Key result
The ESC 0/1-h Algorithm with hs-cTnT successfully stratified 3,534 CAD patients into Rule-Out (n=1,125) and Rule-In (n=2,409) groups with improved performance compared to Troponin T at presentation.
Why the study?
Outcomes and clinical implications of the ESC 0/1-h algorithm with hs-cTnT in the context of developing countries remain understudied.
Does the ESC 0/1-h Algorithm with hs-cTnT improve risk stratification compared to Troponin T at presentation in patients with CAD in a developing country?
Cohort (n=3,534)
Does the ESC 0/1-h Algorithm with hs-cTnT improve risk stratification compared to Troponin T at presentation in patients with CAD in a developing country?
The ESC 0/1-h algorithm with hs-cTnT effectively risk-stratifies patients with CAD in developing country settings, identifying high-risk patients for adverse events.
Answers are grounded in this paper and cite their sources.
Supports 0/1-h hs-cTnT algorithm for CAD stratification in developing countries; extends evidence but leaves open need for RCTs.
OBJECTIVE: The European Society of Cardiology (ESC) 0/1-h Algorithm with high-sensitivity cardiac troponin T (hs-cTnT) has shown promising results in risk stratification and management of patients with coronary artery disease (CAD). However, its outcomes and clinical implications in the context of developing countries remain understudied. METHODS: This cohort study aimed to evaluate the outcomes and clinical significance of the ESC 0/1-h Algorithm in a developing country setting. A total of 3534 patients with CAD were enrolled, with 1125 in the Rule-Out group and 2409 in the Rule-In group. Baseline characteristics, performance metrics, primary and secondary outcomes, and predictors of Rule-In and Rule-Out groups were assessed. RESULTS: The study enrolled 3534 patients with CAD, with 1125 in the Rule-Out group and 2409 in the Rule-In group. The 0/1-h Algorithm with hs-cTnT demonstrated improved performance compared to Troponin T at Presentation. It exhibited higher sensitivity, specificity, negative predictive value, positive predictive value, and area under the curve (AUC) for risk stratification in patients with CAD. Significant differences were observed in baseline characteristics between the Rule-Out and Rule-In groups, including age, gender, and comorbidities. The Rule-In group had a higher incidence of adverse cardiac events and underwent more invasive procedures compared to the Rule-Out group. Age, gender, hypertension, diabetes, and smoking were identified as significant predictors of Rule-In and Rule-Out. These findings highlight the clinical significance of implementing the 0/1-h Algorithm in the management of patients with CAD in a developing country setting. CONCLUSION: The algorithm's performance, along with its ability to identify high-risk patients and predict outcomes, highlights its potential to enhance patient care and outcomes in resource-limited settings.
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Rana et al. (2023) conducted a cohort in coronary artery disease (n=3,534). ESC 0/1-h Algorithm with high-sensitivity cardiac troponin T (hs-cTnT) vs. Troponin T at Presentation was evaluated on Risk stratification and adverse cardiac events. The ESC 0/1-h Algorithm with hs-cTnT successfully stratified 3,534 CAD patients into Rule-Out (n=1,125) and Rule-In (n=2,409) groups with improved performance compared to Troponin T at presentation.
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