Pulsed Field Versus High‐Power Short‐Duration Radiofrequency Ablation in Atrial Fibrillation: A Meta‐Analysis
Bibliographic record
Abstract
ABSTRACT Background Atrial fibrillation, which has increased in prevalence by 33% over the past two decades, affects 59 million people worldwide. It is treated using thermal and nonthermal techniques like radiofrequency, cryoballoon, laser, and pulsed‐field ablation (PFA). This meta‐analysis is the first to compare PFA with high‐power short‐duration radiofrequency ablation (HPSD‐RFA). Methods We comprehensively searched PubMed, Cochrane Central, and ScienceDirect from inception to August 2024. In Review Manager 5.4.1, we pooled risk ratios (RRs) and weighted mean difference (WMD) along with 95% confidence intervals for dichotomous and continuous outcomes, respectively, and employed a random effects model. Study quality was assessed via the Newcastle–Ottawa Scale, and funnel plots were used to evaluate the risk of publication bias. Results Seven studies with a total of 1538 patients were analyzed in this meta‐analysis. PFA was associated with a shorter total procedural time (MD = −36.39 min; 95% CI: [−46.23, −26.55]; p < 0.00001; I2 = 90%), left atrial dwell time (MD = −33.22 min; 95% CI: [−53.21, −13.23]; p = 0.001; I2 = 93%), and a longer fluoroscopy time compared to the HPSD‐RFA (MD = 9.06 min; 95% CI: [6.13, 11.99]; p < 0.00001; I2 = 96%). Other outcomes were comparable between the two arms. Conclusion PFA outperforms HPSD ablation in terms of procedural efficiency outcomes except for the total fluoroscopy time. Still, both techniques are comparable regarding safety and arrhythmia control outcomes.
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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 | 0.010 | 0.020 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.048 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".