A Novel Electrocardiographic Index to Predict the Severity of Coronary Calcification

Electrocardiogram (ECG) remains an essential tool in cardiology. Coronary artery calcium (CAC) score, measured via computed tomography, is a well-established predictor of cardiovascular risk. However, its cost and availability limit widespread use. This study introduces a novel ECG-based index, the PARLA (Prediction of Ischemia via Angle of QRS-T and corrected QT Length Assessment) Index, combining the QTc interval and frontal QRS-T (fQRS-T) angle, to assess its association with CAC severity.

This retrospective, cross-sectional study included patients who underwent ECG and coronary computed tomography angiography. Exclusion criteria encompassed conduction abnormalities, significant valvular disease, cardiomyopathy, prior coronary interventions, and medications affecting ECG parameters. The PARLA Index was defined as the sum of the QTc interval and absolute fQRS-T angle. Patients were classified based on CAC score: <100 (low CAC score) vs. ≥100 (high CAC score). Statistical analyses, including logistic regression and receiver operating characteristic (ROC) curve analysis, assessed the predictive value of the PARLA Index for CAC severity.

Among 595 patients (mean age 53.4 ± 11.6 years, 39.5% female), the high-CAC group had older age, higher prevalence of hypertension and diabetes, and greater left ventricular wall thickness. The PARLA Index was significantly higher in the high-CAC group (440± 26 vs. 465 ± 37, P < .001). Multivariate regression identified the PARLA Index as an independent predictor of CAC ≥100 (OR: 1.021, P < .001). ROC analysis determined an optimal PARLA Index cut-off of 450 (AUC: 0.705, sensitivity: 63%, specificity: 66%).

The PARLA Index is a novel, simple ECG-derived parameter that correlates with CAC severity and may serve as a noninvasive tool for cardiovascular risk stratification. Future studies should validate its prognostic value.