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Pulsed Field Ablation: A Review of Preclinical and Clinical Studies

2025· review· en· W4408781901 on OpenAlexaff
Andrew Sullivan, Martín Aguilar, Zachary Laksman

Bibliographic record

VenueBioengineering · 2025
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial Inactivation Methods
Canadian institutionsUniversité de MontréalMontreal Heart InstituteUniversity of British Columbia
Fundersnot available
KeywordsAblationIrreversible electroporationCardiac electrophysiologyMedicinePulmonary veinCardiologyElectroporationBiomedical engineeringElectrophysiologyInternal medicineBiology

Abstract

fetched live from OpenAlex

Pulsed field ablation (PFA) is an emerging technology that utilizes ultra-short high-voltage electric pulses to create nanopores in cell membranes, leading to cell death through irreversible electroporation (IRE). PFA is touted to be highly tissue-selective, which may mitigate the risk of collateral injury to vital adjacent structures. In the field of cardiac electrophysiology, initial studies have shown promising results for acute pulmonary vein isolation (PVI) and lesion durability, with overall freedom from recurrent atrial arrhythmia comparable to traditional thermal ablation modalities. While further large studies are required for long-term efficacy and safety data, PFA has the potential to become a preferred energy source for cardiac ablation for some indications. This review outlines the basic principles and biophysics of IRE and its application to cardiac electrophysiology through a review of the existing preclinical and clinical data.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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.

Opus teacher head0.129
GPT teacher head0.505
Teacher spread0.376 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations5
Published2025
Admission routes1
Has abstractyes

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