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Cardiac biomarker-based risk stratification algorithm in patients with severe COVID-19
Kunal Mahajan1, Prakash Chand Negi1, Neeraj Ganju1
1Department of Cardiology, Indira Gandhi Medical College, Shimla, 171001, India.
Insights
An algorithmic approach using cardiac biomarkers can help manage patients with severe coronavirus disease 2019 (COVID-19). This method aids in risk stratification and prognostication, potentially reducing unnecessary tests and exposure risks.
Area of Science:
- Cardiology
- Infectious Diseases
- Biomarker Research
Background:
- Elevated cardiac biomarkers are common in coronavirus disease 2019 (COVID-19) patients.
- COVID-19 is linked to acute cardiac injury in 7-28% of cases, increasing mortality.
- Patients with pre-existing cardiovascular disease face higher risks of cardiac complications from COVID-19.
Purpose of the Study:
- To propose an algorithmic approach for using cardiac biomarkers in severe COVID-19 patients.
- To rationalize the use of cardiac biomarkers for triage, risk stratification, and prognostication.
- To potentially reduce unnecessary investigations and infection exposure for healthcare teams.
Main Methods:
- Systematic literature search of PubMed and Google Scholar databases up to May 31st, 2020.
- Review of available data on the role of cardiac biomarkers in COVID-19 patients.
- Development of an algorithmic approach for biomarker utilization in severe COVID-19.
Main Results:
- Cardiac biomarkers can help differentiate cardiac causes of dyspnea in severe COVID-19.
- Biomarkers support triaging, risk-stratification, and clinical decision-making.
- An algorithmic approach may prevent unnecessary downstream testing and reduce infection exposure.
Conclusions:
- Triage, risk-stratification, and prognostication of COVID-19 patients using cardiac biomarkers are beneficial.
- Evidence of myocardial injury and underlying cardiovascular disease are key factors.
- Further research is required to validate the proposed benefits of this algorithmic approach.
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.
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