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Electrical Risk Score as a Predictor of Coronary Artery Disease
Özge Turgay Yıldırım1, Tuğba Dişikırık1, Gamze Yeter Arslan2
1Eskişehir City Health Application and Research Center, Health Sciences University, 26080 Eskişehir, Turkey.
Insights
The Electrical Risk Score (ERS), using ECG data, is linked to coronary artery disease (CAD) presence and severity. Elevated ERS may help predict and identify CAD early in stable patients.
Area of Science:
- Cardiology
- Medical Diagnostics
- Electrocardiography
Background:
- Coronary artery disease (CAD) is a major global cause of death.
- Effective risk stratification is crucial for managing CAD patients.
- The Electrical Risk Score (ERS) uses electrocardiogram (ECG) data but its link to CAD presence and severity needs clarification.
Purpose of the Study:
- To investigate the association between the Electrical Risk Score (ERS) and the presence and extent of CAD.
- To determine if ERS can serve as a non-invasive marker for CAD detection.
Main Methods:
- Retrospective analysis of 314 patients undergoing coronary angiography.
- Calculation of ERS based on six ECG parameters.
- Multivariate logistic regression analysis to assess independent associations.
Main Results:
- Mean ERS was significantly higher in patients with CAD compared to controls (p=0.006).
- Delayed QRS transition, prolonged QTc, and extended T peak-T end intervals were more common in the CAD group.
- ERS was independently associated with the presence of CAD (p<0.05).
Conclusions:
- The Electrical Risk Score (ERS) is significantly associated with CAD presence and severity.
- Elevated ERS, driven by specific ECG parameters, may aid in early CAD prediction and identification.
- ERS offers a potential non-invasive tool for risk stratification in stable patients.
Abstract:
Background/Objectives: Coronary artery disease (CAD) is a leading cause of global mortality, necessitating effective risk stratification tools for optimal patient management. The electrical risk score (ERS) is a multi-parametric index incorporating various electrocardiographic (ECG) parameters, previously shown to predict unfavorable cardiovascular outcomes. However, the relationship between ERS and the presence and severity of CAD remains unclear. This study aimed to investigate the association of ERS with the presence and extent of CAD as assessed by coronary angiography. Methods: This retrospective study included 314 consecutive patients who underwent coronary angiography. ERS was calculated using six ECG parameters: heart rate > 75 bpm, left ventricular hypertrophy, delayed QRS transition zone, frontal QRS-T angle > 90°, prolonged QTc interval, and extended T peak to T end interval. Results: Of the study population (mean age 57.8 ± 11.4, 61.5% male), 158 were diagnosed with CAD, and 156 constituted the control group. The mean ERS was significantly higher in the CAD group than the control group (2.34 ± 1.35 vs. 1.78 ± 1.12, p = 0.006). Among ERS components, delayed QRS transition (p = 0.023), prolonged QTc (p = 0.004), and extended T peak to T end interval (p = 0.001) were notably more prevalent in the CAD group. ERS was independently associated with the presence of CAD on multivariate logistic regression analysis (p < 0.05). Conclusions: ERS is significantly associated with the presence and severity of CAD in stable patients. Elevated ERS, particularly due to delayed QRS transition, prolonged QTc, and extended T peak to T end interval, may serve as a valuable, non-invasive marker for prediction and early identification of CAD.
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