Predictors of severity and mortality among patients hospitalized with COVID-19 in Rhode Island.

<h4>Background</h4>In order for healthcare systems to prepare for future waves of COVID-19, an in-depth understanding of clinical predictors is essential for efficient triage of hospitalized patients.<h4>Methods</h4>We performed a retrospective cohort study of 259 patients ad...

Full description

Bibliographic Details
Main Authors: Aakriti Pandita, Fizza S Gillani, Yiyun Shi, Anna Hardesty, Meghan McCarthy, Jad Aridi, Dimitrios Farmakiotis, Silvia S Chiang, Curt G Beckwith
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2021-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0252411
id doaj-db387c42f0754408bc0e2bc3e1edfeb3
record_format Article
spelling doaj-db387c42f0754408bc0e2bc3e1edfeb32021-07-15T04:30:39ZengPublic Library of Science (PLoS)PLoS ONE1932-62032021-01-01166e025241110.1371/journal.pone.0252411Predictors of severity and mortality among patients hospitalized with COVID-19 in Rhode Island.Aakriti PanditaFizza S GillaniYiyun ShiAnna HardestyMeghan McCarthyJad AridiDimitrios FarmakiotisSilvia S ChiangCurt G Beckwith<h4>Background</h4>In order for healthcare systems to prepare for future waves of COVID-19, an in-depth understanding of clinical predictors is essential for efficient triage of hospitalized patients.<h4>Methods</h4>We performed a retrospective cohort study of 259 patients admitted to our hospitals in Rhode Island to examine differences in baseline characteristics (demographics and comorbidities) as well as presenting symptoms, signs, labs, and imaging findings that predicted disease progression and in-hospital mortality.<h4>Results</h4>Patients with severe COVID-19 were more likely to be older (p = 0.02), Black (47.2% vs. 32.0%, p = 0.04), admitted from a nursing facility (33.0% vs. 17.9%, p = 0.006), have diabetes (53.9% vs. 30.4%, p<0.001), or have COPD (15.4% vs. 6.6%, p = 0.02). In multivariate regression, Black race (adjusted odds ratio [aOR] 2.0, 95% confidence interval [CI]: 1.1-3.9) and diabetes (aOR 2.2, 95%CI: 1.3-3.9) were independent predictors of severe disease, while older age (aOR 1.04, 95% CI: 1.01-1.07), admission from a nursing facility (aOR 2.7, 95% CI 1.1-6.7), and hematological co-morbidities predicted mortality (aOR 3.4, 95% CI 1.1-10.0). In the first 24 hours, respiratory symptoms (aOR 7.0, 95% CI: 1.4-34.1), hypoxia (aOR 19.9, 95% CI: 2.6-152.5), and hypotension (aOR 2.7, 95% CI) predicted progression to severe disease, while tachypnea (aOR 8.7, 95% CI: 1.1-71.7) and hypotension (aOR 9.0, 95% CI: 3.1-26.1) were associated with increased in-hospital mortality.<h4>Conclusions</h4>Certain patient characteristics and clinical features can help clinicians with early identification and triage of high-risk patients during subsequent waves of COVID-19.https://doi.org/10.1371/journal.pone.0252411
collection DOAJ
language English
format Article
sources DOAJ
author Aakriti Pandita
Fizza S Gillani
Yiyun Shi
Anna Hardesty
Meghan McCarthy
Jad Aridi
Dimitrios Farmakiotis
Silvia S Chiang
Curt G Beckwith
spellingShingle Aakriti Pandita
Fizza S Gillani
Yiyun Shi
Anna Hardesty
Meghan McCarthy
Jad Aridi
Dimitrios Farmakiotis
Silvia S Chiang
Curt G Beckwith
Predictors of severity and mortality among patients hospitalized with COVID-19 in Rhode Island.
PLoS ONE
author_facet Aakriti Pandita
Fizza S Gillani
Yiyun Shi
Anna Hardesty
Meghan McCarthy
Jad Aridi
Dimitrios Farmakiotis
Silvia S Chiang
Curt G Beckwith
author_sort Aakriti Pandita
title Predictors of severity and mortality among patients hospitalized with COVID-19 in Rhode Island.
title_short Predictors of severity and mortality among patients hospitalized with COVID-19 in Rhode Island.
title_full Predictors of severity and mortality among patients hospitalized with COVID-19 in Rhode Island.
title_fullStr Predictors of severity and mortality among patients hospitalized with COVID-19 in Rhode Island.
title_full_unstemmed Predictors of severity and mortality among patients hospitalized with COVID-19 in Rhode Island.
title_sort predictors of severity and mortality among patients hospitalized with covid-19 in rhode island.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2021-01-01
description <h4>Background</h4>In order for healthcare systems to prepare for future waves of COVID-19, an in-depth understanding of clinical predictors is essential for efficient triage of hospitalized patients.<h4>Methods</h4>We performed a retrospective cohort study of 259 patients admitted to our hospitals in Rhode Island to examine differences in baseline characteristics (demographics and comorbidities) as well as presenting symptoms, signs, labs, and imaging findings that predicted disease progression and in-hospital mortality.<h4>Results</h4>Patients with severe COVID-19 were more likely to be older (p = 0.02), Black (47.2% vs. 32.0%, p = 0.04), admitted from a nursing facility (33.0% vs. 17.9%, p = 0.006), have diabetes (53.9% vs. 30.4%, p<0.001), or have COPD (15.4% vs. 6.6%, p = 0.02). In multivariate regression, Black race (adjusted odds ratio [aOR] 2.0, 95% confidence interval [CI]: 1.1-3.9) and diabetes (aOR 2.2, 95%CI: 1.3-3.9) were independent predictors of severe disease, while older age (aOR 1.04, 95% CI: 1.01-1.07), admission from a nursing facility (aOR 2.7, 95% CI 1.1-6.7), and hematological co-morbidities predicted mortality (aOR 3.4, 95% CI 1.1-10.0). In the first 24 hours, respiratory symptoms (aOR 7.0, 95% CI: 1.4-34.1), hypoxia (aOR 19.9, 95% CI: 2.6-152.5), and hypotension (aOR 2.7, 95% CI) predicted progression to severe disease, while tachypnea (aOR 8.7, 95% CI: 1.1-71.7) and hypotension (aOR 9.0, 95% CI: 3.1-26.1) were associated with increased in-hospital mortality.<h4>Conclusions</h4>Certain patient characteristics and clinical features can help clinicians with early identification and triage of high-risk patients during subsequent waves of COVID-19.
url https://doi.org/10.1371/journal.pone.0252411
work_keys_str_mv AT aakritipandita predictorsofseverityandmortalityamongpatientshospitalizedwithcovid19inrhodeisland
AT fizzasgillani predictorsofseverityandmortalityamongpatientshospitalizedwithcovid19inrhodeisland
AT yiyunshi predictorsofseverityandmortalityamongpatientshospitalizedwithcovid19inrhodeisland
AT annahardesty predictorsofseverityandmortalityamongpatientshospitalizedwithcovid19inrhodeisland
AT meghanmccarthy predictorsofseverityandmortalityamongpatientshospitalizedwithcovid19inrhodeisland
AT jadaridi predictorsofseverityandmortalityamongpatientshospitalizedwithcovid19inrhodeisland
AT dimitriosfarmakiotis predictorsofseverityandmortalityamongpatientshospitalizedwithcovid19inrhodeisland
AT silviaschiang predictorsofseverityandmortalityamongpatientshospitalizedwithcovid19inrhodeisland
AT curtgbeckwith predictorsofseverityandmortalityamongpatientshospitalizedwithcovid19inrhodeisland
_version_ 1721301818065027072