Aims: Artificial intelligence (AI) has the potential to transform cardiac electrophysiology (EP), particularly in arrhythmia detection, procedural optimization, and patient outcome prediction. However, a standardized approach to reporting and understanding AI-related research in EP is lacking. This scientific statement aims to develop and apply a checklist for AI-related research reporting in EP to enhance transparency, reproducibility, and understandability in the field. Methods and results: An AI checklist specific to EP was developed with expert input from the writing group and voted on using a modified Delphi process, leading to the development of a 29-item checklist. The checklist was subsequently applied to assess reporting practices to identify areas where improvements could be made and provide an overview of the state of the art in AI-related EP research in three domains from May 2021 until May 2024: atrial fibrillation (AF) management, sudden cardiac death (SCD), and EP lab applications. The EHRA AI checklist was applied to 31 studies in AF management, 18 studies in SCD, and 6 studies in EP lab applications. Results differed between the different domains, but in no domain reporting of a specific item exceeded 55% of included papers. Key areas such as trial registration, participant details, data handling, and training performance were underreported (<20%). The checklist application highlighted areas where reporting practices could be improved to promote clearer, more comprehensive AI research in EP. Conclusion: The EHRA AI checklist provides a structured framework for reporting AI research in EP. Its use can improve understanding but also enhance the reproducibility and transparency of AI studies, fostering more robust and reliable integration of AI into clinical EP practice.

Background: Contemporary AF ablation practice has changed rapidly with the introduction of newer energy-delivery platforms. How these changes translate into longitudinal patterns of technology use and procedural characteristics within routine electrophysiology services is less well described. Methods: We performed a retrospective, procedure-level longitudinal service evaluation of AF ablations performed between April 2014 and June 2025 at a United Kingdom (UK) tertiary center. Index and repeat procedures were included. We describe annual technology use and observed skin-to-skin procedure time, fluoroscopy time, and dose-area product (DAP). These are operational measures, not surrogate clinical endpoints. We undertook no adjusted comparative analysis because technology choice was coupled with calendar era and relevant clinical and operator-level covariates were incomplete. Results: The analysis included 2862 procedures, comprising 1878 (66%) radiofrequency ablation (RFA), 735 (26%) cryoballoon, and 249 (9%) pulsed field ablation (PFA). RFA remained the predominant approach until 2020, cryoballoon use peaked in 2018 (n = 138), and PFA increased from 56 procedures in 2023 to 98 in 2024 and 95 in the first half of 2025. The median skin-to-skin time changed from 205 min in 2014 to 104 min in 2025. Observed median fluoroscopy time changed from 32 to 13 min, and median DAP from 3405 to 782 Gy.cm². Conclusions: Over 11 years, the centre experienced a marked change in AF ablation practice, characterised by the progressive adoption of newer technologies, alongside lower recorded procedure durations and radiation exposure. These observations describe service-level temporal trends and should not be interpreted as evidence that any individual ablation modality caused the observed changes or improved clinical outcomes.