Predictors of COVID‐19 severity: A literature review

Summary The coronavirus disease 2019 (COVID‐19) pandemic is a rapidly evolving global emergency that continues to strain healthcare systems. Emerging research describes a plethora of patient factors—including demographic, clinical, immunologic, hematological, biochemical, and radiographic findings—t...

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Bibliographic Details
Published in:Reviews in medical virology Vol. 31; no. 1; pp. 1 - 10
Main Authors: Gallo Marin, Benjamin, Aghagoli, Ghazal, Lavine, Katya, Yang, Lanbo, Siff, Emily J., Chiang, Silvia S., Salazar‐Mather, Thais P., Dumenco, Luba, Savaria, Michael C, Aung, Su N., Flanigan, Timothy, Michelow, Ian C.
Format: Journal Article
Language:English
Published: England Wiley Periodicals Inc 01.01.2021
Subjects:
Adult
Aging
Biomarkers
Child
Comorbidity
Computed tomography
Coronaviruses
COVID-19
COVID-19 - mortality
COVID-19 - pathology
COVID-19 - transmission
Humans
Hypoxia
Hypoxia - pathology
Literature reviews
Mortality
Pandemics
predictors
Prognosis
SARS-CoV-2 - pathogenicity
SARS‐CoV‐2
severity
Severity of Illness Index
COVID-19
predictors
severity
SARS-CoV-2
ISSN:1052-9276, 1099-1654, 1099-1654
Online Access:Get full text
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Description
Summary:Summary The coronavirus disease 2019 (COVID‐19) pandemic is a rapidly evolving global emergency that continues to strain healthcare systems. Emerging research describes a plethora of patient factors—including demographic, clinical, immunologic, hematological, biochemical, and radiographic findings—that may be of utility to clinicians to predict COVID‐19 severity and mortality. We present a synthesis of the current literature pertaining to factors predictive of COVID‐19 clinical course and outcomes. Findings associated with increased disease severity and/or mortality include age > 55 years, multiple pre‐existing comorbidities, hypoxia, specific computed tomography findings indicative of extensive lung involvement, diverse laboratory test abnormalities, and biomarkers of end‐organ dysfunction. Hypothesis‐driven research is critical to identify the key evidence‐based prognostic factors that will inform the design of intervention studies to improve the outcomes of patients with COVID‐19 and to appropriately allocate scarce resources.
Bibliography:Funding information
National Institute of Allergy and Infectious Diseases, Grant/Award Number: R25AI140490; National Institutes of Health
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AUTHOR CONTRIBUTIONS
Benjamin Gallo Marin contributed to the conception of the manuscript, drafted the manuscript, circulated for review, and revised the final manuscript. Ghazal Aghagoli contributed to the conception of the manuscript, drafted the manuscript, circulated for review, and revised and approved the final manuscript. Katya Lavine contributed to drafting, revising, and approving the final manuscript. Lanbo Yang contributed to drafting the manuscript and approved the final manuscript. Emily J. Siff, Silvia S. Chiang, Thais P. Salazar-Mather, Luba Dumenco, Michael C Savaria, Su N. Aung, Timothy Flanigan contributed to drafting the manuscript and revising and approving the final manuscript. Ian C. Michelow conceptualized, reviewed, and revised and approved the manuscript.
ISSN:1052-9276
1099-1654
1099-1654
DOI:10.1002/rmv.2146