Dear members and friends of the ESC WG on e-Cardiology,

Welcome to the third editorial of the Working Group (WG) on e-Cardiology on four selected groundbreaking and impactful papers in the field of e-cardiology. 

The first paper by Johnson et al. in Nature Medicine explores the role of AI in the automated interpretation of long-term ambulatory ECG recordings — a topic of growing relevance as lower-cost devices and direct-to-consumer technologies increase workloads for ECG technicians. The study compared AI-based critical rhythm annotation (ventricular tachycardia, atrial fibrillation, supraventricular tachycardia, asystole, and third-degree AV block) with manual annotation by human experts. The AI model demonstrated high sensitivity (98.6%) compared to technicians (80.3%), with fewer false negatives (3.2 vs. 44.3 per 1,000 patients). However, it exhibited a higher false-positive rate (12 vs. 5 per 1,000 patient-days). Whether these promising results hold across different Holter ECG systems remains to be determined.

The second selected paper by De Coster et al published in Europace reviews the evolution of electrocardiography from a diagnostic tool to a therapeutic modality. The authors provide an insightful overview of optogenetics, a novel approach that uses genetically modified light-sensitive proteins to control cardiac bioelectricity. This method enables precise, non-invasive modulation of arrhythmic activity, representing a paradigm shift in arrhythmia treatment. While challenges remain, optogenetics could significantly advance personalized cardiac therapies.

The third paper by Nishihara et al. published in the European Heart Journal - Digital Health, introduces a novel strategy for early heart failure detection and management using deep learning and multi-point ECG analysis. By identifying subtle electrocardiographic changes, the AI model enhances diagnostic accuracy, offering potential for real-time monitoring and personalized interventions. As artificial intelligence continues to transform cardiovascular medicine, this study underscores its role in optimizing heart failure management and improving patient outcomes.

Finally, Monika Gawalko provides insights into a highly anticipated clinical study by Deisenhöfer et al. investigating the value of individualized lesion sets in patients with persistent AF. This multicenter trial demonstrates that AI-guided ablation targeting spatio-temporal dispersion areas, in addition to PVI, significantly improves AF-free survival at one year compared to PVI alone in patients with persistent AF. While long-term rhythm maintenance may require additional interventions, these findings highlight the potential of AI-driven precision ablation to enhance treatment outcomes in complex AF cases.

We wish the reader an enjoyable and stimulating time exploring the selected manuscripts.

On behalf of the entire ESC WG on e-Cardiology,
Sven Knecht, DSc,
Nucleus member of the ESC WG on e-Cardiology 2024-2026