Next-Generation AI-ECG Frameworks for Early Arrhythmia Identification and Stratified Prognostic Evaluation

Authors:
Publisher website
Google Scholar
Abstract
Recent developments in electrocardiographic signal analysis have redefined the diagnostic and prognostic landscape of cardiac arrhythmias. This review synthesizes current international evidence on advanced ECG-centered analytical strategies for early detection and risk stratification, incorporating studies published between 2021 and 2025 and contextualizing their applicability within healthcare systems in Mexico, Colombia, and Ecuador. The collective literature demonstrates that early identification of atrial fibrillation achieves consistently high diagnostic accuracy, supported by robust waveform characterization, rhythm-based modeling, and recognition of subtle conduction irregularities. Comparable approaches applied to supraventricular and ventricular arrhythmias also yield strong performance despite higher morphological variability. In contrast, prognostic assessment of ventricular instability and sudden cardiac death presents greater complexity; however, recent investigations highlight meaningful advances based on dynamic features such as beat-to-beat variability, QRS complexity, repolarization heterogeneity, and ectopic burden. Evidence further underscores the decisive impact of monitoring duration, with 7–14-day ambulatory patches markedly outperforming conventional ECG and short Holter recordings in detecting intermittent arrhythmic episodes. A multidimensional interpretive framework—integrating atrial conduction markers, repolarization indices, autonomic modulation, and electrical instability signatures—emerges as essential for achieving clinically relevant predictive performance. Finally, the review highlights expanding feasibility for regional adoption in Latin America, supported by progressive improvements in infrastructure, workflow integration, and clinical capacity. Overall, the findings reflect a pivotal transition toward enhanced ECG analysis as a central component of contemporary arrhythmia evaluation, with substantial implications for early diagnosis, risk prediction, and long-term patient outcomes.