Outcomes of European Society of Cardiology 0/1‐h algorithm with high‐sensitivity cardiac troponin T among patients with coronary artery disease

Author:

Rana Muhammad Omer Rehman1,Habib Aatika2,Sheikh Muhammad Abdullah Amir3,Ayub Shayan3,Zubair Rafia4,Rehman Ayesha5,Malik Jahanzeb6ORCID,Akhtar Waheed7,Awais Muhammad8

Affiliation:

1. Department of Interventional Cardiology Armed Forces Institute of Cardiology Rawalpindi Pakistan

2. Department of Cardiology Guy's and St. Thomas' NHS Trust London Pakistan

3. Department of Medicine King Edward Medical University Lahore Pakistan

4. Department of Medicine Gujranwala Medical College Gujranwala Pakistan

5. Department of Cardiology Armed Forces Institute of Cardiology Rawalpindi Pakistan

6. Department of Cardiovascular Medicine Cardiovascular Analytics Group Islamabad Pakistan

7. Department of Cardiology Abbas Institute of Medical Sciences Muzaffrabad Pakistan

8. Department of Cardiology Islamic International Medical College Rawalpindi Pakistan

Abstract

AbstractObjectiveThe 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.MethodsThis 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.ResultsThe 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.ConclusionThe 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.

Publisher

Wiley

Subject

Cardiology and Cardiovascular Medicine,Radiology, Nuclear Medicine and imaging,General Medicine

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