Predictive value of combined electrocardiographic and echocardiographic parameters for major adverse cardiovascular events in patients with established coronary artery disease: a single-center retrospective cohort study
Objective To explore the predictive value of combining conventional ECG parameters (P-wave dispersion, Sokolow-Lyon voltage) and echocardiographic parameters (left atrial volume index, LAVI) for major adverse cardiovascular events (MACE) in coronary artery disease (CAD) patients. Methods From January 2024 to February 2026, 306 angiographically confirmed CAD patients were enrolled. All underwent standard 12-lead ECG and transthoracic echocardiography at admission. Over a median follow-up of 15.2 months, 50 patients developed MACE and 256 remained event-free. Baseline ECG (P-wave dispersion, QTc, Sokolow-Lyon voltage) and echocardiographic parameters (LAVI, left ventricular ejection fraction, left ventricular mass index) were compared. Independent predictors were identified by multivariate Cox regression, and a combined model was built. Incremental value was assessed by C-index, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). The study was approved by the institutional review board. Results The MACE group had higher P-wave dispersion, LAVI, and left ventricular mass index, and lower Sokolow-Lyon voltage and LVEF (all p < 0.05). After multivariate adjustment, increased P-wave dispersion and greater LAVI were independent predictors of MACE (both p < 0.05). The combination model (P-wave dispersion + LAVI) significantly outperformed the basic clinical model (age, sex, diabetes, prior MI, eGFR) in risk discrimination (C-index, NRI, IDI all p < 0.05). Sensitivity analyses confirmed robustness. Conclusion Routinely available ECG-derived P-wave dispersion and echocardiographic LAVI are independent, complementary predictors of MACE in CAD patients. Integrating these two parameters into a simple risk model significantly enhances risk discrimination and reclassification, providing a practical, cost-effective tool for individualized management.