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.
Several biologically plausible associations between individual single nucleotide polymorphisms and clinical outcomes were found. Our data also strongly suggest that combined pathway-based analysis may provide valuable prognostic markers of clinical outcomes.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.