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Predicting Need for Escalation of Care or Death From Repeated Daily Clinical Observations and Laboratory Results in Patients With Severe Acute Respiratory Syndrome Coronavirus 2

Crooks, Colin J.; West, Joe; Fogarty, Andrew; Morling, Joanne R.; Grainge, Matthew J.; Gonem, Sherif; Simmonds, Mark; Race, Andrea; Juurlink, Irene; Briggs, Steve; Cruickshank, Simon; Hammond-Pears, Susan; Card, Timothy R.

Predicting Need for Escalation of Care or Death From Repeated Daily Clinical Observations and Laboratory Results in Patients With Severe Acute Respiratory Syndrome Coronavirus 2 Thumbnail


Authors

JOE WEST JOE.WEST@NOTTINGHAM.AC.UK
Professor of Epidemiology

ANDREW FOGARTY ANDREW.FOGARTY@NOTTINGHAM.AC.UK
Clinical Associate Professor & Reader in Clinical Epidemiology

JOANNE MORLING JOANNE.MORLING@NOTTINGHAM.AC.UK
Clinical Associate Professor

Sherif Gonem

Mark Simmonds

Andrea Race

Irene Juurlink

Steve Briggs

Simon Cruickshank

Susan Hammond-Pears

Dr TIM CARD tim.card@nottingham.ac.uk
Clinical Associate Professor



Abstract

We compared the performance of prognostic tools for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using parameters fitted either at the time of hospital admission or across all time points of an admission. This cohort study used clinical data to model the dynamic change in prognosis of SARS-CoV-2 at a single hospital center in the United Kingdom, including all patients admitted from February 1, 2020, to December 31, 2020, and then followed up for 60 days for intensive care unit (ICU) admission, death, or discharge from the hospital. We incorporated clinical observations and blood tests into 2 time-varying Cox proportional hazards models predicting daily 24- to 48-hour risk of admission to the ICU for those eligible for escalation of care or death for those ineligible for escalation. In developing the model, 491 patients were eligible for ICU escalation and 769 were ineligible for escalation. Our model had good discrimination of daily risk of ICU admission in the validation cohort (n=1,141; C statistic: C=0.91, 95% confidence interval: 0.89, 0.94) and our score performed better than other scores (National Early Warning Score 2, International Severe Acute Respiratory and Emerging Infection Comprehensive Clinical Characterisation Collaboration score) calculated using only parameters measured on admission, but it overestimated the risk of escalation (calibration slope = 0.7). A bespoke daily SARS-CoV-2 escalation risk prediction score can predict the need for clinical escalation better than a generic early warning score or a single estimation of risk calculated at admission.

Citation

Crooks, C. J., West, J., Fogarty, A., Morling, J. R., Grainge, M. J., Gonem, S., …Card, T. R. (2022). Predicting Need for Escalation of Care or Death From Repeated Daily Clinical Observations and Laboratory Results in Patients With Severe Acute Respiratory Syndrome Coronavirus 2. American Journal of Epidemiology, 191(11), 1944-1953. https://doi.org/10.1093/aje/kwac126

Journal Article Type Article
Acceptance Date Jul 19, 2022
Online Publication Date Jul 22, 2022
Publication Date 2022-11
Deposit Date Mar 17, 2022
Publicly Available Date Mar 29, 2024
Journal American Journal of Epidemiology
Print ISSN 0002-9262
Electronic ISSN 1476-6256
Peer Reviewed Peer Reviewed
Volume 191
Issue 11
Pages 1944-1953
DOI https://doi.org/10.1093/aje/kwac126
Keywords Critical care, SARS-CoV-2, Covid-19, risk prediction, death
Public URL https://nottingham-repository.worktribe.com/output/7608690
Publisher URL https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac126/6648775?login=true

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