Evaluation Of Cardiac Biomarkers For Early Diagnosis And Prognosis In Acute Myocardial Infarction: A Prospective Study

Abstract

Background: Acute myocardial infarction (AMI) is a leading cause of morbidity and mortality worldwide. Early and accurate diagnosis is crucial for effective management, and cardiac biomarkers play a significant role in this process. This study assesses the diagnostic and prognostic value of various cardiac biomarkers in AMI.

Objective: To evaluate the diagnostic accuracy and prognostic significance of cardiac biomarkers including high-sensitivity Troponin I (hs-cTnI), Creatine Kinase-MB (CK-MB), Heart-type Fatty Acid Binding Protein (H-FABP), Copeptin, and B-type Natriuretic Peptide (BNP) in patients with Acute Myocardial Infarction.

Methods: A prospective cohort study was conducted involving 100 patients with suspected AMI. Blood samples for biomarkers were collected at presentation, and at 6-, 12-, and 24-hours post-symptom onset. Diagnostic performance (sensitivity, specificity, positive predictive value, and negative predictive value) was assessed for each biomarker, along with prognostic implications, particularly for in-hospital mortality and major adverse cardiovascular events (MACE). Statistical analyses were performed using SPSS and R software.

Results: The study showed that hs-cTnI had the highest sensitivity (82%) at presentation, reaching peak sensitivity (96%) at 3-6 hours. A multimarker approach combining hs-cTnI and Copeptin demonstrated the highest sensitivity (98%) at 0-1 hour. Prognostic markers, particularly elevated ST2 and NT-proBNP levels, were associated with higher in-hospital mortality, heart failure, and arrhythmias. ST2 also showed significant predictive value for 30-day survival rates.

Conclusion: High-sensitivity Troponin I (hs-cTnI), particularly when combined with Copeptin, was the most reliable biomarker for early AMI diagnosis. Elevated ST2 and NT-proBNP levels were significant prognostic markers, identifying patients at high risk for adverse outcomes. This study highlights the utility of a multimarker approach to improve both diagnostic accuracy and prognostic prediction in AMI.