101 Is pulsed field ablation better tolerated? - A comparative study of patient experience after af ablation using pulsed field, radiofrequency and cryoballoon ablation
Bibliographic record
Abstract
Background Pulsed field ablation (PFA) is a novel non-thermal ablation treatment for atrial fibrillation (AF). In addition to the emerging safety and efficacy data from early adopters of PFA for AF ablation, there is a growing perception that PFA is better tolerated by patients than established ablation modalities. We sought to compare procedure-related patient symptoms following PFA, radiofrequency (RF) and cryoballoon ablation. Methods We prospectively enrolled 120 patients (age: 65 ±10: female 32%) with paroxysmal or early persistent AF from 3 institutions who underwent pulmonary vein isolation (PVI) using PFA, RF or cryoballoon ablation between November 2022 and October 2023, with 40 age- and sex-matched patients per group. Patient symptom scores were collected at 24-hours and 7-days post ablation for chest pain, breathlessness, palpitations, sore throat, groin pain and fatigue, each graded using a 5-point Likert scale. Statistical analysis was performing using Kruskal-Wallis test and thereafter the Dunn-Bonferroni post-hoc test. Results Patients reported a greater degree of procedure-related symptoms in the cryoballoon cohort at 24 hours post-procedure, which mostly improved by day 7 (figures 1 and 2). The median symptom scores were significantly higher (p<0.05) in the cryoballoon cohort than in the PFA and RF cohort for chest pain, breathlessness, palpitations, sore throat and groin pain. There was no significant difference between PFA and RF patients across the symptom domains. Conclusion PVI using either PFA or RF ablation appears better tolerated than cryoballoon ablation in the immediate and early post-procedure recovery period. Conflict of Interest Nil
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".