tetano
Editor, Senior Moderator
Nat Commun
. 2021 Feb 16;12(1):1058.
doi: 10.1038/s41467-020-20816-7.
Real-time prediction of COVID-19 related mortality using electronic health records
Patrick Schwab[SUP] 1 [/SUP], Arash Mehrjou[SUP] 2 3 [/SUP], Sonali Parbhoo[SUP] 4 [/SUP], Leo Anthony Celi[SUP] 5 6 [/SUP], J?rgen Hetzel[SUP] 7 8 [/SUP], Markus Hofer[SUP] 8 [/SUP], Bernhard Sch?lkopf[SUP] 2 3 [/SUP], Stefan Bauer[SUP] 2 9 [/SUP]
Affiliations
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.
. 2021 Feb 16;12(1):1058.
doi: 10.1038/s41467-020-20816-7.
Real-time prediction of COVID-19 related mortality using electronic health records
Patrick Schwab[SUP] 1 [/SUP], Arash Mehrjou[SUP] 2 3 [/SUP], Sonali Parbhoo[SUP] 4 [/SUP], Leo Anthony Celi[SUP] 5 6 [/SUP], J?rgen Hetzel[SUP] 7 8 [/SUP], Markus Hofer[SUP] 8 [/SUP], Bernhard Sch?lkopf[SUP] 2 3 [/SUP], Stefan Bauer[SUP] 2 9 [/SUP]
Affiliations
- PMID: 33594046
- DOI: 10.1038/s41467-020-20816-7
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.