Predictors of <scp>COVID</scp>‐19 severity: A literature review

Benjamin Gallo Marin(Brown University), Ghazal Aghagoli(Brown University), Katya Lavine(Brown University), Lanbo Yang(Brown University), Emily J. Siff(Brown University), Silvia S. Chiang(Rhode Island Department of Health), Thais P. Salazar‐Mather(Brown University), Luba Dumenco(Brown University), Michael C. Savaria(Brown University), Su Aung(Brown University), Timothy Flanigan(Brown University), Ian C. Michelow(Rhode Island Department of Health)
Reviews in Medical Virology
July 30, 2020
Cited by 876Open Access
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Abstract

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.


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