Pulsed Field Ablation: A Systematic Review
Bibliographic record
Abstract
Background: Atrial fibrillation (AF) is the most prevalent cardiac arrhythmia, leading to significant health and economic burdens. Pulmonary vein isolation (PVI) is a key treatment strategy, with pulsed field ablation (PFA) emerging as a promising method due to its specificity and reduced collateral damage compared to traditional thermal ablation techniques like radiofrequency ablation (RFA) and cryoablation (CB). Materials and Methods: A comprehensive literature search was performed across multiple databases, including PubMed, Embase, and MEDLINE via Ovid, Scopus, Cochrane CENTRAL, and ClinicalTrials.Gov. Studies reporting on the efficacy and safety of PFA in AF treatment were selected and analyzed. Quality assessment of the studies was conducted using the Newcastle-Ottawa Scale. Result: Of the 440 articles initially identified, 28 met the inclusion criteria. PVI using PFA demonstrated high success rates, with most studies reporting over 90% success. Durability stands around 65% after 1 year. Mortality was 0.06%-0.32%, while stroke rate was 0.3%-4.4%. There were no reported oesophageal injuries or pulmonary vein stenosis due to the highly selective electroporation-induced cell death caused by PFA rather than coagulative necrosis, sparing nearby structures. There is a short learning curve for PFA. Conclusion: PFA is a highly effective and safe ablation method. It offers an alternative to conventional thermal ablation strategies in the treatment of AF, showing promise to reduce the risk of collateral damage and complications associated with thermal ablation techniques. However, further research is needed to understand its long-term efficacy and safety fully and to standardize procedural protocols for wider clinical application.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.008 |
| Bibliometrics | 0.010 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".