Cardiac biomarker-based risk stratification algorithm in patients with severe COVID-19

Abstract
Background and aims
Cardiac biomarkers like cardiac troponins and natriuretic peptides are elevated in a substantial proportion of patients with coronavirus disease 2019 (COVID-19). We propose an algorithmic approach using cardiac biomarkers to triage, risk-stratify and prognosticate patients with severe COVID-19.
Methods
We systematically searched the PubMed and Google Scholar databases until May 31st, 2020, and accessed the available data on the role of cardiac biomarkers in patients with COVID-19.
Results
COVID-19 is associated with acute cardiac injury in around 7–28% of patients, significantly increasing its associated complications and mortality. Patients with underlying cardiovascular disease are more prone to develop acute cardiac injury as a result of COVID-19. The use of cardiac biomarkers may aid in differentiating the cardiac cause of dyspnea in patients with severe COVID-19. Cardiac biomarkers may also aid in triaging, risk-stratification, clinical decision-making, and prognostication of patients with COVID-19. However, there are concerns that routine testing in all patients with COVID-19 irrespective of severity, may result in unnecessary downstream investigations which may be misleading. In this brief review, using an algorithmic approach, we have tried to rationalize the use of cardiac biomarkers among patients with severe COVID-19. This approach is also likely to lessen the infection exposure risk to the cardiovascular team attending patients with severe COVID-19.
Conclusion
It appears beneficial to triage, risk-stratify, and prognosticate patients with COVID-19 based on the evidence of myocardial injury and the presence of underlying cardiovascular disease. Future research studies are, however, needed to validate these proposed benefits.