Predictors of COVID-19 severity: A literature review.

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

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.