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  5. Development and validation of the ISARIC 4C Deterioration model for adults hospitalised with COVID-19: a prospective cohort study
 
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Development and validation of the ISARIC 4C Deterioration model for adults hospitalised with COVID-19: a prospective cohort study
File(s)
ISARIC 4C Deterioration model.pdf (754.34 KB)
Published version
Author(s)
Gupta, RK
Harrison, EM
Ho, A
Docherty, AB
Knight, SR
more
Type
Journal Article
Abstract
Background
Prognostic models to predict the risk of clinical deterioration in acute COVID-19 cases are urgently required to inform clinical management decisions.

Methods
We developed and validated a multivariable logistic regression model for in-hospital clinical deterioration (defined as any requirement of ventilatory support or critical care, or death) among consecutively hospitalised adults with highly suspected or confirmed COVID-19 who were prospectively recruited to the International Severe Acute Respiratory and Emerging Infections Consortium Coronavirus Clinical Characterisation Consortium (ISARIC4C) study across 260 hospitals in England, Scotland, and Wales. Candidate predictors that were specified a priori were considered for inclusion in the model on the basis of previous prognostic scores and emerging literature describing routinely measured biomarkers associated with COVID-19 prognosis. We used internal–external cross-validation to evaluate discrimination, calibration, and clinical utility across eight National Health Service (NHS) regions in the development cohort. We further validated the final model in held-out data from an additional NHS region (London).

Findings
74 944 participants (recruited between Feb 6 and Aug 26, 2020) were included, of whom 31 924 (43·2%) of 73 948 with available outcomes met the composite clinical deterioration outcome. In internal–external cross-validation in the development cohort of 66 705 participants, the selected model (comprising 11 predictors routinely measured at the point of hospital admission) showed consistent discrimination, calibration, and clinical utility across all eight NHS regions. In held-out data from London (n=8239), the model showed a similarly consistent performance (C-statistic 0·77 [95% CI 0·76 to 0·78]; calibration-in-the-large 0·00 [–0·05 to 0·05]); calibration slope 0·96 [0·91 to 1·01]), and greater net benefit than any other reproducible prognostic model.

Interpretation
The 4C Deterioration model has strong potential for clinical utility and generalisability to predict clinical deterioration and inform decision making among adults hospitalised with COVID-19.

Funding
National Institute for Health Research (NIHR), UK Medical Research Council, Wellcome Trust, Department for International Development, Bill & Melinda Gates Foundation, EU Platform for European Preparedness Against (Re-)emerging Epidemics, NIHR Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections at University of Liverpool, NIHR HPRU in Respiratory Infections at Imperial College London.
Date Issued
2021-04-01
Date Acceptance
2021-01-01
Citation
The Lancet Respiratory Medicine, 2021, 9 (4), pp.349-359
URI
http://hdl.handle.net/10044/1/85694
URL
https://www.sciencedirect.com/science/article/pii/S2213260020305592
DOI
https://www.dx.doi.org/10.1016/S2213-2600(20)30559-2
ISSN
2213-2600
Publisher
Elsevier
Start Page
349
End Page
359
Journal / Book Title
The Lancet Respiratory Medicine
Volume
9
Issue
4
Copyright Statement
© 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.
License URL
http://creativecommons.org/licenses/by/4.0/
Sponsor
National Institute for Health Research
Commission of the European Communities
Medical Research Council (MRC)
National Institute for Health Research
UKRI MRC COVID-19 Rapid Response Call
UK Research and Innovation
UK Research and Innovation
Identifier
https://doi.org/10.1016/S2213-2600(20)30559-2
Grant Number
RDA06 79560
602525
PO 4050681719
NIHR201385
MC_PC19025
1257927
9815274 MC_PC_19025
Subjects
ISARIC4C Investigators
1103 Clinical Sciences
1117 Public Health and Health Services
1199 Other Medical and Health Sciences
Publication Status
Published
Date Publish Online
2021-01-11
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