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

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 t...

Cur síos iomlán

Sonraí bibleagrafaíochta
Príomhchruthaitheoirí: Millar, JE, Neyton, L, Seth, S, Dunning, J, Merson, L, Murthy, S, Russell, CD, Keating, S, Swets, M, Sudre, CH, Spector, TD, Ourselin, S, Steves, CJ, Wolf, J, Docherty, AB, Harrison, EM, Openshaw, PJM, Semple, MG, Baillie, JK
Rannpháirtithe: ISARIC-4C
Formáid: Journal article
Teanga:English
Foilsithe / Cruthaithe: Springer Nature 2022
_version_ 1826307671417946112
author Millar, JE
Neyton, L
Seth, S
Dunning, J
Merson, L
Murthy, S
Russell, CD
Keating, S
Swets, M
Sudre, CH
Spector, TD
Ourselin, S
Steves, CJ
Wolf, J
Docherty, AB
Harrison, EM
Openshaw, PJM
Semple, MG
Baillie, JK
author2 ISARIC-4C
author_facet ISARIC-4C
Millar, JE
Neyton, L
Seth, S
Dunning, J
Merson, L
Murthy, S
Russell, CD
Keating, S
Swets, M
Sudre, CH
Spector, TD
Ourselin, S
Steves, CJ
Wolf, J
Docherty, AB
Harrison, EM
Openshaw, PJM
Semple, MG
Baillie, JK
author_sort Millar, JE
collection OXFORD
description 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.
first_indexed 2024-03-07T07:06:39Z
format Journal article
id oxford-uuid:bba650b4-84a1-4310-ad7a-44f1fffd64d0
institution University of Oxford
language English
last_indexed 2024-03-07T07:06:39Z
publishDate 2022
publisher Springer Nature
record_format dspace
spelling oxford-uuid:bba650b4-84a1-4310-ad7a-44f1fffd64d02022-05-05T11:47:35ZDistinct clinical symptom patterns in patients hospitalised with COVID-19 in an analysis of 59,011 patients in the ISARIC-4C studyJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:bba650b4-84a1-4310-ad7a-44f1fffd64d0EnglishSymplectic ElementsSpringer Nature2022Millar, JENeyton, LSeth, SDunning, JMerson, LMurthy, SRussell, CDKeating, SSwets, MSudre, CHSpector, TDOurselin, SSteves, CJWolf, JDocherty, ABHarrison, EMOpenshaw, PJMSemple, MGBaillie, JKISARIC-4C 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.
spellingShingle Millar, JE
Neyton, L
Seth, S
Dunning, J
Merson, L
Murthy, S
Russell, CD
Keating, S
Swets, M
Sudre, CH
Spector, TD
Ourselin, S
Steves, CJ
Wolf, J
Docherty, AB
Harrison, EM
Openshaw, PJM
Semple, MG
Baillie, JK
Distinct clinical symptom patterns in patients hospitalised with COVID-19 in an analysis of 59,011 patients in the ISARIC-4C study
title Distinct clinical symptom patterns in patients hospitalised with COVID-19 in an analysis of 59,011 patients in the ISARIC-4C study
title_full Distinct clinical symptom patterns in patients hospitalised with COVID-19 in an analysis of 59,011 patients in the ISARIC-4C study
title_fullStr Distinct clinical symptom patterns in patients hospitalised with COVID-19 in an analysis of 59,011 patients in the ISARIC-4C study
title_full_unstemmed Distinct clinical symptom patterns in patients hospitalised with COVID-19 in an analysis of 59,011 patients in the ISARIC-4C study
title_short Distinct clinical symptom patterns in patients hospitalised with COVID-19 in an analysis of 59,011 patients in the ISARIC-4C study
title_sort distinct clinical symptom patterns in patients hospitalised with covid 19 in an analysis of 59 011 patients in the isaric 4c study
work_keys_str_mv AT millarje distinctclinicalsymptompatternsinpatientshospitalisedwithcovid19inananalysisof59011patientsintheisaric4cstudy
AT neytonl distinctclinicalsymptompatternsinpatientshospitalisedwithcovid19inananalysisof59011patientsintheisaric4cstudy
AT seths distinctclinicalsymptompatternsinpatientshospitalisedwithcovid19inananalysisof59011patientsintheisaric4cstudy
AT dunningj distinctclinicalsymptompatternsinpatientshospitalisedwithcovid19inananalysisof59011patientsintheisaric4cstudy
AT mersonl distinctclinicalsymptompatternsinpatientshospitalisedwithcovid19inananalysisof59011patientsintheisaric4cstudy
AT murthys distinctclinicalsymptompatternsinpatientshospitalisedwithcovid19inananalysisof59011patientsintheisaric4cstudy
AT russellcd distinctclinicalsymptompatternsinpatientshospitalisedwithcovid19inananalysisof59011patientsintheisaric4cstudy
AT keatings distinctclinicalsymptompatternsinpatientshospitalisedwithcovid19inananalysisof59011patientsintheisaric4cstudy
AT swetsm distinctclinicalsymptompatternsinpatientshospitalisedwithcovid19inananalysisof59011patientsintheisaric4cstudy
AT sudrech distinctclinicalsymptompatternsinpatientshospitalisedwithcovid19inananalysisof59011patientsintheisaric4cstudy
AT spectortd distinctclinicalsymptompatternsinpatientshospitalisedwithcovid19inananalysisof59011patientsintheisaric4cstudy
AT ourselins distinctclinicalsymptompatternsinpatientshospitalisedwithcovid19inananalysisof59011patientsintheisaric4cstudy
AT stevescj distinctclinicalsymptompatternsinpatientshospitalisedwithcovid19inananalysisof59011patientsintheisaric4cstudy
AT wolfj distinctclinicalsymptompatternsinpatientshospitalisedwithcovid19inananalysisof59011patientsintheisaric4cstudy
AT dochertyab distinctclinicalsymptompatternsinpatientshospitalisedwithcovid19inananalysisof59011patientsintheisaric4cstudy
AT harrisonem distinctclinicalsymptompatternsinpatientshospitalisedwithcovid19inananalysisof59011patientsintheisaric4cstudy
AT openshawpjm distinctclinicalsymptompatternsinpatientshospitalisedwithcovid19inananalysisof59011patientsintheisaric4cstudy
AT semplemg distinctclinicalsymptompatternsinpatientshospitalisedwithcovid19inananalysisof59011patientsintheisaric4cstudy
AT bailliejk distinctclinicalsymptompatternsinpatientshospitalisedwithcovid19inananalysisof59011patientsintheisaric4cstudy