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Akademický článek
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Autor:
King, Joseph T, Yoon, James S, Bredl, Zachary M, Habboushe, Joseph P, Walker, Graham A, Rentsch, Christopher T, Tate, Janet P, Kashyap, Nitu M, Hintz, Richard C, Chopra, Aneesh P, Justice, Amy C
BACKGROUND: The Veterans Health Administration COVID-19 (VACO) Index predicts 30-day all-cause mortality in patients with COVID-19 using age, sex and pre-existing comorbidity diagnoses. The VACO Index was initially developed and validated in a nation
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=core_ac_uk__::aa9130bf88ae26381bc57d6f02b4169c
https://researchonline.lshtm.ac.uk/id/eprint/4662857/7/King_etal_2021_Accuracy-of-the-veterans-health.pdf
https://researchonline.lshtm.ac.uk/id/eprint/4662857/7/King_etal_2021_Accuracy-of-the-veterans-health.pdf
Autor:
King, Joseph T, Yoon, James S, Bredl, Zachary M, Habboushe, Joseph P, Walker, Graham A, Rentsch, Christopher T, Tate, Janet P, Kashyap, Nitu M, Hintz, Richard C, Chopra, Aneesh P, Justice, Amy C
Publikováno v:
MedRxiv
BackgroundThe Veterans Health Administration COVID-19 (VACO) Index incorporates age, sex, and pre-existing comorbidity diagnoses readily available in the electronic health record (EHR) to predict 30-day all-cause mortality in both inpatients and outp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=core_ac_uk__::3e42900303780765719fb802a1204d95
https://researchonline.lshtm.ac.uk/id/eprint/4659116/1/2021.01.01.20249069v1.full.pdf
https://researchonline.lshtm.ac.uk/id/eprint/4659116/1/2021.01.01.20249069v1.full.pdf