The frontal QRS-T angle, derived from a standard 12-lead electrocardiogram (ECG), quantifies the relationship between ventricular depolarization and repolarization. Although a widened angle has been associated with myocardial disarray and arrhythmic risk, its diagnostic utility for detecting hypertrophic cardiomyopathy (HCM) in children, adolescents, and young adults has not been well established. We analyzed 6,128 participants aged ≤ 30 years from the Heartfelt community cardiovascular screening program. HCM was defined as septal or posterior wall thickness ≥ 2.5 SD above the mean for body-surface area in pediatric participants or ≥ 15 mm in adults. In a secondary analysis, the ≥ 15 mm threshold was applied irrespective of age. Electrocardiographic variables were evaluated using logistic regression and receiver operating characteristic (ROC) analyses. Among the 6,128 screened participants, 162 met criteria for HCM. Compared with unaffected individuals, participants with HCM were younger and had shorter PR intervals, QRS durations, and QTc values (all p < 0.001). The frontal QRS-T angle did not differ significantly between groups (23° [12-34] vs 24° [14-36]; p = 0.175) and demonstrated poor discriminatory performance (AUC 0.47; 95% CI 0.43-0.51). Findings were similar in the secondary analysis applying the ≥ 15 mm threshold across all ages (AUC 0.43; p = 0.67). In this large cohort of young community-screened participants, the frontal QRS-T angle did not distinguish individuals with hypertrophic cardiomyopathy. These findings suggest that adult-derived electrocardiographic thresholds may not be directly applicable to pediatric or athletic populations and highlight the need for age-specific ECG screening criteria.

The effects of community-acquired pneumonia (CAP) on cardiac electrophysiology have been described in children; however, their relationship with physiological circadian regulation remains unclear. This study aimed to evaluate morning-evening variations in electrocardiographic parameters in children with CAP compared to healthy controls. Thirty-six children diagnosed with CAP and 47 healthy controls were included. Electrocardiographic recordings were obtained in the morning and evening. Heart rate, atrial conduction parameters, and ventricular repolarization indices were analyzed to assess time effects, group differences, and time × group interactions. Children with CAP exhibited higher heart rates and shorter atrial conduction parameters than controls at both time points. Ventricular repolarization indices were increased in the pneumonia group. Tp-e/QT and Tp-e/QTc ratios were higher in children with CAP but did not show significant temporal variation. The frontal QRS-T angle demonstrated limited diurnal variation in healthy controls, whereas no significant temporal change was observed in the pneumonia group. Associations between Tp-e/QT, Tp-e/QTc, and QTc differed according to measurement time.Conclusion: Children with CAP demonstrate alterations in atrial conduction and ventricular repolarization compared with healthy peers. These findings suggest that CAP may be associated with temporal changes in specific electrophysiological relationships rather than a complete loss of physiological circadian regulation.

Introduction: Prolongation of the QT interval and QRS duration, which are markers of ventricular repolarization and depolarization, has been reported in patients receiving flecainide therapy. However, the effects of flecainide on the QRS-T angle-a recognized indicator of transmural dispersion of repolarization-remain unclear. The aim of our study was to investigate the impact of flecainide therapy on the QRS-T angle. Method: In this study, 200 patients who were prescribed flecainide therapy due to atrial or ventricular arrhythmias were included. Prior to the initiation of flecainide treatment, all patients underwent a 12-lead electrocardiogram (ECG) in which heart rate (HR), PR and QRS durations, QT, QTc, JT, Tp-Te intervals and the frontal plane QRS-T angle were measured. At the 1-month follow-up, patients underwent repeat ECG recording and were evaluated for both cardiac and non-cardiac side effects of flecainide. The same ECG parameters were measured again using the follow-up recordings. Changes in ECG parameters between the baseline and 1-month post-treatment were analyzed. Results: Following flecainide administration, the drug was discontinued in 18 patients (9%) due to adverse effects (11 cases of cardiac and seven cases of non-cardiac). HR significantly decreased (78 ± 22 bpm to 74 ± 15 bpm and p < 0.05). PR interval and QRS duration significantly increased (148 ± 23 ms to 156 ± 9 ms and 89 ± 17 ms to 99 ± 19 ms, respectively p < 0.05 for each). Additionally, JT interval (326 ± 27 ms vs. 334 ± 6 ms), QT interval (416 ± 24 ms vs. 434 ± 24 ms), QTc interval (431 ± 24 vs. 447 ± 25 ms) and Tp-Te interval (84 ± 17 vs. 87 ± 18 ms) all showed statistically significant increases after flecainide treatment (p < 0.05 for-each). However, no significant change was observed in the frontal QRS-T angle. Discussion: In patients receiving flecainide therapy for atrial and ventricular arrhythmias, prolongation was observed in atrioventricular conduction, ventricular depolarization and repolarization parameters as measured by ECG. However, no significant change was detected in the frontal QRS-T angle.

BACKGROUND: This study investigated the association between the Electrical Risk Score (ERS), derived from 12-lead electrocardiography (ECG), and electrocardiographic markers related to ventricular arrhythmia risk in patients with acute cholecystitis (AC), using conventional statistical analyses and machine learning–based exploratory analyses. Given the cross-sectional study design, clinical cardiovascular outcomes and longitudinal prognostic effects were not assessed. METHODS: In this prospective cross-sectional study, 153 patients diagnosed with AC and 100 age- and sex-matched healthy controls were enrolled. The ERS was calculated as the sum of six binary ECG parameters (range 0–6), and its individual components were compared between groups. The Tp–e interval (reflecting transmural dispersion of ventricular repolarization) and the frontal QRS–T angle (representing spatial heterogeneity between depolarization and repolarization vectors) were also analyzed. Six ensemble ML models including CatBoost and XGBoost were trained to estimate ERS variability using demographic, laboratory, and ECG variables. Model interpretation was performed using SHAP (Shapley Additive Explanations) analysis to improve transparency of model behavior. RESULTS: ERS was significantly higher in the AC group (2.1 ± 1.0) compared with controls (1.36 ± 0.71; p < 0.001). QT and QTc intervals, frontal QRS–T angle, and delayed QRS transition zone were significantly increased in AC patients. Laboratory markers including glucose, AST, ALT, hs-CRP, and WBC counts were also elevated in the AC group. Multivariate regression analysis identified AC, age, and AST as independent factors associated with ERS. Among ML models, CatBoost demonstrated the highest internal predictive performance for ERS estimation (R² = 0.9929, RMSE = 0.0578). Because ERS is derived from electrocardiographic parameters that were also included among model inputs, these predictive metrics should be interpreted cautiously. SHAP analysis indicated that heart rate, Tp–e interval, QTc interval, and frontal QRS–T angle were the most influential contributors to ERS estimation. Sensitivity analyses excluding ERS component variables suggested that systemic factors such as electrolyte balance and inflammatory markers may contribute to ERS variability, although their influence was weaker than that of electrophysiological parameters. Clinical endpoints such as arrhythmia, sudden cardiac death, or mortality were not evaluated. CONCLUSIONS: ERS values were significantly elevated in patients with AC and were associated with ECG markers reflecting ventricular repolarization heterogeneity. These findings indicate a cross-sectional electrophysiological association rather than evidence of prognostic utility. The integration of explainable ML techniques provided an interpretable exploratory framework for examining ERS variability, although no inference regarding prediction of future cardiovascular events can be drawn from the present data. Prospective longitudinal studies are required to determine whether ERS has independent clinical or prognostic relevance in this population.

BACKGROUND: Ischemic stroke (IS) remains a leading cause of death and disability worldwide. Stroke–heart syndrome, triggered by acute cerebral ischemia, causes autonomic dysfunction that can result in myocardial injury, arrhythmias, and sudden cardiac death, even in the absence of preexisting cardiac disease. The Electrical Risk Score (ERS), derived from standard electrocardiographic (ECG) parameters, has prognostic value in cardiac conditions, but its utility in IS populations remains unclear. This study aimed to evaluate the discriminative performance of ERS between confirmed acute IS patients and matched healthy controls, and to assess its prognostic value for 30-day all-cause mortality among patients with IS. METHODS: This prospective observational study enrolled 200 patients with acute IS and 101 age- and sex-matched healthy controls at a tertiary emergency department. ERS (range: 0–6) was calculated using six predefined ECG parameters: heart rate, QTc interval, Tp-e interval, frontal QRS-T angle, QRS transition zone, and left ventricular hypertrophy. RESULTS: ERS was significantly higher in IS patients compared to controls (p < 0.001). ERS independently predicted 30-day mortality (adjusted OR 1.66, 95% CI 1.14–2.42; p = 0.008). Receiver operating characteristic (ROC) analysis showed that ERS ≥ 3 discriminated confirmed IS cases from matched controls with 61% sensitivity and 77% specificity (AUC: 0.725; 95% CI: 0.669–0.781; PPV: 0.841; NPV: 0.500; p < 0.001). ERS ≥ 4 predicted 30-day mortality with 55% sensitivity and 74% specificity (AUC: 0.681; 95% CI: 0.585–0.778; PPV: 0.267; NPV: 0.907; p = 0.002). Higher ERS values showed a significant positive correlation with stroke severity based on Glasgow Coma Scale (GCS) scores (p = 0.005). CONCLUSION: ERS is a simple bedside ECG-based tool with moderate accuracy for predicting acute IS and short-term mortality. It may support early risk stratification in settings with limited stroke-specific resources. Further multicenter studies are needed for validation.