Adverse Event Landscape of Pulsed Field Ablation Catheters: A Computational Review of FDA MAUDE Post-Market Surveillance Data.

BACKGROUND

Pulsed field ablation (PFA) is Food and Drug Administration (FDA)-cleared for pulmonary vein isolation in atrial fibrillation. Using a keyword-based natural language processing pipeline applied to free-text narratives in the FDA MAUDE database, we aimed to characterize and compare adverse event and device malfunction profiles across the four cleared PFA systems.

METHODS

We retrieved 6930 MAUDE reports for FDA product code QZI (pulsed field ablation catheter) spanning December 13, 2023 through April 30, 2026, covering all four FDA-cleared PFA systems. Reports were deduplicated and assigned to a specific device system using manufacturer and brand name fields. Concatenated free-text narratives were classified into 11 predefined adverse event categories using multi-label keyword-based natural language processing. Device malfunction reports were additionally subclassified into one of 11 hardware-specific subtypes. Descriptive statistics were used throughout.

RESULTS

Of 6930 reports, 4185 (60.4%) were classified into at least one adverse event category. The three most common categories were device/catheter malfunction (2068; 29.8%), cardiac tamponade/pericardial effusion (915; 13.2%), and stroke/TIA/cerebral embolism (600; 8.7%). PFA-specific physiologic adverse events-ST-elevation myocardial infarction (STEMI), hemolysis/acute kidney injury, and phrenic nerve palsy-accounted for 615 combined reports (8.9% of all reports). Fatality proportions were highest for vascular access complications (6.8%), esophageal/atrioesophageal injury (6.0%), and coronary artery spasm/STEMI (5.3%). Among malfunction reports, retraction/retrieval failure predominated for Farapulse (48.9%), while electrical/energy delivery failure was the leading subtype for PulseSelect (29.4%).

CONCLUSIONS

Natural language processing (NLP)-assisted keyword classification enables systematic, scalable characterization of adverse event patterns across nearly 7000 real-world PFA reports. PFA-specific physiologic adverse events are identifiable through post-market surveillance data and constitute a distinct safety phenotype separate from device malfunction. This approach provides a reproducible framework for near-real-time surveillance of novel cardiac ablation systems.