Evidence map›Paper›PMID 35478198›Full record

ArticleScientific reports2022

Distinct clinical symptom patterns in patients hospitalised with COVID-19 in an analysis of 59,011 patients in the ISARIC-4C study.

Jonathan E Millar, Lucile Neyton, Sohan Seth, Jake Dunning, Laura Merson, Srinivas Murthy, Clark D Russell, Sean Keating, Maaike Swets, Carole H Sudre and 10 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.0field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 16 citations in OpenAlex.

  1. Association of Cancer History with COVID-19 Risk and Outcomes among Older Postmenopausal Women: Results from the Women's Health Initiative.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2025
    Article
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  6. Association ofInterdisciplinary perspectives on infectious diseases · 2023
    Article
  7. Article
  8. Defining resistance and tolerance traits in Covid-19: towards a stratified medicine approach.QJM : monthly journal of the Association of Physicians · 2022
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

20 authors at 18 institutions in 3 countries.

Jonathan E MillarDivision of Functional Genetics and Development, Roslin Institute, University of Edinburgh, Easter Bush Campus, Midlothian, Edinburgh, EH25 9RG, UK.
Lucile NeytonDivision of Functional Genetics and Development, Roslin Institute, University of Edinburgh, Easter Bush Campus, Midlothian, Edinburgh, EH25 9RG, UK.
Sohan SethInstitute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh, Edinburgh, UK.
Jake DunningNational Infection Service, Public Health England, London, UK.
Laura MersonCentre for Tropical Medicine and Global Health, Nuffield Department of Medicine, ISARIC Global Support Centre, University of Oxford, Oxford, UK.
Srinivas MurthyBC Children's Hospital, University of British Columbia, Vancouver, Canada.
Clark D RussellCentre for Inflammation Research, The Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK.
Sean KeatingIntensive Care Unit, Royal Infirmary of Edinburgh, Edinburgh, UK.
Maaike SwetsDivision of Functional Genetics and Development, Roslin Institute, University of Edinburgh, Easter Bush Campus, Midlothian, Edinburgh, EH25 9RG, UK.
Carole H SudreSchool of Biomedical and Imaging Sciences, King's College London, London, UK.
Timothy D SpectorDepartment of Twin Research and Genetic Epidemiology, King's College London, London, UK.
Sebastien OurselinSchool of Biomedical and Imaging Sciences, King's College London, London, UK.
Claire J StevesDepartment of Twin Research and Genetic Epidemiology, King's College London, London, UK.
Jonathan WolfZOE Global Ltd, London, UK.
Annemarie B DochertyCentre for Medical Informatics, Usher Institute, University of Edinburgh, Edinburgh, UK.
Ewen M HarrisonCentre for Medical Informatics, Usher Institute, University of Edinburgh, Edinburgh, UK.
Peter J M OpenshawNational Heart and Lung Institute, Imperial College London, London, UK.
Malcolm G SempleNIHR Health Protection Research Unit in Emerging and Zoonotic Infections, Institute of Infection, Veterinary and Ecological Sciences, Faculty of Health and Life Sciences, University of Liverpool, Liverpool, UK. M.G.Semple@liverpool.ac.uk.
J Kenneth BaillieDivision of Functional Genetics and Development, Roslin Institute, University of Edinburgh, Easter Bush Campus, Midlothian, Edinburgh, EH25 9RG, UK. j.k.baillie@ed.ac.uk.
ISARIC-4C
Roslin Institute · GBUniversity of Liverpool · GBImperial College London · GBKing's College London · GBPublic Health England · GBCentre for Inflammation Research · GBUniversity of Edinburgh · GBUniversity of Oxford · GBCentre for Human Genetics · GBJohn Radcliffe Hospital · GBMRC University of Glasgow Centre for Virus Research · GBNottingham University Hospitals NHS Trust · GBUniversity of Cambridge · GBEdinburgh Royal Infirmary · GBLiverpool School of Tropical Medicine · GBUniversity of Birmingham · GBUniversity of British Columbia · CAZOE (United Kingdom) · GB

Funding

Medical Research Council MC_PC_19025Medical Research Council MC_PC_19059Medical Research Council MC_PC_20058Medical Research Council MR/S032304/1
6 · The paper itself

Abstract

COVID-19 is clinically characterised by fever, cough, and dyspnoea. Symptoms affecting other organ systems have been reported. However, it is the clinical associations of different patterns of symptoms which influence diagnostic and therapeutic decision-making. In this study, we applied clustering techniques to a large prospective cohort of hospitalised patients with COVID-19 to identify clinically meaningful sub-phenotypes. We obtained structured clinical data on 59,011 patients in the UK (the ISARIC Coronavirus Clinical Characterisation Consortium, 4C) and used a principled, unsupervised clustering approach to partition the first 25,477 cases according to symptoms reported at recruitment. We validated our findings in a second group of 33,534 cases recruited to ISARIC-4C, and in 4,445 cases recruited to a separate study of community cases. Unsupervised clustering identified distinct sub-phenotypes. First, a core symptom set of fever, cough, and dyspnoea, which co-occurred with additional symptoms in three further patterns: fatigue and confusion, diarrhoea and vomiting, or productive cough. Presentations with a single reported symptom of dyspnoea or confusion were also identified, alongside a sub-phenotype of patients reporting few or no symptoms. Patients presenting with gastrointestinal symptoms were more commonly female, had a longer duration of symptoms before presentation, and had lower 30-day mortality. Patients presenting with confusion, with or without core symptoms, were older and had a higher unadjusted mortality. Symptom sub-phenotypes were highly consistent in replication analysis within the ISARIC-4C study. Similar patterns were externally verified in patients from a study of self-reported symptoms of mild disease. The large scale of the ISARIC-4C study enabled robust, granular discovery and replication. Clinical interpretation is necessary to determine which of these observations have practical utility. We propose that four sub-phenotypes are usefully distinct from the core symptom group: gastro-intestinal disease, productive cough, confusion, and pauci-symptomatic presentations. Importantly, each is associated with an in-hospital mortality which differs from that of patients with core symptoms.

Indexed as

COVID-19ConfusionCoughDyspneaFatigueFemaleFeverHumansProspective Studies

Identifiers

PMID35478198
PMCPMC9043502
OpenAlexW4224943602

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.