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Risk stratification of patients admitted to hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: development and validation of the 4C Mortality Score

Stephen R KnightCentre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UKAntonia HoDepartment of Infectious Diseases, Queen Elizabeth University Hospital, Glasgow, UKRiinu PiusCentre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UKIain BuchanInstitute of Population Health Sciences, University of Liverpool, Liverpool, UKGail CarsonISARIC Global Support Centre, Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UKThomas M DrakeCentre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UKJake DunningNational Heart and Lung Institute, Imperial College London, London, UKCameron J FairfieldCentre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UKCarrol GambleLiverpool Clinical Trials Centre, University of Liverpool, Liverpool, UKChristopher GreenInstitute of Microbiology & Infection, University of Birmingham, Birmingham, UKRishi K GuptaInstitute of Global Health, University College London, London, UKSophie HalpinLiverpool Clinical Trials Centre, University of Liverpool, Liverpool, UKHayley HardwickNIHR Health Protection Research Unit, Institute of Infection, Veterinary and Ecological Sciences, Faculty of Health and Life Sciences, University of Liverpool, Liverpool, UKKarl HoldenNIHR Health Protection Research Unit, Institute of Infection, Veterinary and Ecological Sciences, Faculty of Health and Life Sciences, University of Liverpool, Liverpool, UKPeter HorbyISARIC Global Support Centre, Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UKClare JacksonLiverpool Clinical Trials Centre, University of Liverpool, Liverpool, UKKenneth A McLeanCentre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UKLaura MersonISARIC Global Support Centre, Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UKJonathan S. Nguyen‐Van‐TamDivision of Epidemiology and Public Health, University of Nottingham School of Medicine, Nottingham, UKLisa NormanCentre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UKMahdad NoursadeghiDivision of Infection and Immunity, University College London, London, UKPiero OlliaroCentre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UKMark G. PritchardCentre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UKClark D RussellQueen's Medical Research Institute, University of Edinburgh, Edinburgh, UKCatherine A. ShawCentre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UKAziz SheikhCentre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UKTom SolomonNIHR Health Protection Research Unit, Institute of Infection, Veterinary and Ecological Sciences, Faculty of Health and Life Sciences, University of Liverpool, Liverpool, UKCathie SudlowHealth Data Research UK, London, UKOlivia SwannDepartment of Child Life and Health, University of Edinburgh, Edinburgh, UKLance TurtleNIHR Health Protection Research Unit, Institute of Infection, Veterinary and Ecological Sciences, Faculty of Health and Life Sciences, University of Liverpool, Liverpool, UKPeter OpenshawNational Heart and Lung Institute, Imperial College London, London, UKJ. Kenneth BaillieIntensive Care Unit, Royal Infirmary Edinburgh, Edinburgh, UKMalcolm G. SempleNIHR Health Protection Research Unit, Institute of Infection, Veterinary and Ecological Sciences, Faculty of Health and Life Sciences, University of Liverpool, Liverpool, UK [email protected]Annemarie B DochertyCentre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UKEwen M. HarrisonCentre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK

2020en

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Abstract Objective To develop and validate a pragmatic risk score to predict mortality in patients admitted to hospital with coronavirus disease 2019 (covid-19). Design Prospective observational cohort study. Setting International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) World Health Organization (WHO) Clinical Characterisation Protocol UK (CCP-UK) study (performed by the ISARIC Coronavirus Clinical Characterisation Consortium—ISARIC-4C) in 260 hospitals across England, Scotland, and Wales. Model training was performed on a cohort of patients recruited between 6 February and 20 May 2020, with validation conducted on a second cohort of patients recruited after model development between 21 May and 29 June 2020 . Participants Adults (age ≥18 years) admitted to hospital with covid-19 at least four weeks before final data extraction. Main outcome measure In-hospital mortality. Results 35 463 patients were included in the derivation dataset (mortality rate 32.2%) and 22 361 in the validation dataset (mortality rate 30.1%). The final 4C Mortality Score included eight variables readily available at initial hospital assessment: age, sex, number of comorbidities, respiratory rate, peripheral oxygen saturation, level of consciousness, urea level, and C reactive protein (score range 0-21 points). The 4C Score showed high discrimination for mortality (derivation cohort: area under the receiver operating characteristic curve 0.79, 95% confidence interval 0.78 to 0.79; validation cohort: 0.77, 0.76 to 0.77) with excellent calibration (validation: calibration-in-the-large=0, slope=1.0). Patients with a score of at least 15 (n=4158, 19%) had a 62% mortality (positive predictive value 62%) compared with 1% mortality for those with a score of 3 or less (n=1650, 7%; negative predictive value 99%). Discriminatory performance was higher than 15 pre-existing risk stratification scores (area under the receiver operating characteristic curve range 0.61-0.76), with scores developed in other covid-19 cohorts often performing poorly (range 0.63-0.73). Conclusions An easy-to-use risk stratification score has been developed and validated based on commonly available parameters at hospital presentation. The 4C Mortality Score outperformed existing scores, showed utility to directly inform clinical decision making, and can be used to stratify patients admitted to hospital with covid-19 into different management groups. The score should be further validated to determine its applicability in other populations. Study registration ISRCTN66726260

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DOI: 10.1136/bmj.m3339

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