Risk stratification and prognosis prediction using cardiac biomarkers in COVID-19: a single-centre retrospective

Madoka Sano1, Toshiaki Toyota2, Takeshi Morimoto3

  • 1Department of Cardiovascular Medicine, Kobe City Medical Center General Hospital, Kobe, Japan.

BMJ Open
|April 24, 2024
PubMed

Insights

Elevated cardiac biomarkers like hsTnI and NT-proBNP indicate a higher risk of death in COVID-19 patients. These markers can help stratify patient risk and guide clinical decisions for better outcomes.

Area of Science:

  • Cardiology
  • Infectious Diseases
  • Biomarkers

Background:

  • COVID-19 poses a significant risk, necessitating tools for patient risk stratification.
  • Cardiac biomarkers are increasingly recognized for their prognostic potential in various critical illnesses.

Purpose of the Study:

  • To evaluate the prognostic value of cardiac biomarkers in stratifying risk among hospitalized COVID-19 patients.
  • To assess the association between specific cardiac biomarkers and all-cause mortality in COVID-19.

Main Methods:

  • A retrospective cohort study included 917 COVID-19 patients.
  • Cardiac biomarkers including high-sensitive troponin I (hsTnI), N-terminal pro-B-type natriuretic peptide (NT-proBNP), creatine kinase (CK), and CK myocardial band (CK-MB) were measured.
  • Patients were stratified based on clinically relevant thresholds, and the primary outcome was 30-day all-cause death.

Main Results:

  • Elevated levels of hsTnI, NT-proBNP, CK, and CK-MB were significantly associated with increased 30-day cumulative incidence of all-cause death.
  • Specific thresholds for each biomarker demonstrated a dose-dependent relationship with mortality risk.
  • Adjusted analysis confirmed the significant association between cardiac biomarker elevation and increased risk of death.

Conclusions:

  • Elevation of cardiac biomarkers is a significant indicator of poor prognosis in COVID-19 patients.
  • Cardiac biomarkers can serve as valuable tools for risk stratification in COVID-19 management.
  • Further research may explore the integration of these biomarkers into clinical decision-making algorithms.
Abstract