SARS2 simplified scores to estimate risk of hospitalization and death among patients with COVID-19

Abstract Although models have been developed for predicting severity of COVID-19 from the medical history of patients, simplified models with good accuracy could be more practical. In this study, we examined utility of simpler models for estimating risk of hospitalization of patients with COVID-19 a...

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Autores principales:	Hesam Dashti, Elise C. Roche, David William Bates, Samia Mora, Olga Demler
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/6bbff66c1d6448228591636cfd44411a
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spelling	oai:doaj.org-article:6bbff66c1d6448228591636cfd44411a2021-12-02T11:37:26ZSARS2 simplified scores to estimate risk of hospitalization and death among patients with COVID-1910.1038/s41598-021-84603-02045-2322https://doaj.org/article/6bbff66c1d6448228591636cfd44411a2021-03-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-84603-0https://doaj.org/toc/2045-2322Abstract Although models have been developed for predicting severity of COVID-19 from the medical history of patients, simplified models with good accuracy could be more practical. In this study, we examined utility of simpler models for estimating risk of hospitalization of patients with COVID-19 and mortality of these patients based on demographic characteristics (sex, age, race, median household income based on zip code) and smoking status of 12,347 patients who tested positive at Mass General Brigham centers. The corresponding electronic records were queried (02/26–07/14/2020) to construct derivation and validation cohorts. The derivation cohort was used to fit generalized linear models for estimating risk of hospitalization within 30 days of COVID-19 diagnosis and mortality within approximately 3 months for the hospitalized patients. In the validation cohort, the model resulted in c-statistics of 0.77 [95% CI 0.73–0.80] for hospitalization, and 0.84 [95% CI 0.74–0.94] for mortality among hospitalized patients. Higher risk was associated with older age, male sex, Black ethnicity, lower socioeconomic status, and current/past smoking status. The models can be applied to predict the absolute risks of hospitalization and mortality, and could aid in individualizing the decision making when detailed medical history of patients is not readily available.Hesam DashtiElise C. RocheDavid William BatesSamia MoraOlga DemlerNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Hesam Dashti Elise C. Roche David William Bates Samia Mora Olga Demler SARS2 simplified scores to estimate risk of hospitalization and death among patients with COVID-19
description	Abstract Although models have been developed for predicting severity of COVID-19 from the medical history of patients, simplified models with good accuracy could be more practical. In this study, we examined utility of simpler models for estimating risk of hospitalization of patients with COVID-19 and mortality of these patients based on demographic characteristics (sex, age, race, median household income based on zip code) and smoking status of 12,347 patients who tested positive at Mass General Brigham centers. The corresponding electronic records were queried (02/26–07/14/2020) to construct derivation and validation cohorts. The derivation cohort was used to fit generalized linear models for estimating risk of hospitalization within 30 days of COVID-19 diagnosis and mortality within approximately 3 months for the hospitalized patients. In the validation cohort, the model resulted in c-statistics of 0.77 [95% CI 0.73–0.80] for hospitalization, and 0.84 [95% CI 0.74–0.94] for mortality among hospitalized patients. Higher risk was associated with older age, male sex, Black ethnicity, lower socioeconomic status, and current/past smoking status. The models can be applied to predict the absolute risks of hospitalization and mortality, and could aid in individualizing the decision making when detailed medical history of patients is not readily available.
format	article
author	Hesam Dashti Elise C. Roche David William Bates Samia Mora Olga Demler
author_facet	Hesam Dashti Elise C. Roche David William Bates Samia Mora Olga Demler
author_sort	Hesam Dashti
title	SARS2 simplified scores to estimate risk of hospitalization and death among patients with COVID-19
title_short	SARS2 simplified scores to estimate risk of hospitalization and death among patients with COVID-19
title_full	SARS2 simplified scores to estimate risk of hospitalization and death among patients with COVID-19
title_fullStr	SARS2 simplified scores to estimate risk of hospitalization and death among patients with COVID-19
title_full_unstemmed	SARS2 simplified scores to estimate risk of hospitalization and death among patients with COVID-19
title_sort	sars2 simplified scores to estimate risk of hospitalization and death among patients with covid-19
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/6bbff66c1d6448228591636cfd44411a
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SARS2 simplified scores to estimate risk of hospitalization and death among patients with COVID-19

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