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

Medicine and Health

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

P. Schwab, A. Mehjoo, et al.

Discover CovEWS, a groundbreaking risk scoring system that predicts COVID-19 mortality risk using electronic health records. Developed by a team of experts including Patrick Schwab, Arash Mehjoo, Sonali Parbhoo, and others, this innovative tool showcases exceptional predictive performance, allowing for timely interventions that could save lives.

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Playback language: English
Abstract
This study introduces CovEWS, a risk scoring system for predicting COVID-19 mortality risk using electronic health records (EHRs). Developed using data from over 66,430 patients across 69 healthcare institutions, CovEWS demonstrated high predictive performance (78.8% to 69.4% specificity at sensitivities >95%) up to 192 hours before mortality events. The system enables earlier intervention and may help mitigate COVID-19 mortality.
Publisher
Nature Communications
Published On
Feb 16, 2021
Authors
Patrick Schwab, Arash Mehjoo, Sonali Parbhoo, Leo Anthony Celi, Jürgen Hetzel, Markus Hofer, Bernhard Schölkopf, Stefan Bauer
Tags
COVID-19
mortality risk
electronic health records
predictive performance
intervention

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