OPTIMIZATION OF EARLY DETECTION ALGORITHMS FOR SUBCLINICAL ARRHYTHMOGENIC CONDITIONS IN MILITARY PERSONNEL BASED ON DIGITAL ELECTROCARDIOGRAPHIC SCREENING AND RISK STRATIFICATION OF SUDDEN CARDIAC EVENTS

Abstrak

Subclinical arrhythmogenic conditions are associated with an increased risk of sudden cardiac events in military personnel and often remain undetected during routine cardiovascular examinations. This study aimed to optimize early detection algorithms using digital electrocardiographic screening and integrated cardiovascular risk stratification. A prospective study was conducted between 2023 and 2025 involving 286 active-duty military personnel aged 18–45 years. All participants underwent digital 12-lead ECG screening, heart rate variability assessment, and clinical cardiovascular evaluation. Electrocardiographic abnormalities included ventricular ectopic activity, QT/QTc prolongation, fragmented QRS complexes, and conduction disturbances. Subclinical arrhythmogenic abnormalities were identified in 61 (21.3%) participants. Reduced heart rate variability was detected in 52 (18.2%) individuals and was significantly associated with elevated arrhythmogenic risk (p<0.001). The developed digital ECG algorithm demonstrated sensitivity of 90.2%, specificity of 86.4%, and ROC-AUC of 0.91. Digital electrocardiographic screening combined with integrated risk stratification demonstrates high diagnostic value for early detection of latent arrhythmogenic conditions and may improve preventive cardiovascular monitoring in military personnel.