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Tran Nguyen Phuong Hai1, Nguyen Minh Kha2,3, Do Nguyen Tuong Dat2
1Department of Interventional Cardiology, Cho Ray Hospital, Ho Chi Minh City, Vietnam.
Insights
High-sensitivity cardiac troponin I (hs-cTnI) levels are inversely correlated with left ventricular ejection fraction (LVEF) in non-ST-elevation myocardial infarction (NSTEMI) patients. This biomarker helps predict left ventricular systolic dysfunction (LVSD), aiding early risk stratification and management.
Area of Science:
- Cardiology
- Biomarkers
- Diagnostic Medicine
Background:
- Cardiovascular diseases (CVDs), especially coronary artery disease (CAD), are leading causes of death globally, impacting both high-income and low-income nations.
- Acute myocardial infarction (AMI) significantly contributes to mortality and cardiovascular complications, particularly in patients with left ventricular systolic dysfunction (LVSD).
Purpose of the Study:
- To investigate the correlation between high-sensitivity cardiac troponin I (hs-cTnI) levels and left ventricular systolic dysfunction (LVSD) in patients with non-ST-elevation myocardial infarction (NSTEMI).
- To evaluate the predictive value of hs-cTnI for left ventricular ejection fraction (LVEF) in NSTEMI patients.
Main Methods:
- A descriptive, cross-sectional study involving 117 first-time NSTEMI patients.
- Measurement of admission hs-cTnI levels and assessment of LVEF via echocardiography.
- Receiver operating characteristic (ROC) curve analysis to determine the predictive value and optimal cut-off points of hs-cTnI for LVSD.
Main Results:
- A significant inverse correlation was observed between hs-cTnI levels and LVEF (r = -0.569, p < 0.001).
- Patients with moderate-to-severe LVSD (LVEF ≤ 40%) exhibited the highest median hs-cTnI levels (25,000 pg/mL).
- Optimal hs-cTnI cut-offs were identified for predicting LVEF < 50% (12,344 pg/mL) and LVEF ≤ 40% (20,979 pg/mL) with high accuracy.
Conclusions:
- Hs-cTnI is a reliable biomarker for predicting LVSD in NSTEMI patients.
- The inverse correlation between hs-cTnI and LVEF supports its use in risk stratification.
- Early identification of LVSD using hs-cTnI can inform management decisions for NSTEMI patients.
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.
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