The Prognostic Ability of ECG Findings in Predicting Cardiovascular Events: A Five‐Year Nested Case—Cohort Study in an Iranian Population (Shiraz Heart Study)

Background and Aims: Electrocardiographic (ECG) markers may provide incremental prognostic value for cardiovascular disease (CVD) events beyond traditional ASCVD risk scores. This study aimed to evaluate the association between baseline ECG parameters and the incidence of cardiovascular events over 5 years in a nested case-control cohort. Methods: We analyzed 442 participants from the Shiraz Heart Study, including 221 individuals who experienced CVD events and 221 ASCVD risk-matched event-free controls. Detailed ECG parameters and clinical variables were evaluated. Multivariable logistic regression, including a prespecified 22-variable model and LASSO penalized regression, was used to identify independent ECG predictors. Model performance was assessed using bootstrap-corrected area under the curve (AUC). Results: = 0.036) remained independent predictors of incident CVD events in the prespecified 22-variable model, which was constructed based on clinical relevance and supported by univariable analyses. This model demonstrated excellent discrimination (bootstrap-corrected AUC 0.97, 95% CI 0.96-0.98). In the parsimonious four-variable LASSO model, ST-segment coving (OR 4.31, 95% CI 1.38-13.0) and PR interval (OR 0.977, 95% CI 0.961-0.992) remained independent predictors, and model performance remained robust (bootstrap-corrected AUC 0.96, 95% CI 0.94-0.98). Other ECG features, including prolonged QTc, abnormal R-wave progression, left ventricular hypertrophy, and T-wave inversions, were significant in univariable analyses but did not remain independent predictors in multivariable models. Conclusion: Baseline ECG parameters provide independent prognostic information for cardiovascular events beyond traditional ASCVD risk factors. These findings highlight the potential of ECG markers to enhance risk stratification, although external validation in larger and diverse populations is warranted before clinical implementation.