported to achieve superior remission rates in GCA patients and enables faster withdrawal of glucocorticoids therapy [ 42, 43, 44, 45]. Therefore, stratification of GCA would be an ideal strategy particularly for this cohort of patients. A recent article [ 46] highlighted the need to implement disease stratification in standard practice and suggested using clinical, laboratory, histology, and imaging as parameters for stratification. In medicine, stratification is not a new policy. In fact, it is a common approach which has been implement in oncology, haematology [ 45, 46] as well as rheumatology (e.g. SLE and ANCA associated vasculitis) [ 46, 47]. The stratification system is supported by high-quality evidence as a facilitator for the prediction of disease outcome and the tailoring of therapy accordingly [ 47, 48, 49].

This guideline endorsed the Treat to Target concept of GCA. In agreement with the recently published Treat-to-target recommendations in giant cell arteritis and polymyalgia rheumatica [ 52], the level of agreement was high among the experts who shared in this study. However, in contrast to Dejaco et al. study [ 50] which considered the GCA treatment target of GCA to be remission, defined as the absence of clinical symptoms and systemic inflammation, this guideline stratified the target according to the disease stage whether early or established. The definition of the Target has also expanded beyond remission state to include also, in addition to clinical remission, avoidance of visual loss or other vascular damage/tissue ischemia, rapid initiation of treatment and achievement of remission, maintenance of remission with the minimal effective dose of therapy, maintain GCA disease related tissue and vascular integrity (whenever appropriate), minimization of glucocorticoid use and relapse prevention, along with avoidance of damage accrual. Patient reported outcomes and Disease activity score (study submitted for publication) have also been added as targets of treatment. T2T recommendations have been endorsed in rheumatology [ 51, 52, 53], and frequently serve as an outcome in clinical trials and observational studies of GCA [ 52].

Limitations of the study

Despite the low level of evidence in the literature, the level of agreement for each of the statements included in this recommendation was consistently high among the expert panel members.

In conclusion, we are embarking now on the era of targeted GCA management approach with several avenues to stratify, diagnose and manage this cohort of patients. Close partnership with other teams that care for those with GCA including rheumatology, medicine, neurology and primary care, will facilitate early diagnosis and improve long-term management. Therefore, to improve the patients' quality of care and effectively manage their disease, we propose that healthcare professionals dealing with GCA will implement these recommendations into their standard clinical practice. Fast-track GCA pathway, patient stratification, US assessment of the temporal artery, patient reported outcomes as well as quantification of the GCA-response to therapy represent the main pillars of GCA management in the coming decade.

Availability of data and materials

The data will be available upon reasonable request.

Abbreviations

ACR:

American College of Rheumatology

CVS:

Cardiovascular

CXR:

Chest X-ray

GCA:

Giant cell arteritis

GC:

Glucocorticoids

GOR:

Grade of recommendations

LV-GCA:

Large vessel-GCA

MRA:

MR angiography

NSAIDs:

Non-steroidal anti-inflammatory drugs

CEBM:

Oxford Centre for Evidence-based Medicine

PJP:

Pneumocystis jirovecii pneumonia

PMR:

Polymyalgia rheumatica

RCTs:

Randomized controlled trials

TAB:

Temporal Artery Biopsy

CEG:

The Clinical, Evidence-based, Guidelines"

EULAR:

The European Alliance of Associations for Rheumatology

LOE:

The level of evidence

TCZ:

Tocilizumab

T2T:

Treat to Target

TMP-SMX:

Trimethoprim/sulfamethoxazole

US:

Ultrasonography

References

1. Prior JA, Ranjbar H, Belcher J et al (2017) Diagnostic delay for giant cell arteritis - a systematic review and meta-analysis. BMC Med 15:120. https://doi.org/10.1186/s12916-017-0871-z

2. Patil P, Williams M, Maw WW, Achilleos K, Elsideeg S, Dejaco C, Borg F, Gupta S, Dasgupta B. Fast track pathway reduces sight loss in giant cell arteritis: results of a longitudinal observational cohort study. Clin Exp Rheumatol. 2015;33(2 Suppl 89):S-103-6. Epub 2015 May.

3. Serling-Boyd N, Stone JH (2020) Recent advances in the diagnosis and management of giant cell arteritis. Curr Opin Rheumatol 32(3):201-207

Article CAS PubMed PubMed Central Google Scholar

4. OCEBM Levels of Evidence Working Group (2011) The Oxford levels of evidence 2. Oxford Centre for Evidence-Based Medicine, Oxford, UK

Google Scholar

5. Niederberger M, Spranger J (2020) Delphi technique in health sciences: a map. Front Public Health 8:457. https://doi.org/10.3389/fpubh.2020.00457

6. Von der Gracht H (2012) Consensus measurement in Delphi studies: review and implications for future quality assurance. Technol Forecast Soc 79(8):1525-1536

Article Google Scholar

7. Niederberger M, Deckert S (2022) Das Delphi-Verfahren: Methodik, Varianten und Anwendungsbeispiele [The Delphi technique: Methodology, variants and usage examples]. Z Evid Fortbild Qual Gesundhwes 174:11-19. https://doi.org/10.1016/j.zefq.2022.08.007. German

8. Jaam M, Awaisu A, El-Awaisi A, Stewart D, El Hajj MS (2022) Use of the Delphi technique in pharmacy practice research. Res Social Adm Pharm 18(1):2237-2248. https://doi.org/10.1016/j.sapharm.2021.06.028

9. Muratore F, Kermani TA, Crowson CS et al (2018) Large-vessel dilatation in giant cell arteritis: a different subset of disease? Arthritis Care Res 70:1406-1411

Article Google Scholar

10. El Miedany Y, Elgaafary M, Toth M, Azim AA, Palmer D, Dolbear G, Abu-Zaid MH, Affam D, Hassan W, Elnady B, Tabra SA, Saber S. Development of outcome measures for giant cell arteritis for use in clinical trials and standard practice. ClinRheumatol. 2023. https://doi.org/10.1007/s10067-023-06704-7.

11. Stone JH, Han J, Aringer M et al (2021) Long-term effect of tocilizumab in patients with giant cell arteritis: open-label extension phase of the giant cell arteritis actemra (giacta) trial. Lancet Rheumatol 3:328-336

Article Google Scholar

12. Stone JH, Tuckwell K, Dimonaco S et al (2019) Glucocorticoid dosages and acute-phase reactant levels at giant cell arteritis flare in a randomized trial of tocilizumab. Arthritis Rheumatol 71:1329-1338

Article CAS PubMed PubMed Central Google Scholar

13. Tomelleri A, van der Geest KS, Sebastian A, van Sleen Y, Schmidt W, Dejaco C et al (2021) Disease stratification in giant cell arteritis to reduce relapses and prevent long-term vascular damage. Lancet (Rheumatology) 3:886-895

Article Google Scholar

14. Watson EK, Rose PW, Neal RD et al (2012) Personalised cancer follow-up: risk stratification, needs assessment or both? Br J Cancer 106:1-5

Article CAS PubMed PubMed Central Google Scholar

15. Dejaco C, Kerschbaumer A, Aletaha D, et al. Treat-to-target recommendations in giant cell arteritis and polymyalgia rheumatic. Annals of the Rheumatic Diseases Published Online First: 24 February 2023. https://doi.org/10.1136/ard-2022-223429.

Download references

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Author information

Authors and Affiliations

1. Canterbury Christ Church University, Canterbury, England

Y El Miedany & G Dolbear

2. Community and Public Health, Ain Shams University, Cairo, Egypt

M El Gaafary

3. Darent Valley Hospital, Kent, England

M Toth

4. Cairo University, Giza, Egypt

A Abdel Azim

5. North Middlesex University Hospital, London, UK

D Palmer

6. Darent Valley Hospital, Dartford, UK

D Affam

7. Rheumatology and Rehabilitation, Benha University, Benha, Egypt

W Hassan

8. Rheumatology and Rehabilitation, Faculty of Medicine, Tanta University, Tanta, Egypt

SA Tabra & MH Abu-zaid

9. Rheumatology and Rehabilitation, Ain Shams University, Cairo, Egypt

S Saber

10. Rheumatology and Rehabilitation Department, Tanta Faculty of Medicine, El-Geish Street, Tanta, 31527, Gharbia, Egypt

MH Abu-zaid

Contributions

Conceptualization and design, Yasser El Miedany, Mohammed Hassan Abu-Zaid; Acquisition of data, Yasser El Miedany, Mohammed Hassan Abu-Zaid; Formal analysis, Maha El Gaafary; Investigation, Samar Tabra and waleed hassan; Methodology, all authors; Writing - original draft, Yasser El Miedany, Mohammed Hassan Abu-Zaid; Final approval of the version to be submitted, all authors.

Corresponding author

Correspondence to MH Abu-zaid.

Ethics declarations

Ethics approval and consent to participate

This study was performed in accordance with the Helsinki Declaration. This was a multistep process which followed the "Clinical, Evidence-based, Guidelines" (CEG) initiative protocol (ethical approval code: 34842/8/21, ethical board Tanta University). Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that the corresponding author "Mohammed Hassan Abu-Zaid" is associate editor in the Egyptian Rheumatology and Rehabilitation, Yasser El Miedany, & Waleed Haasn are from editorial board of the journal. There is no financial support and sponsorship.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Reprints and permissions

About this article

Cite this article

El Miedany, Y., El Gaafary, M., Toth, M. et al. Step forward towards treat-to-target management of giant cell arteritis: patients stratification aiming to targeted remission - updated guidelines. Egypt Rheumatol Rehabil 51, 5 (2024). https://doi.org/10.1186/s43166-024-00237-w
Download citation

Received:

Accepted:

Published:

DOI: https://doi.org/10.1186/s43166-024-00237-w

Share this article

Anyone you share the following link with will be able to read this content:

Get shareable link

Provided by the Springer Nature SharedIt content-sharing initiative

Keywords

# data[].attributes.attachment_link.title
Step forward towards treat-to-target management of giant cell arteritis: patients stratification aiming to targeted remission - updated guidelines - Egyptian Rheumatology and Rehabilitation

# data[].attributes.attachment_link.description
Background The aim of this work is to develop guidelines for health care professionals in the giant cell arteritis diagnosis and management, based on patients' stratification and targeted outcome measures. Results Fourteen expert panel had completed the two rounds surveys. After the end of round two, twenty three recommendations were released distributed on 8 domains.

# data[].attributes.headline
Challenges and options for management of stones in anomalous kidneys: a review of current literature

# data[].attributes.subject
Challenges and options for management of stones in anomalous kidneys: a review of current literature

# data[].attributes.headline
The necessary and neglected work of the soul in healthcare

# data[].attributes.subject
The necessary and neglected work of the soul in healthcare

# data[].attributes.body
Login using OpenAthens

# data[].attributes.headline
Surgical trainee experiences from 2013 to 2023 within the United Kingdom as reported by the General Medical Council National Training Survey

# data[].attributes.subject
Surgical trainee experiences from 2013 to 2023 within the United Kingdom as reported by the General Medical Council National Training Survey

# data[].attributes.attachment_link.description
About ScienceDirect
Shopping cart
Contact and
supportTerms and
conditionsPrivacy policy

# data[].attributes.headline
Worldwide trends of practice and intervention in paediatric endourology: comparison of European versus Non-European responses

# data[].attributes.subject
Worldwide trends of practice and intervention in paediatric endourology: comparison of European versus Non-European responses

# data[].attributes.attachment_link.title
Worldwide trends of practice and intervention in Paediatric Endourology: Comparison of European versus Non-European responses

# data[].attributes.headline
Conference Abstract - Wegener’s vagueness: midfacial granulomatosis with polyangiitis, or cocaine usage?

# data[].attributes.subject
Conference Abstract - Wegener’s vagueness: midfacial granulomatosis with polyangiitis, or cocaine usage?

# data[].attributes.attachment_link.provider_name
Journal of Neurology, Neurosurgery & Psychiatry

# data[].attributes.attachment_link.readable_text
A 45-year-old woman presented with several months of right-sided headache, associated with vocal hoarseness, fever, night sweats and weight loss. Severe right-sided periorbital pain came in episodes lasting several hours, associated with ipsilateral partial ptosis, facial swelling and hyperaesthesia. Indomethacin and greater occipital nerve block were ineffectual; however, a transient symptomatic improvement had coincided with previous steroid treatment.

She had a background of cocaine use. Longstanding sinus complaints were investigated with nasen- doscopy, revealing nasal septal crusting and a hole in the soft palate. Fluctuating lymphadenopathy on previous imaging was investigated with blood tests, showing persistently raised ESR and ANCA positivity. Normal eosinophil counts.

Serial MRI head scans showed evidence of worsening inflammatory, sclerotic and bony erosive changes to the midfacial skull base. The nasal septum and turbinates were obliterated, and maxillary/ethmoid/sphenoid sinuses were persistently effused. Granulomatosis with polyangiitis was diagnosed, and treatment with high-dose steroids and mycophenolate mofetil was commenced. Headache symptoms convinc- ingly improved.

We present a case of headache with atraumatic midline skull base destruction, in a patient satisfying diagnostic criteria for granulomatosis with polyangiitis [1-2]. However, chronic cocaine use can have over- lapping clinical, immunological and radiological features [3-6]. Recent literature is reviewed to evaluate this diagnostic challenge [8-10].

# data[].attributes.attachment_link.title
Wegener's vagueness: midfacial granulomatosis with polyangiitis, or cocaine usage?

# data[].attributes.attachment_link.description
A 45-year-old woman presented with several months of right-sided headache, associated with vocal hoarseness, fever, night sweats and weight loss. Severe right-sided periorbital pain came in episodes lasting several hours, associated with ipsilateral partial ptosis, facial swelling and hyperaesthesia. Indomethacin and greater occipital nerve block were ineffectual; however, a transient symptomatic improvement had coincided with previous steroid treatment.

# data[].attributes.headline
Conference Abstract - A deep dive into a neurological rarity

# data[].attributes.subject
Conference Abstract - A deep dive into a neurological rarity

# data[].attributes.attachment_link.provider_name
Journal of Neurology, Neurosurgery & Psychiatry

# data[].attributes.attachment_link.readable_text
Association of British Neurologists: Annual Meeting Abstracts 2023

Abstract

A 52-year-old fit and well man presented with sudden band like sensation around his chest, eight hours after scuba diving. On movement, he developed abrupt left leg weakness the next day evolving over a few hours, with nadir bilateral leg power 0/5 and urinary retention. He received five hours of hyperbaric oxygen treatment (HBOT) and intravenous immunoglobulin for possible Guillain-Barre syndrome, with no improvement. Cerebrospinal fluid protein was 0.7g/L. Ten days later, on repatriation to the UK, first exam- ination revealed spastic paraparesis with power 2/5, pinprick sensory level at T4 and preserved dorsal column function. Brain imaging was normal but in the spinal cord there was an anterior non-enhancing lesion at T3-4, felt to be ischaemic. He received further prolonged HBOT and methylprednisolone. He suffered a pulmonary embolism, probably provoked by hospital acquired pneumonia, although bloods revealed one positive lupus anticoagulant. Repeat testing returned equivocal with negative anticardiolipin antibodies. Cerebrovascular and cardiovascular abnormalities were not identified on CT-angiogram and bubble echocardiogram. After HBOT there was significant improvement and at 6 months, he can walk with a stick. Neurological complications of scuba diving are rare. This case should alert neurologists to this possible phenomenon and to consider delayed hyperbaric oxygen treatment.

Statistics from Altmetric.com

Request Permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center's RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

Read the full text or download the PDF:

# data[].attributes.attachment_link.description
A 52-year-old fit and well man presented with sudden band like sensation around his chest, eight hours after scuba diving. On movement, he developed abrupt left leg weakness the next day evolving over a few hours, with nadir bilateral leg power 0/5 and urinary retention.

# data[].attributes.headline
Venetoclax-based low intensity therapy in molecular failure of NPM1 mutated AML

# data[].attributes.subject
Venetoclax-based low intensity therapy in molecular failure of NPM1 mutated AML

# data[].attributes.attachment_link.title
Venetoclax-based low intensity therapy in molecular failure of NPM1 mutated AML

# data[].attributes.attachment_link.description
Key Points. 84% of patients treated with venetoclax combinations for NPM1mut molecular failure achieved a molecular response and 71% became MRD negativeVenetocl

# data[].attributes.headline
‘Distal-to-proximal’ surgical release of the proximal interphalangeal joint in Dupuytren’s disease

# data[].attributes.subject
‘Distal-to-proximal’ surgical release of the proximal interphalangeal joint in Dupuytren’s disease

# data[].attributes.headline
Lack of regional pathways impact on surgical delay: Analysis of the Orthopaedic Trauma Hospital Outcomes-Patient Operative Delays (ORTHOPOD) study

# data[].attributes.subject
Lack of regional pathways impact on surgical delay: Analysis of the Orthopaedic Trauma Hospital Outcomes-Patient Operative Delays (ORTHOPOD) study

# data[].attributes.headline
Conference Abstract - OGBN P44 Does laparoscopic fundoplication have a role in non-erosive reflux disease? 

# data[].attributes.subject
Conference Abstract - OGBN P44 Does laparoscopic fundoplication have a role in non-erosive reflux disease? 

# data[].attributes.attachment_link.title
OGBN P44 Does laparoscopic fundoplication have a role in non-erosive reflux disease?

# data[].attributes.attachment_link.description
AbstractBackground. Non-erosive reflux disease (NERD) is a sub-group of gastro-oesophageal reflux disease (GORD) characterised by reflux related symptoms withou

# data[].attributes.headline
Characteristics and outcomes of neonates hospitalised with SARS-CoV-2 infection in the UK by variant: a prospective national cohort study

# data[].attributes.subject
Characteristics and outcomes of neonates hospitalised with SARS-CoV-2 infection in the UK by variant: a prospective national cohort study

# data[].attributes.attachment_link.readable_text
Data availability statement

Data are available on reasonable request. The datasets generated during and analysed during the current study are available from the corresponding author on reasonable request.

https://creativecommons.org/licenses/by/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.

Introduction

Children are less severely affected by SARS-CoV-2 than adults, and this pattern has been seen across viral variants. 1 In the neonatal period (first 28 days), neonates can be infected by SARS-CoV-2 or indirectly affected because of maternal infection, for example, through spontaneous or iatrogenic preterm birth. We have previously reported that neonates were more likely than older children to require respiratory support following SARS-CoV-2 infection when the wildtype variant was dominant, 2 but it is not clear if this pattern persisted in later periods. The alpha and delta variants of SARS-CoV-2 resulted in more severe maternal SARS-CoV-2 infection, 3 but there are few studies describing the impact of SARS-CoV-2 viral variants in neonates. 4

Using population-level active surveillance data linked to maternal, neonatal and paediatric intensive care and perinatal mortality data, we aimed to describe the epidemiology, clinical course and short-term outcomes of neonates with confirmed SARS-CoV-2 infection cared for in hospitals in the UK over the first 2 years of the pandemic, stratified by the dominant SARS-CoV-2 variant in circulation at the time of infection.

Methods

This was a national prospective cohort study using the British Paediatric Surveillance Unit (BPSU). 5 From 1 April 2020, senior paediatricians (~4000) in all 155 hospital trusts and health boards in the UK with their associated 190 neonatal units (NNUs) received a weekly (until March 2021) then monthly electronic BPSU reporting card asking them to report any baby who had laboratory-confirmed SARS-CoV-2 infection in the first 28 days after birth and received inpatient care on a postnatal ward, NNU, paediatric inpatient ward or paediatric intensive care unit (PICU). Well neonates born in the UK remained with their mother on postnatal wards until mother and baby were fit for discharge; neonates with asymptomatic SARS-CoV-2 on postnatal wards and asymptomatic cases detected through screening were not reported. Monthly reporting cards sought confirmation that all eligible neonates in the previous month had been reported, and that any reports of no infected neonates were accurate (active negative surveillance). To maximise case ascertainment, we linked to national testing data from Public Health England and Health Protection Scotland between 1 March 2020 and 31 March 2021, as well as the Paediatric Intensive Care Audit Network, 6 United Kingdom Obstetric Surveillance System (UKOSS) data 7 and MBRRACE-UK national perinatal mortality surveillance data. 8 Additional details can be found in the online supplemental methods. Intensive care was defined using British Association of Perinatal Medicine categories of care 9 for neonatal admissions, or any admission to a PICU. Severe disease was defined as having received respiratory support. Very preterm birth was defined as birth at <32 gestational weeks.

Neonatal deaths were verified with the MBRRACE-UK national surveillance of perinatal deaths. 10 Neonatal deaths were attributed to SARS-CoV-2 if the treating paediatrician reported that SARS-CoV-2 infection contributed to the baby's death; we also recorded if the referring clinician reported that maternal SARS-CoV-2 infection led to spontaneous or iatrogenic preterm birth.

UK SARS-CoV-2 testing policy among pregnant women and neonates evolved during the study. Initially, only symptomatic women and neonates were tested. Routine screening of all obstetric admissions was recommended by the Royal College of Obstetricians and Gynaecologists on 29 May 2020 and neonatal testing recommended for symptomatic neonates of mothers with a SARS-CoV-2 infection; testing of asymptomatic neonates varied. Confirmation of neonatal SARS-CoV-2 infection required at least two positive samples, including one at least 72 hours after birth. 11 UK policy was that well neonates of SARS-CoV-2-infected mothers should be cared for alongside their mother in the postnatal ward and not routinely tested.

This analysis presents characteristics and outcomes for neonates reported as having confirmed SARS-CoV-2 infection in the first 28 days after birth, between 1 March 2020 and 1 April 2022, and for whom complete data had been received by 30 July 2022. To provide a complete description of the first two pandemic years, this report includes neonates with SARS-CoV-2 infection between 1 March 2020 and 30 April 2020 previously reported. 2

As individual-level SARS-CoV-2 variant data were not recorded in medical records, the outcomes were compared across four proxy groups according to the period in which the original wildtype, alpha variant, delta variant or omicron variant was the dominant circulating strain in the UK.

The original wildtype period included neonates diagnosed from 1 March to 30 November 2020, the alpha variant period from 1 December 2020 to 15 May 2021, the delta variant period from 16 May 2021 to 14 December 2021 and the omicron variant period from 15 December 2021 to 1 April 2022. We chose cut-off dates for the delta and omicron periods using data on variant sequencing from Public Health England to identify the week when these variants first contributed >50% of SARS-CoV-2 infections nationally. 12 Since genomic data on the variant were less widely available at the start of the pandemic, Public Health England modelled proxy data and reported that the alpha variant reflected the substantial majority of infections across all areas of England during December 2020; therefore, 1 December 2020 was used as an estimated cut-off date. 13

Results

Monthly BPSU card returns were received between 91.3% (3748/4070, April 2020) and 71.9% (3110/4298, February 2022) of UK paediatricians over the surveillance period. In total, 1192 potentially eligible neonates were reported to the BPSU system over the study period and 116 non-duplicate neonates were identified from other sources ( figure 1). Linkage with data held in the NNRD was achieved for 99% (132/134) of neonates reported through the BPSU system who received NNU care. Three hundred and forty-four neonates were diagnosed with SARS-CoV-2 infection in the first 28 days after birth and received inpatient care, predominantly in the wildtype-dominant and alpha-dominant periods, with numbers dropping in subsequent variant periods: 146 neonates were reported in the wildtype period, 123 in the alpha period, 57 in the delta and 18 in the omicron periods ( figure 2). Three hundred and twenty cases were in England, 16 cases in Scotland, 6 in Wales or Northern Ireland; country data were missing for 2 cases.

Median age at diagnosis was 9 days (IQR 3-17 days); 44.5% (153/344) of the neonates were diagnosed in the first 7 days after birth; of these, 66.7% (102/153) were born to a mother with confirmed SARS-CoV-2 infection within 7 days before or after giving birth. The age distribution at diagnosis was similar across different dominant circulating variant periods ( online supplemental figure 1). Respiratory signs were common along with poor feeding or vomiting and fever ( online supplemental figure 2); 15% of neonates were asymptomatic.

Neonates in hospital with neonatal SARS-CoV-2 infection were more commonly preterm and male when compared with all live births in England and Wales and this was consistent across all variant epochs, although sex differences were less marked in the alpha period ( table 1). The highest proportions of very preterm births were seen in the delta-predominant period. An over-representation of non-white ethnic groups among neonatal SARS-CoV-2 infections in the wildtype period was not seen with later variants ( table 1).

Most neonates in hospital with neonatal SARS-CoV-2 infection did not require high-level care; however, 44.7% required some form of respiratory support and 21.8% received intensive care ( table 2). Higher numbers and proportions of neonates in hospital with neonatal SARS-CoV-2 in the delta period required intensive care or invasive respiratory support, compared with other variant periods ( figure 3). Infection following suspected nosocomial transmission, excluding vertical transmission, affected 7.8% of neonates overall. Outcomes following neonatal SARS-CoV-2 infection were generally good; however, 11 deaths occurred in neonates who tested positive for SARS-CoV-2, 4 of which were attributed either directly or indirectly to neonatal SARS-CoV-2 infection (case fatality 4/344, 1.2% 95% CI 0.3% to 3.0%). Three of these four neonates had been born preterm due to maternal COVID-19. All four SARS-CoV-2-related neonatal deaths were in the delta period.

As expected in any neonatal population, degree of prematurity was strongly linked with receipt of respiratory support with all extremely preterm neonates infected with SARS-CoV-2 requiring ventilation; this highlights the challenges separating severe manifestations of SARS-CoV-2 infection from conditions related to preterm birth ( online supplemental table 1).

Discussion

Using population-level active surveillance data from March 2020 to April 2022 and spanning wildtype, alpha, delta and omicron variant-predominant periods during which there were approximately 1.4 million births recorded in the UK, 14-16 we confirm that the need for inpatient care for neonates with SARS-CoV-2 infection was rare and outcomes were generally good. Neonatal SARS-CoV-2 infection led to severe disease in a minority of neonates, with death related to neonatal SARS-CoV-2 infection occurring in 1.2% of hospitalised neonates. During the delta variant-predominant period, higher numbers of neonates had severe disease associated with SARS-CoV-2 infection, defined as requiring respiratory support, compared with other variant epochs. We believe this is the first study to present descriptive data from a national cohort on neonatal deaths reported as related to SARS-CoV-2 infection, all of which occurred in the delta-predominant period in the UK.

The pattern of more serious neonatal disease in the delta period described here may be explained by the higher number and proportion of neonates born very preterm with neonatal SARS-CoV-2 infection during this period. More severe maternal infection and higher rates of preterm birth have been described in the delta-predominant wave in the UK 3 and internationally 17; it is unclear whether this pattern of more severe maternal disease was related to changing characteristics of the viral variant or changes in behaviour and low vaccination rates among pregnant women in the UK during this period. Similarly, it is not possible to determine from these data presented whether the delta variant was more pathogenic in neonates, or whether adverse neonatal outcomes were a result of more severe maternal SARS-CoV-2 disease leading to more preterm births, a well-described risk factor for neonatal infection. 18

There have been very few population-based studies of neonates infected with SARS-CoV-2 infection, and data describing neonatal SARS-CoV-2 infection by variant are even more sparse. Population-level data from Germany describing paediatric SARS-CoV-2 infection show higher rates of COVID-19-related hospitalisation and intensive care unit admission for children under 5 years in the delta-predominant period compared with alpha-predominant, wildtype-predominant and omicron-predominant periods, 19 although data from the UK did not report a higher rate of intensive care admissions for children under 5 with delta compared with earlier viral variants. 20 Data covering approximately 10% of the US population found similar rates of intensive care admissions of infants <6 months of age with the delta and omicron variants. 21 A further study examining administrative data representing approximately 20% of US hospital admissions found that COVID-19 among newborns is rare but is associated with newborn critical care outcomes like invasive ventilation, and that risks for invasive compared with non-invasive ventilatory support were higher in delta compared with pre-delta periods, 22 consistent with the UK data we present here. Single-centre case-series have also reported more severe SARS-CoV-2 infection in infants and neonates in delta-predominant compared with other variant-predominant periods, 4 supporting a link between infection with the delta variant and more severe neonatal disease.

Although there have been multiple registries describing neonatal SARS-CoV-2 infection, 23 24 there have been very few representative population-level studies and those that have published have been limited by low case numbers. 25 The population-level data we present here include and build on previously published neonatal surveillance data from the UK from the first weeks of the SARS-CoV-2 pandemic when the wildtype variant predominated. 2 These updated data describe the presentation and clinical course of neonatal SARS-CoV-2 infection in the largest number of neonates reported to date. Consistent with early data, 2 we confirm that while respiratory signs were widespread, symptomatic neonatal SARS-CoV-2 most commonly presented with poor feeding or other gastrointestinal signs. Fever and respiratory signs were also common but did not predominate as in other paediatric groups. 26 Data from Switzerland in one of the few other population-level surveillance studies found fever and respiratory signs most common at presentation in the 73 neonates reported, 25 possibly reflecting the non-specific nature of these neonatal signs. The large number of neonatal cases we report compared with other neonatal studies provide confidence in our key findings that while receipt of respiratory support is relatively common among neonates hospitalised with neonatal SARS-CoV-2, this is generally seen in the context of preterm birth. Almost half of hospitalised neonates with SARS-CoV-2 infection received some form of respiratory support. We also report reassuring short-term outcomes following neonatal SARS-CoV-2 infection consistent with Swiss national data 25 and international registry data. 27 28

The high rate of presumed nosocomial transmission reported throughout the study (7.8%) is of concern. This likely reflects the challenges of limiting viral exposure in NNUs with few isolation facilities, in the context of a pandemic with high rates of staff and parent infection.

Conclusions

Inpatient care for neonates infected with SARS-CoV-2 was uncommon throughout the first 2 years of the pandemic and short-term outcomes were generally good. Severe disease was more common, although still rare, during the delta variant period; this may have been influenced by more severe maternal disease resulting in more very preterm neonates. Rapidly established and ongoing national surveillance was essential to understand the neonatal impact of the evolving SARS-CoV-2 pandemic, highlighting the key role of established systems such as the BPSU, UKOSS and MBRRACE-UK perinatal mortality surveillance. The long-term effects of early life exposure to SARS-CoV-2 are unknown, and ongoing data collection, linkage and developmental follow-up remain crucial.

Data availability statement

Data are available on reasonable request. The datasets generated during and analysed during the current study are available from the corresponding author on reasonable request.

Acknowledgments

We acknowledge the assistance of Jacob Avis, Richard Lynn and Farhana Ahmed at the BPSU, the BPSU reporting clinicians, the NIHR Clinical Research Networks and other people without whose support this research would not have been possible in such a timely manner.

# data[].attributes.attachment_link.title
Characteristics and outcomes of neonates hospitalised with SARS-CoV-2 infection in the UK by variant: a prospective national cohort study

# data[].attributes.attachment_link.description
Objective Neonatal infection with wildtype SARS-CoV-2 is rare and good outcomes predominate. We investigated neonatal outcomes using national population-level data to describe the impact of different SARS-CoV-2 variants. Design Prospective population-based cohort study. Setting Neonatal, paediatric and paediatric intensive care inpatient care settings in the UK.

# data[].attributes.headline
Beyond the symptoms: Personalizing giant cell arteritis care through multidimensional patient reported outcome measure

# data[].attributes.subject
Beyond the symptoms: Personalizing giant cell arteritis care through multidimensional patient reported outcome measure

# data[].attributes.attachment_link.readable_text
The .gov means it's official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you're on a federal government site.

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

doi: 10.1016/j.semarthrit.2023.152285. Online ahead of print.

Affiliations

¹ Professor Canterbury Christ Church University, England; H. Senior Clinical Lecturer, King's College London, England. Electronic address: secretary@rheumatology4u.com.

² Professor Community and Public Health, Ain Shams University, Cairo, Egypt.

³ H. Senior Clinical Lecturer, King's College London, England; Darent Valley Hospital, Kent, England.

⁴ North Middlesex University Hospital, London, England.

⁵ Darent Valley Hospital, Kent, England.

⁶ Professor of Internal Medicine/Rheumatology, College of Medicine, King Abdulaziz University, Saudi Arabia.

⁷ Professor Rheumatology, Physical Medicine and Rehabilitation, Assiut University, Egypt.

⁸ Professor Rheumatology and Rehabilitation, Benha University, Benha, Egypt.

⁹ Assistant Professor Rheumatology and Rehabilitation, Tanta University, Tanta, Egypt.

¹⁰ Rheumatology and Rehabilitation, Ain Shams University, Cairo, Egypt.

¹¹ Lectuer Rheumatology and Rehabilitation, Alexandria University, Alexanrdia, Egypt.

doi: 10.1016/j.semarthrit.2023.152285. Online ahead of print.

Affiliations

¹ Professor Canterbury Christ Church University, England; H. Senior Clinical Lecturer, King's College London, England. Electronic address: secretary@rheumatology4u.com.

² Professor Community and Public Health, Ain Shams University, Cairo, Egypt.

³ H. Senior Clinical Lecturer, King's College London, England; Darent Valley Hospital, Kent, England.

⁴ North Middlesex University Hospital, London, England.

⁵ Darent Valley Hospital, Kent, England.

⁶ Professor of Internal Medicine/Rheumatology, College of Medicine, King Abdulaziz University, Saudi Arabia.

⁷ Professor Rheumatology, Physical Medicine and Rehabilitation, Assiut University, Egypt.

⁸ Professor Rheumatology and Rehabilitation, Benha University, Benha, Egypt.

⁹ Assistant Professor Rheumatology and Rehabilitation, Tanta University, Tanta, Egypt.

¹⁰ Rheumatology and Rehabilitation, Ain Shams University, Cairo, Egypt.

¹¹ Lectuer Rheumatology and Rehabilitation, Alexandria University, Alexanrdia, Egypt.

Abstract

Background: Giant Cell Arteritis (GCA) is the commonest form of systemic vasculitis in people over the age of 50. Published research highlighted the lack of a disease-specific patient reported outcomes (PROMs) for GCA.

Objectives: To assess the validity, reliability and responsiveness to change of a devised disease specific patient self-reported outcome measures questionnaire for Giant Cell Arteritis (GCA).

Methods: The GCA-PROMs was conceptualized based on frameworks outlined in the OMERACT developed core set of Outcome Measures for Large-Vessel Vasculitis and the guiding principles of the FDA guidance. Initially, cognitive interviews were conducted to identify item pool of questions. Item selection and reduction was achieved based on patients as well as an interdisciplinary group of specialists. Rasch and internal consistency reliability analyses were implemented.

Results: A total of 54 GCA patients completed the questionnaire. The GCA-PROMs questionnaire was reliable as demonstrated by a high standardized alpha (0.878-0.983). Content construct assessment of the GCA-PROMs functional disability and QoL revealed significant correlation (p< 0.01) with both HAQ and EQ-5D. Changes in functional disability, QoL showed significant (p< 0.01) variation with diseases activity status in response to therapy.

Conclusions: The developed GCA-PROMs questionnaire is a reliable and valid instrument for assessment of GCA patients. A stratified treatment regimen depending on the individual patient's risk factors as well as preferences and associated comorbidities is the best approach to tailored patient management.

Keywords: Benefit/risk ratio; GCA; GCA-PROMs; Giant cell arteritis; PROMs; Patient education; Patient stratification.

PubMed Disclaimer

Conflict of interest statement

Declaration of Competing Interest Authors declare no conflicts of interest.

# data[].attributes.attachment_link.keywords[]
national center for biotechnology information

# data[].attributes.attachment_link.title
Beyond the symptoms: Personalizing giant cell arteritis care through multidimensional patient reported outcome measure - PubMed

# data[].attributes.attachment_link.description
The developed GCA-PROMs questionnaire is a reliable and valid instrument for assessment of GCA patients. A stratified treatment regimen depending on the individual patient's risk factors as well as preferences and associated comorbidities is the best approach to tailored patient management.

# data[].attributes.headline
Conference Abstract - Metastatic lung cancer: another symptom of Long COVID?

# data[].attributes.subject
Conference Abstract - Metastatic lung cancer: another symptom of Long COVID?

# data[].attributes.attachment_link.title
Metastatic lung cancer: another symptom of Long COVID?

# data[].attributes.attachment_link.description
National data indicates fewer lung cancer diagnoses in 2020 than 2019 in England, but post-pandemic outcomes are not yet available (https://www.rcplondon.ac.uk/projects/outputs/nlca-annual-report-2022). We aimed to identify trends in lung cancer diagnosis in our hospital before, during and after the COVID-19 pandemic, ahead of national data.

# data[].attributes.headline
The implications when offering percutaneous nephrostomy for the management of malignant obstructive uropathy secondary to urological malignancy: can we be more selective?

# data[].attributes.subject
The implications when offering percutaneous nephrostomy for the management of malignant obstructive uropathy secondary to urological malignancy: can we be more selective?

# data[].attributes.headline
New-Onset Rheumatic Immune-Mediated Inflammatory Diseases Following SARS-CoV-2 Vaccinations until May 2023: A Systematic Review

# data[].attributes.subject
New-Onset Rheumatic Immune-Mediated Inflammatory Diseases Following SARS-CoV-2 Vaccinations until May 2023: A Systematic Review

# data[].attributes.attachment_link.title
New-Onset Rheumatic Immune-Mediated Inflammatory Diseases Following SARS-CoV-2 Vaccinations until May 2023: A Systematic Review

# data[].attributes.attachment_link.description
A comprehensive, up-to-date systematic review (SR) of the new-onset rheumatic immune-mediated inflammatory diseases (R-IMIDs) following COVID-19 vaccinations is lacking. Therefore, we investigated the demographics, management, and prognosis of new R-IMIDs in adults following SARS-CoV-2 vaccinations. A systematic literature search of Medline, Embase, Google Scholar, LitCovid, and Cochrane was conducted.

# data[].attributes.headline
Efficacy and Safety of Hyaluronic Acid and Platelet-Rich Plasma Combination Therapy Versus Platelet-Rich Plasma Alone in Treating Knee Osteoarthritis: A Systematic Review

# data[].attributes.subject
Efficacy and Safety of Hyaluronic Acid and Platelet-Rich Plasma Combination Therapy Versus Platelet-Rich Plasma Alone in Treating Knee Osteoarthritis: A Systematic Review

# data[].attributes.headline
Taking a Break? The Growing Trend of FY3: Why More Junior Doctors are Taking Time Out after the Foundation Programme and What They Elect to Do?

# data[].attributes.subject
Taking a Break? The Growing Trend of FY3: Why More Junior Doctors are Taking Time Out after the Foundation Programme and What They Elect to Do?

# data[].attributes.attachment_link.readable_text
There is a growing trend of UK doctors taking time out of clinical training following completion of the Foundation Programme. At a time when NHS services are facing unparalleled demand, considering the reasons why early career clinicians are deciding to delay entry into specialist training is paramount. Here, we describe some of the push and pull factors contributing to the "FY3" year phenomenon as well as the avenues doctors explore. Within the NHS, clinical fellowships can offer more flexibility in terms of rota and location compared to specialty training posts whilst also providing clinical experience and the chance to develop highly sought-after skills in teaching, research, and leadership. Similarly, locum rotas can be negotiated and usually offer significantly enhanced pay. Outside of the NHS, healthcare systems in Australia, New Zealand, and Canada actively seek out UK doctors, incentivising them with better work-life balance, increased pay, and improved working conditions, leading many doctors who had intended to return to the NHS to stay abroad. Doctors are also becoming increasingly aware of their transferable skills and the value they can bring to non-clinical roles in the pharmaceutical industry, management consulting, and medical law. Although the FP was originally introduced to address issues surrounding career progression and poor training experiences, current push factors for taking an "FY3" including increasing competition for specialty training posts, an imbalance towards service provision versus training, and high workload suggest systemic issues within the UK health service are undermining this aim and ultimately leading doctors to take time out of training.

# data[].attributes.attachment_link.title
Taking a Break? The Growing Trend of FY3: Why More Junior Doctors are Taking Time Out after the Foundation Programme and What They Elect to Do?

# data[].attributes.attachment_link.description
There is a growing trend of UK doctors taking time out of clinical training following completion of the Foundation Programme. At a time when NHS services are facing unparalleled demand, considering the reasons why early career clinicians are deciding to delay entry into specialist training is paramount.

# data[].attributes.headline
Reconstruction of the ‘Foot at Risk’ during Acute Charcot Neuroarthropathy

# data[].attributes.subject
Reconstruction of the ‘Foot at Risk’ during Acute Charcot Neuroarthropathy

# data[].attributes.headline
Streams, rivers and data lakes: an introduction to understanding modern electronic healthcare records

# data[].attributes.subject
Streams, rivers and data lakes: an introduction to understanding modern electronic healthcare records

# data[].attributes.attachment_link.readable_text
Abstract

As foundation doctors, we have often found ourselves informing patients that a certain aspect of their medical information cannot be immediately found, either because it is on an electronic system we cannot access, or it is in a hospital that is unlinked to our own. Unsurprisingly, this frequently leaves patients flabbergasted and confused. We started to wonder: if patients' data are entered onto an electronic system: where do those data go? If medical data are searched for, where do those data come from? Why are there so many hidden sources of information that clinicians cannot access? In an ever-increasing digital sphere, electronic data will be the future of holistic health and social care planning, impacting every clinician's day-to-day role. From electronic healthcare records to the use of artificial intelligence solutions, this article will serve as an introduction to how data flows in modern healthcare systems.

What makes electronic healthcare records differ from one another?

Healthcare data can be defined as patient information that is entered by clinical or non-clinical individuals. Traditionally written in paper format (eg discharge letters, test results, appointments and clinical notes), patient records could become multiple volumes of healthcare data. Electronic healthcare records (EHR) are defined as a data system that stores patient healthcare data. Although a clinician might believe that they are interacting with a single EHR, in reality, most hospitals use multiple types (Table 1).

EHR software brands can vary by hospital and are often divided into two categories: (1) bespoke ('lots of little' EHRs or 'best of breed') models: where many single systems are designed for specific departments needs and data communicates between them; or (2) monolithic models: where one EHR system is used for the whole hospital serving every clinical department or scenario.

The benefit of monolithic EHRs is that they directly link healthcare data without the need to open new software or use multiple single sign-on tools. However, monolithic EHRs can be difficult to specialise to the needs of every clinical department. For foundation doctors, this manifests as a clear difference in usability from one EHR system to another.

Data fragmentation and integration: where are my patients' data?

EHRs that are entirely unlinked to other healthcare software are termed 'data silos'. Data silos represent a closed-off, unintegrated source of clinical information and include data used in research, private healthcare, genomics and in wearable devices (eg digital watches that monitor heart rate). Historically, when EHRs were deployed, not enough consideration was put into how those data could be shared or integrated into other systems. From a foundation doctor's perspective, this means fragmented or missing data, which require accessing multiple systems to retrieve (eg by making laborious calls and sending emails to clinical secretaries or on-call doctors at another institute or NHS Trust).

Another way in which healthcare data become fragmented and lost is when a clinician attempts to adapt an EHR to fit their clinical need. This occurs via the frontend-backend disconnect: what a clinician sees on the user interface (frontend) does not encompass all the data stored (backend). It is relatively easy for clinicians to alter the frontend with new electronic forms. However, without altering the backend, these forms are stored in an unusable form; moreover, these alterations require specialist knowledge often lacking in NHS Trusts. Therefore, healthcare records mirror a library without an indexing catalogue, where anyone can just throw a book inside (Fig 1).

Preventing this 'library-with-no-index' scenario, where data cannot be easily retrieved, requires data linkage and integration. This has been attempted for more than 20 years and is currently happening via the integrated care systems (ICS), outlined in the NHS 2019 Long-Term Plan. Unfortunately technological barriers exist that prevent data linkage and integration, preventing clinicians from accessing healthcare data, thereby worsening the socioeconomic burden on healthcare systems.

Streams and rivers: how do my patients' data move through EHR systems?

For clinicians, understanding data flows is key to understanding how data are shared between different EHRs. When healthcare data are entered, like a stream it can flow one way, whereas a turbulent data river can flow both ways, allowing for data exchange. Data can also differ in language and structure; therefore, if they are not standardised, the flow becomes a torrent of garbled unstructured data, useless to clinicians seeking a source of accurate, succinct and timely information (like fishing in murky waters). For communication between different EHR systems, the data need to be standardised; hence, the common data term: interoperability. Interoperability is defined as the ability of different EHR systems to share healthcare data, and is achieved through standardisation of semantics and syntax: semantic standardisation organises via language, referring to the meaning of content, whereas syntactic standardisation organises via structure, referring to the ordering of words, phrases or messages.

Semantic standardisation is traditionally achieved through clinical coding. Clinical coding is performed by GPs in GP practices, and by clinical coders in hospitals. Clinical coders read and interpret clinical text to assign relevant codes that reflects a patient's care during a hospital visit. Correct and efficient clinical coding is essential for service evaluation, research and medical billing. Inaccuracies in coding (eg if a procedure that was carried out is missed) leads to the misallocation of staff, funds and resources, resulting in inefficiencies and waste. For foundation doctors, this often means the frustrating task of filling in structured proformas or checklists to help inform clinical coders before an administrative task is complete or a patient is discharged. The major coding system currently used for diseases is the International Classification of Diseases version 10 (ICD-10). Office of Population and Census survey version 4 (OPCS-4) is the coding classification used for interventions and procedures. Another newer ontological coding system is called Systematized Nomenclature of Medicine-Clinical Terms (SNOMED-CT): this covers diseases, procedures as well as many other biomedical and healthcare concepts (eg anatomy, occupation, etc.). Unlike other coding systems, SNOMED-CT has a larger, more detailed vocabulary and, therefore, it better reflects the language of clinicans.

Syntactic standardisation allows for formal data structuring. For example, if a message states 'NHS number', the recipient knows that the next 10 digits is the NHS number; similarly, dates follow a date-month-year format. The area in healthcare that has most effectively standardised itself is radiology, via Digital Imaging and Communications in Medicine (DICOM). Given that DICOM standards were decided early, different hospitals could easily share imaging. In the rest of healthcare, the main data messaging standard is Health Level Seven (HL7): a universal packaging system and a standard of transmitting data to allow different EHR systems to communicate. The latest HL7 incorporates a flexible data structure called 'fast healthcare interoperability resources' (FHIR) (Fig 2). Unfortunately for foundation doctors, many EHR systems were installed without implementing adequate data syntactic standardisation because of cost, effort and inability to gain consensus; therefore, patients' data can easily get lost or confined inside a difficult to access system. Moreover, owing to data protection legislation, healthcare data need to be retained for access for up to 25 years; therefore, data can be trapped for decades in old systems that function poorly on modern computers.

Machine learning, artificial intelligence and data lakes: how can my patients' data be better utilised?

Foundation doctors who use EHR certainly understand the inefficient ways in which patients' data are utilised; however, newer innovative approaches are on the horizon, such as by using an open-source artificial intelligence (AI) framework called CogStack, which can extract data from unstandardised EHR and data silos. CogStack syphons out data, bringing them into one place: the data lake. Databases store data, data lakes represent large pooled databases and data warehouses represent organised data lakes. Data lakes contain millions of data sets, termed 'big data', sourced from a myriad of databases. Data that clinicians enter can be structured (ie lab results) or unstructured (ie clinical entries in the form of free text). Around 80% of big data are unstructured; this vital raw information cannot be used to a fraction of its worth. Big data require filtering: simplified into essential components ('abstraction'), converted into a suitable format ('transformation') and standardised via terminology ('harmonisation'). Filtering requires a natural language processing (NLP) system, a subset of machine learning (ML) and AI.

AI uses advanced statistical approaches and computer models to mimic the organisation of the human brain. ML is a subset of AI, first introduced during the 1990s; it algorithmically derives patterns and 'learns' from past data without explicit programming. Deep learning is a subset of ML and uses big data to feed machines with large amounts of these raw data, developing its own representations needed for pattern recognition. For clinicians, a ML solution could provide a single user interface that is accessible across all systems simultaneously. The ML concept of NLP allows data to be 'read' quickly by using a combination of text-mining and terminology recognition (Fig 3). An illustration of an open-source NLP that uses big data is the medical concept annotation toolkit (MedCAT). MedCAT uses SNOMED-CT as a source of clinical terminology, but can use any standardised vocabulary.

For clinicians, data are most valuable when they are cleaned and usable; NLP can help sanitise data before use. For foundation doctors looking at clinical entries or writing a discharge letters, it can be time consuming to look through a set of complex patient records. Imagine an NLP system in which your patient's genomics, wearables and other standard clinical information were easily accessible and analysable at the point of entry. This could prevent inefficiencies and be invaluable for patients who cannot fully communicate their own care needs, such as non-native speakers or the cognitively impaired.

Ethical considerations of big data: how can I protect my patients' data?

If AI is to serve as a trusted clinical aid, it must be robust, accurate and as free as possible from bias. Moreover, big data in AI represents the personal information of millions of individuals; thus, respect of privacy via consenting and prevention of data breaches via secure storage embody important safeguarding strategies. Safeguarding data by only including individuals who actively provide consent can appear fair but cause bias because certain socioeconomic classes, ethnic groups and others (eg those with a learning disability) are under-represented in consenting. Opt-out strategies, as well as ensuring openness and honesty, might be the most logical approaches to handling big data in these scenarios.

Anonymising data (all identifiers removed) or pseudonymising data (all identifiers replaced) could reduce the risk of re-identification breaches, especially in research. However, these strategies can lead to vital information, such as demographics, ethnicity or age, being lost, producing biases through missing data. For example, if poorer outcomes are experienced in a certain postcode but that location information is lost via anonymising, research outcomes that appear fair might in fact be biased. Bias does not imply intent; it might simply be unrepresentative of the entire patient population. A solution could be to establish a trusted research environment in which data are more openly used by trusted organisations; this was successful deployed during the coronavirus pandemic, allowing real-time data analysis in a fast-evolving situation.

Conclusion

As EHRs continue to grow, high-quality patient care will require foundation doctors to have a detailed understanding of digital healthcare systems. It will also become essential to teach all doctors about EHR design as well as to train them regarding how best to exploit modern data strategies to efficiently process, extract and utilise raw data obtained at the point of entry. There is a danger of creating AI that has built-in bias; however, with the hindsight of knowing how EHRs have historically worked, there is a unique opportunity to create a system built by design rather than necessity: this requires being conscious in its creation. Health inefficiencies and health inequality continue to represent huge socioeconomic burdens. Establishing EHR interoperability, instituting integrated monolithic EHRs and utilising machine learning tools represent extremely exciting future solutions to these conundrums.

Acknowledgements

We thank Rudy Harris, Klara De Baerdemaeker and Hani Salih for helping to sense check this piece for junior doctors and the general reader.

# data[].attributes.attachment_link.title
Streams, rivers and data lakes: an introduction to understanding modern electronic healthcare records

# data[].attributes.attachment_link.description
As foundation doctors, we have often found ourselves informing patients that a certain aspect of their medical information cannot be immediately found, either because it is on an electronic system we cannot access, or it is in a hospital that is unlinked to our own. Unsurprisingly, this frequently leaves patients flabbergasted and confused.

# data[].attributes.headline
A Multiplexed Urinary Biomarker Panel Has Potential for Alzheimer's Disease Diagnosis Using Targeted Proteomics and Machine Learning

# data[].attributes.subject
A Multiplexed Urinary Biomarker Panel Has Potential for Alzheimer's Disease Diagnosis Using Targeted Proteomics and Machine Learning

# data[].attributes.attachment_link.readable_text
1. Introduction

Alzheimer's disease (AD) is a progressive neurodegenerative disease and the most common cause of dementia. A definite diagnosis of AD can only be made post-mortem and by neuropathological confirmation of extracellular amyloid plaques. These plaques are composed of fibrillar amyloid and intracellular tau tangles, containing hyperphosphorylated tau [ 1].

Since the brain is inaccessible during life, the AD field has relied on imaging and cerebrospinal fluid (CSF) biomarkers to support clinical diagnosis, classify individuals for research studies or to interrogate and track pathophysiology [ 2, 3]. With the development of new disease-modifying therapies, it has become critically urgent to develop biomarkers that will identify individuals who are most likely to benefit from them. Thus, we need to develop tests that are simple to obtain, less invasive, high throughput and cost effective so we can test widely.

Currently, several fluid biomarkers are now validated to support clinical diagnosis in CSF [ 4]. These include the use of the ratio of the beta-amyloid peptides Aβ1-42/1-40, P-tau a marker of tau pathology, and neurofilament light (NfL), a biomarker of neuroaxonal damage [ 5, 6]. There are also promising biomarkers of amyloid, tau and neurodegeneration in plasma [ 7] and they are in the process of being validated in real life populations, with plasma P-tau 217 looking particularly promising [ 8, 9, 10, 11]. However, all these tests are expensive to perform, require invasive procedures, have to be pre-handled and centrifuged at source, and analyses performed in specialist laboratories.

CSF is obtained by lumbar puncture (LP), which is safe and generally well tolerated. However, it is not possible to perform this procedure on everyone, for instance those on blood-thinning agents, and is an invasive procedure that carries a 5-10% risk of post-LP syndrome [ 12]. Although blood is more accessible, it still remains invasive, and requires strict pre-handling practices with rapid centrifugation at source, to provide reliable results [ 13]. Therefore, there is considerable interest and a need for developing biomarkers in novel and non-invasive biological fluids such as urine that are easier and cheaper to collect, store, process and analyse. This could potentially be collected in the home environment and shipped to a lab through the post with no sample preparation required. Sampling is likely to be more acceptable to patients and could be widely used for earlier screening in mid-life populations outside of specialist centres and in any geographical location.

Despite extensive progress in CSF and serum biomarkers, research into biomarkers for brain diseases in urine is lagging behind. This is due to the significantly lower protein concentrations making detection more difficult and that urine is more distant from the brain compared with CSF and plasma. However, with technological advances in mass spectrometry, the increasing use of triple quadrupole mass spectrometers in chemical pathology and their unique ability to perform targeted proteomic analyses of multiple biomarkers at once, it is now conceivable that urinary biomarkers of AD can be measured. Urine has been explored previously for its potential for AD diagnosis particularly for metabolite changes [ 14, 15, 16, 17, 18]; however, the urinary metabolome can be highly variable so we have looked at the potential of urinary proteins. Conventionally most urinary protein is thought to be kidney derived but it has been shown to contain many membrane and extracellular proteins not just from the renal system but also from other distant organs [ 19, 20]. More recently its potential is being explored for neurological conditions such as brain cancer [ 21], Parkinson's disease [ 22] and AD [ 23, 24, 25, 26]

Furthermore, the use of machine learning and AI approaches is revolutionising diagnostics as we move to use multiple biomarkers to refine prognosis and diagnosis [ 27]. Therefore, in this study we tested the hypothesis that individuals with AD would have a different urinary proteomic profile to healthy controls and that these could reflect changes in relevant pathobiological pathways. The aims of this exploratory study were to:

Screen the urine proteome in participants with AD and compare with healthy controls using untargeted proteomics to identity pathways and potential AD biomarkers;

Create a translational and rapid test to validate any biomarkers using a multiplexed, targeted proteomic approach in an independent cohort;

Use machine learning techniques to develop a 'panel' of biomarkers that could be used to help diagnose AD.

2. Results

As expected, a significantly greater proportion of AD individuals in the discovery cohort were APO ε4-positive compared to controls in both cohorts. CSF amyloid concentration was lower in those with AD, and T-tau and P-tau were higher. MMSE scores were unsurprisingly lower in the AD group. These individuals were in the mild to moderate stage of the disease. The discovery and validation cohorts are described in full in Table 1.

2.1. Biomarker Discovery and Pathway Analyses: Comparison of Urinary Proteomic Analyses from AD Patients and Healthy Controls

The discovery cohort was composed of eleven individuals: six participants fulfilled clinical criteria for typical AD, and five were healthy controls. Label free proteomics and bioinformatic analyses identified a total of 1525 proteins. Comparison between the AD and control patient group identified a total of 42 proteins demonstrating changes in expression of protein between both groups (see Supplementary Table S1 for details). As described in the methods section, all proteins ranked A, B and C and demonstrating changes in expression, designated as showing a statistical significance of p < 0.05, were analysed using the Ingenuity Pathway analyses bioinformatics package (Qiagen, Venlo, The Netherlands).

Ingenuity canonical pathways analyses identified proteins activated by oxysterol ligands, cholesterol and bile acid metabolism (LXR/FXR/RXR activation) to be significantly changed in the urine of AD patients. Other changes observed included those involved in protein synthesis or folding and also changes in energy metabolism. Remarkably, disease function analyses identified nine proteins previously described as being altered in AD and amyloidosis diseases (APOA4, HSPA5, RNASET2, PLD3, FRMD4B, B2M, HPX, SERPINC1, OLR1). The functional pathway amyloidosis and familial amyloidosis being the first and third most significant pathways changed, with AD being the second and eighth most significantly relevant disease identified for each pathway, respectively. Figure 1 shows a summary of the results from the discovery phase.

2.2. Development of a Targeted and Multiplex Assay to Validate Potential Urinary Proteomic Biomarkers of AD

Unlike the pathway analyses of potential disease-modifying proteins in AD where all significant, differentially expressed proteins are taken into account, the development of a validatory and high-throughput test requires only those biomarkers with high confidence identification being taken forward. Figure 2 shows the 29 high-confidence proteins identified in this Rank A group that were taken forward for evaluation from the discovery analyses. These potential biomarkers were augmented into our in-house neuroinflammatory targeted proteomic panel [ 28], which was constructed from a mixture of literature reviews, known biomarkers of neurodegeneration and inflammatory factors. Therefore, a total of 88 protein biomarkers were developed into a scheduled, 17 min, multiplexed and targeted proteomic test. This panel of potential hypothesis-driven and hypothesis-generated biomarkers were then analysed in a total of 21 patients which constituted of 9 individuals with AD and 12 healthy, age-matched controls.

2.3. Individual Biomarkers and Univariate Analyses for the Diagnosis of AD

Out of the total of 88 biomarkers analysed in the multiplexed validatory test, we could detect reliably 61 proteins. We applied elastic net regression to pinpoint the most influential proteins in the discrimination between AD and healthy controls. We identified a total of five proteins which demonstrated potential for being put forward as possible biomarkers for AD ( Figure 3a). These included the four proteins, REG1B, VCAM1, TNF-beta and MIEN1, which were observed to be present in lower concentrations in AD urine. The protein, ABAC7, was the only potential biomarker to be elevated, with a 1.5-mean fold increase in concentration in the AD group compared to the controls ( Figure 3a,b). However, of all the biomarkers only MIEN1 demonstrated a statistically significant change in concentration compared to the control group ( Figure 3b). The biomarkers ABAC7 and MIEN1 (FC = −1.8) which demonstrated the greatest fold-change relative to one another, was further evaluated by looking at their relationship to one another in each patient. By ratioing the biomarkers MIEN1/ABAC7, we were able to further increase the statistical significance between the AD and controls even further ( Figure 3 c, p = 0.01).

2.4. Multilinear Regression and Machine Learning Analyses of Multiple Biomarkers for Improving the Specificity and Sensitivity for Diagnosing AD

To improve accuracy and sensitivity of the assay, we modelled the proteins using linear regression ( Figure 4). The AD and control samples were initially assessed using the significantly different protein MIEN1 alone; prediction of the samples in the model demonstrated an overall classification accuracy of 71% (56% sensitivity). To evaluate if the classification strength could be improved by using more predictors, we included the proteins which had been chosen in the elastic net feature selection performed to find the most relevant proteins to discriminate between AD and controls. This rendered us with a model including MIEN1, TNFB, VCAM1, REG1B and ABCA7. These five proteins were applied as predictors in a multiple linear regression model and when the samples were once more predicted, the overall classification accuracy was 86%, demonstrating a 15% improvement as compared to using the protein MIEN1 alone. Given the small sample size, we opted for performing k-fold cross validation on the model, where we utilised ten splits of the data. This resulted in six out of nine samples being accurately predicted as AD, and eight out of twelve samples accurately predicted as control.

3. Discussion

In this exploratory study, we used untargeted proteomic profiling to identify proteins that were differentially expressed in affected AD patients compared to unaffected control urine. We were able to detect differences in a number of proteins known to be implicated in AD pathology and related biological pathways. Furthermore, we developed a targeted proteomics panel and validated our findings in an independent cohort. Our findings suggest that this approach could have potential as a test in clinical practice for first tier screening or potentially to monitor new treatments. Since many of the proteins we identified are implicated in brain amyloidosis, a pathophysiological process which predates symptom onset in AD by ~25 years [ 29], we postulate that this biomarker panel has potential as an early pre-symptomatic screening tool for AD.

Finding biomarkers for early and accurate diagnosis of AD has become an urgent priority in the dementia field, now that three immunotherapies against fibrillar amyloid have demonstrated utility in slowing cognitive progression in mild to moderate AD [ 30, 31]. Inclusion in these studies requires demonstration of amyloidosis and tauopathy in the brain, either by cerebrospinal fluid analysis or PET scanning, and this is likely to remain the gold standard for providing accurate individual biomarkers support for a diagnosis of AD. However, the infrastructure for carrying out LPs and PET scans in the general population is very limited [ 32]. Tools for screening and risk stratification in the general population will be extremely important, particularly in countries without access to advanced diagnostics for dementia [ 33, 34]. Blood biomarkers are currently reasonably advanced in their development, with plasma P-tau 217 (particularly the P-T217/T217 ratio [ 35, 36]) proving to be a strong predictive marker of amyloid burden and tau deposition, in real life populations [ 37, 38] and plasma Aβ42/40 ratio allowing for reasonable separation of AD from non-AD individuals [ 39]. Yet, one limitation of blood biomarkers is the need for strict pre-handling protocols so that samples are centrifuged rapidly to avoid the effects of proteases degrading proteins of interest [ 40]. This is likely to limit its use in regional memory clinics and geographically isolated healthcare environments. It is also likely to be a barrier for home self-testing. In this study, we collected urine from a mid-stream sample. No early aliquoting or centrifugation was required at the point of collection, and very limited instructions were provided to participants, even those with moderately severe cognitive impairment. This means that collection is likely to be feasible across populations in developed and developing countries, making it an attractive screening tool and urine should be considered a more 'liquid gold' biofluid rather than just a waste product.

Using a univariate analysis only one protein, migration and invasion enhancer 1 (MIEN1), demonstrated a clear and statistically significant change in expression between the AD and control groups. MIEN1 is an intracellular protein located to the cytosol and centriole, that is expressed in many tissues but has a particularly high expression in the basal ganglia and cerebellum of the brain. MIEN1 is known to be a negative regulator of apoptosis and a positive regulator of cell migration and has gained significant interest in its role in breast cancer. However, MIEN1 variants have also been associated with early onset AD [ 41]. The exact mechanism of action is unclear, but MIEN1 is postulated to both interact with glutathione peroxidase and plays a significant role in the regulation of apoptosis through control of caspase 3 (CASP3). Variants in both these proteins are known to be associated strongly with AD, in particular CASP3 which cleaves beta amyloid 4a protein which is strongly associated with neuronal cell death observed in AD patients. Although individual statistical significance was not achieved with the other elevated proteins identified in this study, we were able to demonstrate that the diagnostic classification accuracy increases by 15% when utilising a panel of five proteins as compared to one protein alone. This highlights the strength of a carefully selected biomarker panel to improve the diagnostic and predictive ability of discriminant models. Our study is limited by the small sample size, but we anticipate that with increased sample numbers and statistical power, we could improve classification accuracy. Further, the five predictor proteins are involved in a range of biological processes that are plausibly relevant to AD pathophysiology, generally implicating lipid metabolism and inflammation pathways. Metabolomic-wide studies (MWAS) have demonstrated utility in elucidating the molecular mechanisms by which individual genes confer risk for AD. A recent study demonstrated that variations in ABCA7 are linked to increased risk of AD through altered sphingolipid metabolism [ 42]. Using disease and functional analyses, we have identified changes in a number of biomarkers involved in amyloidosis and AD including PLD3. Importantly, a previous urine proteomics study found that PLD3 is associated with AD [ 43]. Future MWAS studies may compliment the current study and other proteomics studies in the manipulation of therapeutic targets for AD.

A strength of this study is the well-phenotyped clinical characterisation of the discovery cohort, carried out at a national specialist centre, with diagnosis supported by imaging and CSF biomarkers. Although the number of individuals was small, we were able to provide an independent discovery and validation cohort. Unusually we had access to 'ideal' healthy controls who were the relatives of patients with AD. This meant that they were age matched, did not have cognitive symptoms, and agreed to have a LP as part of another observational study [ 44], which allowed us to confirm that they did not have biochemical evidence of brain amyloid pathology. Conversely, the validation cohort had limited clinical information, based on the restrictions of the ethics under which these individuals were recruited and therefore the individuals included could be at a different stage of the disease. However, the results obtained in this work are extremely promising and should be replicated in much larger cohorts of samples from patients across a range of neurodegenerative diseases and across AD disease course, especially during the pre-clinical phase to understand the assay's potential as a pre-symptomatic screening tool.

In summary, we have identified and validated differences in the urinary proteome between patients diagnosed with AD and healthy age-matched controls. The use of a machine learning approach in combination with a multiplexed panel of biomarkers, allowed us to improve the power of the assay to correctly identify the majority of AD patients analysed in this study. This provides proof of concept that a multiplex of AD-related proteins can be detected in urine using mass spectrometry and demonstrates the potential utility of high-throughput panels of urinary biomarkers to aid clinical diagnosis of AD.

4. Materials and Methods

4.1. Discovery Cohort

Individuals who fulfilled clinical research criteria for AD were prospectively recruited from a specialist cognitive disorders clinic as previously described [ 44]. All individuals underwent mini-mental state examination (MMSE; [ 45]) brain MRI, detailed neuropsychological assessments and had a LP. Controls were prospectively recruited and were age and sex matched (spouses or friends of those with AD), had no cognitive complaints, MMSE scores ≥ 28 and non-AD CSF profiles. Apolipoprotein E (APOE) ε2/ε3/ε4 genotype status was determined as previously described [ 44].

4.2. Validation Cohort

Individuals who fulfilled consensus criteria for AD were prospectively recruited from a diagnostic LP clinic. We included individuals who fulfilled clinical research criteria for AD [ 46], but CSF and other clinical data were not available for inclusion in this study. Controls were accompanying family or friends and reported no cognitive problems. Only basic demographic data were collected.

4.3. CSF Sample Collection, Pre-Analytical Handling, and Analysis

CSF samples were prospectively collected in the discovery cohort according to a standard operating procedure. Aβ1-42, T-tau, and P-tau assays were performed in batches according to local laboratory standard operating procedures to achieve inter-day coefficients of variation (CV) < 10% as previously described [ 47].

4.4. Urine Sample Collection and Pre-Clinical Handling

Individuals were asked to provide a midstream sample of urine during their research visit and to fill a 100 mL polypropylene screw-top container (Starstedt, product code: 75.1354.001). Samples were collected between 0800 and 1200. Samples were collected at room temperature and transferred directly to a −80 freezer within 2 h.

4.5. Urinary Creatinine Measurements

Creatinine concentration was measured for each urine sample using mass spectrometry as previously described [ 48].

Discovery proteomics: Samples were thawed at room temperature and vortexed for five seconds prior to aliquoting of 2 mL urine into 5 mL centrifuge tubes from Eppendorf. The 2 mL aliquots were centrifuged at room temperature at 3761× g for 30 min to separate the urinary sediment from solution using a Sorvall Legend RT centrifuge. The supernatant was transferred to Amicon Ultra-4 10 kDa molecular weight cut-off filters from Merck Millipore (Burlington, MA, USA) and 2 mL Milli-Q water was added to give a final volume of 4 mL. To concentrate the urinary proteins, the samples were centrifuged at room temperature for one hour at 4444× g (Sorvall Legend RT). The concentrate was transferred to a 1.5 mL centrifuge tube (Eppendorf). To ensure maximum recovery, the filters were washed with 100 μL 50 mM ammonium bicarbonate which was pooled with the concentrate. 800 μL ice-cold acetone was added to the pooled concentrate and the samples were vortexed for five seconds before overnight incubation in −20 °C. To separate the supernatant from the protein pellet, the samples were centrifuged for 10 min at +4 °C and 16,900× g using a Micro-centrifuge 5424 R (Eppendorf). The supernatant was carefully pipetted off and discarded. The pellet was air-dried in a fume hood for 20 min to evaporate residual acetone. 100 μL Milli-Q water was added to the samples and the protein pellet broken up by vigorous vortexing. The samples were thereafter freeze-dried overnight, followed by tryptic digestion with overnight incubation, solid phase extraction to purify the peptides and overnight evaporation of solvents [ 49]. The digested and SPE-cleaned samples were reconstituted in 50 μL 3% acetonitrile, 0.1% TFA and a peptide assay was performed. The peptide concentration in the samples was normalised to 1000 ng/μL before instrumental proteomics discovery analysis by 2D-LC-MS.

The peptides were separated using a 2D-NanoAquity liquid chromatography system (Waters, Manchester, UK). All samples were fractionated online into ten fractions over a 12-h period as previously described [ 50]. After acquisition, data were imported to Progenesis QI for proteomics (Waters) and the fractions 1-10 were individually processed before all results were merged into one experiment. The Ion Accounting workflow was utilised, with UniProt Canonical Human Proteome (exported 2017) as database. The digestion enzyme was set as trypsin. Carbamidomethyl on cysteines was set as a fixed modification; deamidation of glutamine and asparagine, oxidation of tryptophan and pyrrolidone carboxylic acid on the N-terminus were set as variable modifications. The identification tolerance was restricted to at least two fragments per peptide, three fragments per protein and one peptide per protein. A false discovery rate of 4% or less was accepted. The individual fractions were combined in Progenesis, using the multifraction experiment workflow. At least two unique peptides per protein and an identification confidence score larger than 15 were set as thresholds for classifying a protein as a confident identification.

4.6. Development of a High-Throughput, Multiplexed and Targeted Proteomic Assay

Potential biomarkers and those proteins demonstrating significant changes in protein expression were further subdivided and ranked into three groups A, B and C. Rank A biomarkers consisted of protein identifications where at least two unique peptides were observed and had a confidence score higher than 15. Other proteins were ranked B by having at least two unique peptides were identified/confidence score higher than 15, and C ranking indicates that one unique peptide was observed and the confidence score was lower than 15. All proteins, regardless of confidence rank, were then included in bioinformatic analyses where we looked for statistically significant changes in expression and fold change. However, only proteins ranked as A and identified by this high stringency analysis, thus more likely to better and more robust biomarkers, were taken forward for validation using a targeted proteomic approach.

The sample cohort for the targeted validation study was prepared using the same method as the discovery cohort but using 4 mL of urine and with 150 ng whole protein ENO1 (yeast) added as an internal standard to account for losses during sample preparation and for quantitation. The concentrated, digested and SPE-cleaned urine samples were reconstituted in 50 μL 3% acetonitrile, 0.1% TFA, containing 0.1 μM of stable heavy isotope labelled peptides or 'AquaPeptides' (ALDOA, C3, GSTO1, RSU1 and TSP1) prior to analysis by UPLC-MS/MS. The analytical settings have been described previously [ 28]. The MRM method consisted of 189 unique peptides and was split over two injections to ensure adequate acquisition of the transitions. A table detailing MRM transitions is available in Supplementary Table S2. After acquisition, data were peak picked using an in-house developed Python-based guided user interface (GUI) and peak picking application [ 51] or the MassLynx (version 4.1) module TargetLynx (Waters). In the GUI application workflow, the raw instrument files were converted to text files using the application MSConvert from ProteoWizard [ 52] and imported to the application. Peaks were aligned if necessary, and thereafter integrated. When TargetLynx was used, data were imported to the application and quantitative methods were created and applied to the data. The targeted raw data are available via the Panorama repository https://panoramaweb.org/AD_Urine_Proteomics.url (accessed on 27 August 2023). A complete summary of the workflow and methodology is described in Figure 5.

4.7. Statistical Analysis

Most of the statistical analyses were performed in Python (version 3.6) [ 53]. The proteins detected in the discovery analysis transformed to normality using a Box-Cox transformation (boxcox) from SciPy's stats package (version 1.11.0). Student's t-test with a nominal p-value threshold of 0.05 was applied to determine differential protein expression between the groups. Correlation analyses were performed using Pearson correlation (SciPy). The data were visualised using the Seaborn library (version 0.12.2) and the multivariate tool principal component analysis in the software SIMCA, version 17 (Umetrics Sartorius Stedim, Umeå, Sweden).

Linear regression models of proteins analysed in the targeted workflow were built using Scikit-learn (version 1.2.2). Feature selection was performed using a 5-fold cross validated elastic net regression (Scikit-learn) to pinpoint the variables of greatest importance to discriminate between AD and control samples. A multiple linear regression model was built using the panel of selected proteins. Cross validation was performed using KFold cross validations from Scikit-learn with ten splits of the data.

4.8. Pathway Analysis

The proteins expressing a nominally significant difference (p < 0.05) between the AD and the control groups were investigated using the expression analysis workflow in Ingenuity Pathway Analysis (Qiagen, Venlo, The Netherlands). To determine up- or downregulation of a protein in the AD group, the average fold-change compared to the control group was calculated.

4.9. Ethics

Ethical approval was obtained from the National Hospital for Neurology and Neurosurgery Research Ethics Committee (12 LO 1504, Dec 2012, Queen Square ethics committee) and written informed consent was obtained from all participants.

Supplementary Materials

Author Contributions

J.H.: Conceptualization, data acquisition, data curation, formal analysis, methodology and writing-original draft. R.C.P.: Data curation, formal analysis, methodology and writing-original draft. W.E.H.: Data curation, formal analysis, methodology and writing-original draft. J.C.: Writing-original draft. A.J.M.F.: Writing-review & editing. C.F.S.: Data acquisition, writing-review & editing. C.A.L.: Writing-review & editing. E.C.M.: Writing-review & editing. H.Z.: Conceptualization and writing-review & editing. J.M.S.: Conceptualization and writing-review & editing. K.M.: Conceptualization, methodology, formal analysis, funding acquisition, project administration, resources, supervision and writing-original draft. R.W.P.: Conceptualization, methodology, formal analysis, funding acquisition, project administration, resources, supervision and writing-original draft. All authors have read and agreed to the published version of the manuscript.

Funding

R.C.P. is supported by the UK Dementia Research Institute [award number MC_PC_17114] which receives its funding from UK DRI Ltd, funded by the UK Medical Research Council, Alzheimer's Society and Alzheimer's Research UK. H.Z. is a Wallenberg Scholar supported by grants from the Swedish Research Council (#2022-01018 and #2019-02397), the European Union's Horizon Europe research and innovation programme under grant agreement No 101053962, Swedish State Support for Clinical Research (#ALFGBG-71320), the Alzheimer Drug Discovery Foundation (ADDF), USA (#201809-2016862), the AD Strategic Fund and the Alzheimer's Association (#ADSF-21-831376-C, #ADSF-21-831381-C, and #ADSF-21-831377-C), the Bluefield Project, the Olav Thon Foundation, the Erling-Persson Family Foundation, Stiftelsen för Gamla Tjänarinnor, Hjärnfonden, Sweden (#FO2022-0270), the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 860197 (MIRIADE), the European Union Joint Programme-Neurodegenerative Disease Research (JPND2021-00694), the National Institute for Health and Care Research University College London Hospitals Biomedical Research Centre, and the UK Dementia Research Institute at UCL (UKDRI-1003). RWP is supported by an Alzheimer's Association Clinician Scientist Fellowship AACSF-20-685780, the University College London Hospitals Biomedical Research Centre, and the UK Dementia Research Institute at UCL.

Informed Consent Statement

Informed consent was given by all participants in this study.

Data Availability Statement

Acknowledgments

We wish to thank the participants who contributed to this study and to Iceland Foods Ltd.

Conflicts of Interest

H.Z. has served at scientific advisory boards and/or as a consultant for Abbvie, Acumen, Alector, Alzinova, ALZPath, Annexon, Apellis, Artery Therapeutics, AZTherapies, Cognito Therapeutics, CogRx, Denali, Eisai, Nervgen, Novo Nordisk, Optoceutics, Passage Bio, Pinteon Therapeutics, Prothena, Red Abbey Labs, reMYND, Roche, Samumed, Siemens Healthineers, Triplet Therapeutics, and Wave, has given lectures in symposia sponsored by Cellectricon, Fujirebio, Alzecure, Biogen, and Roche, and is a co-founder of Brain Biomarker Solutions in Gothenburg AB (BBS), which is a part of the GU Ventures Incubator Program (outside submitted work). RWP is co-lead for the Neurofilament light consortium, and industry funded academic collaboration funded by Abbvie, Biogen, Bristol Myers Squibb and Roche.

References

1. Therriault, J.; Servaes, S.; Tissot, C.; Rahmouni, N.; Ashton, N.J.; Benedet, A.L.; Karikari, T.K.; Macedo, A.C.; Lussier, F.Z.; Stevenson, J. Equivalence of plasma p-tau217 with cerebrospinal fluid in the diagnosis of Alzheimer's disease. Alzheimer's Dement. 2023. [Google Scholar] [CrossRef]

2. Jchallqvist/mrmIntegrate. Available online: https://github.com/jchallqvist/mrmIntegrate (accessed on 4 April 2023).

3. Python. Available online: https://www.python.org/ (accessed on 18 June 2023).

Figure 1. Discovery urine proteomics of AD versus healthy age-matched controls. ( A) Volcano plot showing the nominally differentially expressed (p < 0.05) proteins in blue and non-significantly different proteins in red. Ingenuity pathway analyses of those proteins observed to have differential expression in the urine of AD patients versus normal, age-matched controls; ( B) Canonical pathway analysis demonstrating that significant differences are observed in lipid and cholesterol homeostasis which is a hallmark of AD; ( C) Disease and functional analyses clearly identifies that there is significant changes in biomarkers involved in amyloidosis and AD, indicating that proteins present in the urine identify underlying disease processes occurring in the brain.

Figure 2. Summary of the biomarker discovery experiment and the identification of those proteins to be put forward as evaluation as potential biomarkers capable of distinguishing AD from controls. Proteins identified with high confidence and amenable to tandem mass spectral analyses are shown as large green circles (downregulated in AD) and pink circles (upregulated in AD).

Figure 3. ( a) Identification of the five proteins that demonstrated significant elevation or were present in lower amounts in the urine of patients with a confirmed AD diagnosis (MIEN1, TNF-beta, VCAM1, REG1B and ABCA7). ( b) Univariate analyses of the two proteins most up- and down regulated, ABCA7 and MIEN1, respectively, with MIEN1 being statistically significantly elevated (p = 0.03). ( c) By looking at the ratio of the biomarkers ABAC7 and MIEN1 to one another, increases the statistical significance between AD and controls even further (p = 0.01). The whiskers show the minimum and maximum and the boxes show the 25th percentile, the median and the 75th percentile. Values outside 1.5 fold the interquartile are represented by dots. x represents the mean.

Figure 4. Figure showing the power of multilinear regression and multiplex biomarker panel analyses to increase accuracy and sensitivity of the test by using four biomarkers in addition to the best performing biomarker (MIEN1).

Figure 5. Methodology Workflow: shows methodology workflow for the discovery cohort protein analysis (stage 1) and the development of a high-throughput, multiplexed and targeted proteomic assay (stage 2).

Table 1. ( a): Demographics, cognitive profiles and cerebrospinal fluid biomarker profiles of the discovery cohort. Abbreviations: AD, Alzheimer's disease; MMSE, mini mental score exam; CSF, cerebrospinal fluid. All data are shown as the mean ± standard deviation unless otherwise stated. ( b): Demographics and cognitive profiles of the validation cohort. Abbreviations: AD, Alzheimer's disease. All data are shown as the mean ± standard deviation unless otherwise stated.

Hällqvist J, Pinto RC, Heywood WE, Cordey J, Foulkes AJM, Slattery CF, Leckey CA, Murphy EC, Zetterberg H, Schott JM, et al. A Multiplexed Urinary Biomarker Panel Has Potential for Alzheimer's Disease Diagnosis Using Targeted Proteomics and Machine Learning. International Journal of Molecular Sciences. 2023; 24(18):13758. https://doi.org/10.3390/ijms241813758

Chicago/Turabian Style

Hällqvist, Jenny, Rui C. Pinto, Wendy E. Heywood, Jonjo Cordey, Alexander J. M. Foulkes, Catherine F. Slattery, Claire A. Leckey, Eimear C. Murphy, Henrik Zetterberg, Jonathan M. Schott, and et al. 2023. "A Multiplexed Urinary Biomarker Panel Has Potential for Alzheimer's Disease Diagnosis Using Targeted Proteomics and Machine Learning" International Journal of Molecular Sciences 24, no. 18: 13758. https://doi.org/10.3390/ijms241813758

# data[].attributes.attachment_link.title
A Multiplexed Urinary Biomarker Panel Has Potential for Alzheimer's Disease Diagnosis Using Targeted Proteomics and Machine Learning

# data[].attributes.attachment_link.description
As disease-modifying therapies are now available for Alzheimer's disease (AD), accessible, accurate and affordable biomarkers to support diagnosis are urgently needed. We sought to develop a mass spectrometry-based urine test as a high-throughput screening tool for diagnosing AD.

# data[].attributes.headline
Transperineal laser ablation as a new minimally invasive surgical therapy for benign prostatic hyperplasia: a systematic review of existing literature

# data[].attributes.subject
Transperineal laser ablation as a new minimally invasive surgical therapy for benign prostatic hyperplasia: a systematic review of existing literature

# data[].attributes.attachment_link.title
Transperineal Laser Ablation for Benign Prostatic Enlargement: A Systematic Review and Pooled Analysis of Pilot Studies

# data[].attributes.attachment_link.description
Transperineal laser ablation (TPLA) of the prostate is a new minimally invasive treatment option in men with lower urinary tract symptoms (LUTS) due to benign prostatic enlargement (BPE). The aim of this systematic review was to investigate the efficacy and safety of TPLA in the management of BPE. T…

# data[].attributes.headline
Contemporary Considerations in the Evolution of Wearable Technology for Arrhythmia Detection

# data[].attributes.subject
Contemporary Considerations in the Evolution of Wearable Technology for Arrhythmia Detection

# data[].attributes.attachment_link.readable_text
Arrhythmias are an increasingly common cause of hospital admissions worldwide. Late detection of arrhythmias is associated with a significantly increased risk of cardiovascular complications. Early identification and management of life-threatening arrhythmias is paramount to reduce mortality. Wearable technologies are now widespread among the general population, providing a continuous output of healthcare data. However, this data are not routinely integrated into clinical practice. Here, we begin by outlining the current landscape in wearable technology for aiding arrhythmia detection; we then consider the clinical impact of wearable technology for both clinicians and patients; we further highlight the latest and emerging trials in wearable technology for arrhythmia detection and finally postulate the wider implications of the expansion of such cardiac devices.

Keywords: Arrhythmia, monitoring, wearables, technology, cardiovascular complications, cardiac devices.

# data[].attributes.attachment_link.keywords[]
contemporary considerations in the evolution of wearable technology
for arrhythmia detection

# data[].attributes.attachment_link.title
Contemporary Considerations in the Evolution of Wearable Technology for Arrhythmia Detection

# data[].attributes.attachment_link.description
Arrhythmias are an increasingly common cause of hospital admissions worldwide. Late detection of arrhythmias is associated with a significantly increased risk of cardiovascular complications. Early identification and management of life-threatening arrhythmias is paramount to reduce mortality. Wearable technologies are now widespread among the general population, providing a continuous output of healthcare data.

# data[].attributes.headline
Preventing the overdiagnosis of chest sepsis in children: A quality improvement project

# data[].attributes.subject
Preventing the overdiagnosis of chest sepsis in children: A quality improvement project

# data[].attributes.headline
Conference Abstract - 369 Should We Be Group and Save Testing for Laparoscopic General Surgical Procedures? a Retrospective Audit of Transfusion Rates at a District General Hospital 

# data[].attributes.subject
Conference Abstract - 369 Should We Be Group and Save Testing for Laparoscopic General Surgical Procedures? a Retrospective Audit of Transfusion Rates at a District General Hospital 

# data[].attributes.attachment_link.title
369 Should We Be Group and Save Testing for Laparoscopic General Surgical Procedures? a Retrospective Audit of Transfusion Rates at a District General Hospital

# data[].attributes.attachment_link.description
AbstractIntroduction. The risk of bleeding in surgery makes the requirement for transfusion a pertinent consideration for all clinical staff involved in the car

# data[].attributes.headline
Variability in the presentation of complicated jejunal diverticulosis

# data[].attributes.subject
Variability in the presentation of complicated jejunal diverticulosis

# data[].attributes.headline
Urinary bladder melanosis with complete resolution case report

# data[].attributes.subject
Urinary bladder melanosis with complete resolution case report

# data[].attributes.attachment_link.readable_text
Bladder melanosis is a rare condition that has been incidentally reported in a limited number of cases during cystoscopies performed for the investigation of LUTS [ 2]. Moreover, bladder melanosis associated with transitional cell carcinoma has been reported in less than 5 cases worldwide. Our case is unique because bladder melanosis was associated with low-grade TCC and had complete resolution within one year.

There have been four reported cases in the literature of patients diagnosed with bladder melanosis and urothelial carcinoma (Table 1). In three out of four reported cases, patients presented initially with haematuria [ 3, 4, 5]. In one case, the patient originally presented with recurrent UTI's, and was found to have bladder melanosis. She represented one year later with haematuria and was then found to have TCC [ 6].

Table 1 A table demonstrating the key features of patients who have been found to have concurrent melanosis and urothelial carcinoma

All patients had cystoscopy, which in all the cases demonstrated dark pigmentation. Four out of five cases, including our case, underwent a TURBT [ 3, 5, 6]. One patient underwent a laparoscopic nephroureterectomy as they were found to have a ureteric tumour [ 4]. Regarding follow-up, three out of five cases, including our case, had regular surveillance cystoscopy [ 4, 6].

To date, the clinical presentation of bladder melanosis has been non-specific, with symptoms varying from recurrent cystitis and dysuria, to more concerning symptoms like gross haematuria, acute renal failure, and palpable mass [ 5]. Due to the rarity of the condition, it is yet unknown whether any of these symptoms are caused by bladder melanosis or whether, in itself, bladder melanosis is asymptomatic and only incidentally reported in cystoscopies [ 7].

Bladder melanosis is reported during cystoscopies as a velvety appearance of the urothelium with brown-black deposits which can be found in any area of the bladder. Moreover, the lesions can be flat or can have a small punctate appearance [ 6]. It is paramount for biopsies of the lesions to be taken to rule out any other aetiologies for dark pigmentation. To date, bladder melanosis is considered to be a benign condition. However, as mentioned above, its presence has been reported in conjunction with malignant proliferation, either as a predecessor or simultaneous. Further research is needed to better understand bladder melanosis's true significance.

The presence of bladder melanosis is proven histopathologically with Fontana-Masson staining. The melanin granules have the capacity to reduce the ammoniacal silver nitrate, resulting in black appearance. Furthermore, adding strong oxidizing agents bleaches the specimen, confirming the presence of melanin [ 6].

The differential diagnosis includes malignant melanoma, which is distinguished by proliferation of melanocytes, which are positive for S-100 and HMB-45 (which would be negative in melanosis). As there is no proliferation of melanocytes, there is nothing to suggest that surveillance with cystoscopy follow-up would be of much benefit for melanosis. In our case, there was no evidence of melanin pigment in the bladder biopsy taken after one year.

Few theories have been proposed with regards to bladder melanosis formation, but the pathophysiological mechanism of the condition is still obscure. The bladder urothelium does not normally contain melanocytes. The question of how does the urothelium gain melanocytic cells has been raised. Most of the published reports assume that: 1. During embryological development, the melanocytes have an aberrant migration; 2. Local transdifferentiating of urothelial stem cells [ 8]. None of the above theories has a solid research background, making the validity of the proposals questionable. Furthermore, it has been proposed that bladder melanosis is the result of an abnormal reaction of the mucosal nerve plexus or resulted secondary to the plasticity of the urothelium [ 8]. Only one case reported the presence of melanosis after bladder Botox therapy but it is yet unknown whether the innervation of the bladder was the culprit [ 8].

# data[].attributes.attachment_link.title
Urinary bladder melanosis with complete resolution case report - African Journal of Urology

# data[].attributes.attachment_link.description
Background Melanosis of the bladder is a rare condition characterized by multifocal, diffuse melanin pigmentation of the urothelial mucosa or lamina propria without any proliferation of melanocytes. Less than 25 cases have been reported so far of which only four patients had concurrent urothelial carcinoma.

# data[].attributes.headline
Development of outcome measures for giant cell arteritis for use in clinical trials and standard practice

# data[].attributes.subject
Development of outcome measures for giant cell arteritis for use in clinical trials and standard practice

# data[].attributes.attachment_link.readable_text
Access options

Buy single article

Instant access to the full article PDF.

USD 39.95

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

References

1. Szekeres D, Al OB (2022) Current developments in the diagnosis and treatment of giant cell arteritis. Front Med 13(9):1066503. https://doi.org/10.3389/fmed.2022.1066503

Article Google Scholar

2. Rimland CA, Quinn KA, Rosenblum JS, Schwartz MN, Bates Gribbons K, Novakovich E, Sreih AG, Merkel PA, Ahlman MA, Grayson PC (2020) Outcome measures in large vessel vasculitis: relationship between patient-, physician-, imaging-, and laboratory-based assessments. Arthritis Care Res 72(9):1296-1304. https://doi.org/10.1002/acr.24117

Article Google Scholar

3. Saw SM, Ng TP (2001) The design and assessment of questionnaires in clinical research. Singap Med J 42(3):131-135

4. Carmines EG, Zeller RA (1979) Reliability and validity assessment (Vol. 17). Sage publications

5. Shi J, Mo X, Sun Z (2012) Content validity index in scale development. Zhong Na Da Xue Xue Bao Yi Xue Ban 37(2):152-155. https://doi.org/10.3969/j.issn.1672-7347.2012.02.007

Article Google Scholar

6. Park JR, Jones JG, Hazleman BL (1981) Relationship of the erythrocyte sedimentation rate to acute phase proteins in polymyalgia rheumatica and giant cell arteritis. Ann Rheum Dis 40:493-495. https://doi.org/10.1136/ard.40.5.493

7. Delecoeuillerie G, Joly P, Cohen de Lara A, Paolaggi JB (1988) Polymyalgia rheumatica and temporal arteritis: a retrospective analysis of prognostic features and different corticosteroid regimens (11 year survey of 210 patients). Ann Rheum Dis 47:733-739. https://doi.org/10.1136/ard.47.9.733

8. Kyle V, Cawston TE, Hazleman BL (1989) Erythrocyte sedimentation rate and C reactive protein in the assessment of polymyalgia rheumatica/giant cell arteritis on presentation and during follow up. Ann Rheum Dis 48:667-671. https://doi.org/10.1136/ard.48.8.667

9. Weyand CM, Fulbright JW, Hunder GG, Evans JM, Goronzy JJ (2000) Treatment of giant cell arteritis: interleukin-6 as a biologic marker of disease activity. Arthritis Rheum 43:1041-1048. https://doi.org/10.1002/1529-0131(200005)43:5<1041::AID-ANR12>3.0.CO;2-7

10. Dejaco C, Kerschbaumer A, Aletaha D, Bond M, Hysa E, Camellino D et al (2023) Treat-to-target recommendations in giant cell arteritis and polymyalgia rheumatica. Ann Rheum Dis:ard-2022-ar223429. https://doi.org/10.1136/ard-2022-223429

Download references

Acknowledgements

The authors acknowledge the kind cooperation and help of Miss. Sara Tousson Mohamed, Specialist librarian, Faculty of Medicine, Alexandria University, and Ms. Genny Franklin, Librarian, Darent Valley Hospital, Dartford, Kent, England, for their support in doing the review of the literature process.

Author information

Authors and Affiliations

1. Canterbury Christ Church University, Canterbury, England

Yasser El Miedany & Gillian Dolbear

2. King's College London, London, England

Yasser El Miedany & Mathias Toth

3. Ain Shams University, Cairo, Egypt

Maha Elgaafary & Sally Saber

4. Darent Valley Hospital, Kent, England

Mathias Toth & Dora Affam

5. Cairo University, Giza, Egypt

Atef Abdel Azim

6. North Middlesex University Hospital, London, England

Deborah Palmer

7. Tanta University, Tanta, Egypt

Mohamed Hassan Abu-zaid & Samar abdAlhamed Tabra

8. Benha University, Benha, Egypt

Waleed Hassan & Bassant Elnady

Contributions

All authors contributed in the study methodology, analysis, and interpretation of the data and outcomes as well as the manuscript writing, reading, and approval of the final version.

Corresponding author

Correspondence to Yasser El Miedany.

Ethics declarations

Ethics approval and consent to participate

Local ethical and methodological protocols for approval of the study were followed and accepted by the research ethical committee of Tanta University (approval number 36264PR45/1/23). All the participants were kept anonymous, in compliance with data protection regulations. Written informed consent from all participants was obtained in accordance with the local ethical committee.

Consent for publication

NA

Disclosures

None.

Additional information

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
Reprints and Permissions

About this article

Cite this article

El Miedany, Y., Elgaafary, M., Toth, M. et al. Development of outcome measures for giant cell arteritis for use in clinical trials and standard practice. Clin Rheumatol (2023). https://doi.org/10.1007/s10067-023-06704-7
Download citation

Get shareable link

Keywords

Disease activity

GCA

Giant cell arteritis

Outcome measures

Patient global assessment

Physician global assessment

Ultrasound

Validity

# data[].attributes.attachment_link.title
Development of outcome measures for giant cell arteritis for use in clinical trials and standard practice - Clinical Rheumatology

# data[].attributes.attachment_link.description
Background Developments in outcome measures in the rheumatic diseases are promoted by the development of successful treatments. Giant cell arteritis (GCA) is a multifaceted disorder and, therefore, measurement of multiple outcomes is relevant to this illness. It is a privilege to analyze and monitor/transfer long-term patients' management outcomes particularly if the same outcomes are used in practice and in trials.