Predictors of <scp>COVID</scp>‐19 severity: A literature review
Benjamin Gallo Marin, Ghazal Aghagoli, Katya Lavine, Lanbo Yang, Emily J. Siff, Silvia S. Chiang, Thais P. Salazar‐Mather, Luba Dumenco, Michael C. Savaria, Su Aung, Timothy Flanigan, Ian C. Michelow
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.