COMPARISON OF HIGH-SENSITIVITY TROPONIN I AND T IN PREDICTING EARLY CARDIAC RISK IN ACUTE CORONARY SYNDROME

Abstract

Background: Acute Coronary Syndrome (ACS) is a major cause of morbidity and mortality in the world and risk stratification needs to be done quickly and accurately. High-sensitivity cardiac troponins, hs-cTnI and hs-cTnT, are important in the early diagnosis and prognostication but the relative effectiveness of the two in predicting early cardiac risk is not well understood especially in the local Pakistani population. Objective: The predictive validity of high-sensitivity Troponin I (hs-cTnI) versus Troponin T (hs-cTnT) in early cardiac risk stratification in patients presenting with ACS. Methodology: A potential observational study was carried out at Omer hospital and cardiac center Lahore, on 138 patients who came with ACS. The measurement of hs-cTnI and hs-cTnT in serial was performed at 0, 1, and 3 hours. Early cardiac risk was determined by in-hospital complications. ROC curve analysis, independent t-tests, and logistic regression that used SPSS-v27 were considered as statistical methods, and p < 0.05 was treated as significant. Results & Findings: No significant correlation was present between baseline clinical and demographic variables and early cardiac risk (p > 0.05), other than an association of prior myocardial infarction (p = 0.013). The dynamic changes in both biomarkers (03 hours hs-cTnI and 03 hours hs-cTnT) were significant in patients with early cardiac risk (p = 0.01 and 0.03, respectively). The predictor performance of Δ hs-cTnI (AUC = 0.63) was slightly better than that of Δ hs-cTnT (AUC = 0.60). In multivariate analysis, both of these biomarkers were predictors of early cardiac risk. Conclusion: High-sensitivity troponins dynamically change have been shown to be better predictors of early cardiac risk than baseline values, although hs-cTnI has a slight advantage over hs-cTnT, and should be used in combination with clinical and ECG data. This research offers important local information to assist better early risk stratification measures in ACS patients.