Predictive Value of High-Sensitivity Troponin I for Left Ventricular Ejection Fraction in Patients with Non-ST-Elevation Myocardial Infarction.

Abstract

Background: According to the World Health Organization's 2021 statistics, cardiovascular diseases (CVDs), particularly coronary artery disease (CAD), remain among the leading causes of global morbidity and mortality, affecting both high-income and low-income countries like Vietnam.

Objective: Acute myocardial infarction (AMI) remains a major cause of mortality and cardiovascular complications, with a poor prognosis in patients with left ventricular systolic dysfunction (LVSD). High-sensitivity cardiac troponin I (hs-cTnI) is a specific biomarker of myocardial injury linked to infarct size and LVSD. However, its role in predicting left ventricular ejection fraction (LVEF) in non-ST-elevation myocardial infarction (NSTEMI) is underexplored. This study investigates the correlation between hs-cTnI and LVSD in NSTEMI patients.

Methods: A descriptive, cross-sectional study was conducted on 117 patients with first-time NSTEMI treated at Cho Ray Hospital from February 2024 to April 2024. Admission hs-cTnI levels were measured and correlated with LVEF, assessed via echocardiography. The predictive value and optimal cut-off points of hs-cTnI for LVSD (LVEF < 50% and ≤ 40%) were determined using receiver operating characteristic (ROC) curve analysis.

Results: Hs-cTnI levels showed a significant inverse correlation with LVEF (r = - 0.569, p < 0.001). Patients with moderate-to-severe LVSD (LVEF ≤ 40%) had the highest median hs-cTnI levels (25,000 pg/mL, p < 0.001). The area under the ROC curve (AUC) for predicting LVEF < 50% was 0.78, with a cut-off of 12,344 pg/mL (sensitivity 68.5%, specificity 82.5%). For LVEF ≤ 40%, the AUC was 0.82, with a cut-off of 20,979 pg/mL (sensitivity 73.3%, specificity 88.5%, accuracy 84.6%). These findings underscore hs-cTnI's utility in identifying LVSD.

Conclusion: Hs-cTnI is inversely correlated with LVEF and serves as a reliable biomarker for predicting LVSD in NSTEMI patients, facilitating risk stratification and early management decisions.