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

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.