Real-time prediction of COVID-19 related mortality using electronic health records.
Nat Commun
; 12(1): 1058, 2021 02 16.
Article
in English
| MEDLINE | ID: covidwho-1087441
ABSTRACT
Coronavirus disease 2019 (COVID-19) is a respiratory disease with rapid human-to-human transmission caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Due to the exponential growth of infections, identifying patients with the highest mortality risk early is critical to enable effective intervention and prioritisation of care. Here, we present the COVID-19 early warning system (CovEWS), a risk scoring system for assessing COVID-19 related mortality risk that we developed using data amounting to a total of over 2863 years of observation time from a cohort of 66 430 patients seen at over 69 healthcare institutions. On an external cohort of 5005 patients, CovEWS predicts mortality from 78.8% (95% confidence interval [CI] 76.0, 84.7%) to 69.4% (95% CI 57.6, 75.2%) specificity at sensitivities greater than 95% between, respectively, 1 and 192 h prior to mortality events. CovEWS could enable earlier intervention, and may therefore help in preventing or mitigating COVID-19 related mortality.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Computer Systems
/
Electronic Health Records
/
COVID-19
Type of study:
Cohort study
/
Observational study
/
Prognostic study
Limits:
Humans
Language:
English
Journal:
Nat Commun
Journal subject:
Biology
/
Science
Year:
2021
Document Type:
Article
Affiliation country:
S41467-020-20816-7
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