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Real-time prediction of COVID-19 related mortality using electronic health records.


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.

SUBMITTER: Schwab P 

PROVIDER: S-EPMC7886884 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Real-time prediction of COVID-19 related mortality using electronic health records.

Schwab Patrick P   Mehrjou Arash A   Parbhoo Sonali S   Celi Leo Anthony LA   Hetzel Jürgen J   Hofer Markus M   Schölkopf Bernhard B   Bauer Stefan S  

Nature communications 20210216 1


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  ...[more]

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