Statistical analysis
Continuous data were expressed as mean +/- standard deviation and compared using Student’s t -test, whilst categorical data were compared using either a Chi-square test or Fisher’s exact test. Variables found to be predictors on univariate analysis with a p value of < 0.05 were entered into a binary logistic multivariate regression model to determine their predictive independence. Accuracy of the multivariate model was determined by the coefficient of determination (R2- value) with a score closer to 1.0 indicating a superior model.
Receiver operating characteristic (ROC) curve analysis was used to generate the best cut-off for the newly derived parameters. Accuracy of the model was calculated by the area under the curve (AUC). Newly derived models were compared to existing ECG-morphology algorithms using the Youden index (sensitivity + specificity – 100), where a perfect test scores 100, and a score <50 indicates limited diagnostic utility. A p value of < 0.05 was considered statistically significant throughout. Data were analysed using IBM SPSS Statistics 27.0 software (SPSS, Inc., IL, USA).