Serial Artificial Intelligence ECG-Derived Atrial Fibrillation Probability and Recurrence Risk After Pulsed Field Ablation
BACKGROUND: Pulsed field ablation is now widely used for atrial fibrillation (AF) ablation, but atrial tachyarrhythmia recurrence remains common and postablation risk tools are limited. We assessed whether a validated sinus‑rhythm artificial intelligence— enabled ECG AF probability score, and its early postablation change, predicts recurrence after pulsed field ablation. METHODS: We studied consecutive patients undergoing index pulsed field ablation across 3 Mayo Clinic sites (February 2024–March 2025) with ≥1 sinus‑rhythm ECG within 180 days preprocedure. Baseline artificial intelligence—enabled ECG AF score (range 0–1) was the mean across baseline ECGs. Recovery indices (RI30/60/90), defined as mean postprocedure artificial intelligence—enabled ECG score within days 1–30/60/90 minus baseline, predicted post‑blanking recurrence using corresponding 30‑, 60‑, and 90‑day blanking windows. The primary outcome was time to first documented AF/atrial flutter/atrial tachycardia episode >30 seconds, ascertained via clinic ECGs, ambulatory monitoring, and device interrogations. Cox regression adjusted for prespecified clinical and echocardiographic covariates assessed associations; Harrell C‑statistic quantified discrimination. RESULTS: Among 1052 patients (67±10 years; 33% women), median baseline score was 0.35; 320 (30%) recurred over 188 days. Higher baseline score independently predicted recurrence (hazard ratio per 0.1 increase, 1.08 [95% CI, 1.03–1.14]). Scores rose on day 0 after ablation, then declined over subsequent weeks, with persistently higher, less‑improving trajectories among patients who recurred (time×recurrence interaction P <0.001). Day 0 score was not independently associated with recurrence after adjustment. Attenuated early recovery (higher recovery index) was independently associated with recurrence, most robustly for RI-90 (hazard ratio per 0.1 increase, 1.15 [95% CI, 1.07–1.24]), and improved discrimination beyond baseline and covariates (C‑statistic, 0.63–0.67; ΔC=0.04). Findings were consistent in a historical thermal ablation cohort. CONCLUSIONS: Baseline and early postablation dynamics of a sinus‑rhythm artificial intelligence—enabled ECG AF probability score are associated with pulsed field ablation recurrence and may aid multivariable risk stratification; prospective validation is warranted.
Authors
- Paul A. Friedman (ORCID: https://orcid.org/0000-0001-5052-2948)
- Kathryn E. Mangold (ORCID: https://orcid.org/0000-0001-7048-2699)
- James Y. Kim (ORCID: https://orcid.org/0000-0001-6073-2009)
- Komandoor S. Srivathsan (ORCID: https://orcid.org/0000-0001-9732-0243)
- Peter A. Noseworthy (ORCID: https://orcid.org/0000-0002-4308-0456)
- Zachi Itzhak Attia (ORCID: https://orcid.org/0000-0002-9706-7900)
- Mayank Sardana (ORCID: https://orcid.org/0000-0001-9465-1047)
- Hema Srikanth Vemulapalli (ORCID: https://orcid.org/0009-0001-2942-1031)
- Juan F. Rodriguez (ORCID: https://orcid.org/0000-0002-8271-9128)
- Julia Wood
Institutions
- Mayo Clinic in Arizona (US)
- Valley Baptist Medical Center (US)
Publication Details
- Journal
- Circulation Arrhythmia and Electrophysiology
- Published
- 2026-10-08
- DOI
- https://doi.org/10.1161/circep.126.015183
- Primary Topic
- Atrial Fibrillation Management and Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 0.00