MétaCan
Menu
Back to cohort
Record W4386150885 · doi:10.1093/europace/euad244

Progress in atrial fibrillation ablation during 25 years of <i>Europace</i> journal

2023· article· en· W4386150885 on OpenAlexaff
Lucas V.A. Boersma, Jason G. Andrade, Timothy R. Betts, Mattias Duytschaever, Helmut Pürerfellner, Francesco Santoro, Stylianos Tzeis, Atul Verma

Bibliographic record

VenueEP Europace · 2023
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsMcGill University Health CentreUniversité de MontréalMontreal Heart InstituteBC Innovation CouncilUniversity of British Columbia
Fundersnot available
KeywordsMedicineAblationAtrial fibrillationCatheter ablationCardiology

Abstract

fetched live from OpenAlex

The first edition of Europace journal in 1999 came right around the time of the landmark publication of the electrophysiologists from Bordeaux, establishing how elimination of ectopic activity from the pulmonary veins (PVs) resulted in a marked reduction of atrial fibrillation (AF). The past 25 years have seen an incredible surge in scientific interest to develop new catheters and energy sources to optimize durability and safety of ablation, as well as study the mechanisms for AF and devise ablation strategies. While ablation in the beginning was performed with classic 4 mm tip catheters that emitted radiofrequency (RF) energy to create tissue lesions, this evolved to using irrigation and contact force (CF) measurement while increasing power. Also, so-called single-shot devices were developed with balloons and arrays to create larger contiguous lesions, and energy sources changed from RF current to cryogenic ablation and more recently pulsed field ablation with electrical current. Although PV ablation has remained the basis for every AF ablation, it was soon recognized that this was not enough to cure all patients, especially those with non-paroxysmal AF. Standardized approaches for additional ablation targets have been used but have not been satisfactory in all patients so far. This led to highly technical mapping systems that are meant to unravel the drivers for the maintenance of AF. In the following sections, the development of energies, strategies, and tools is described with a focus on the contribution of Europace to publish the outcomes of studies that were done during the past 25 years.

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)0.010
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.004
Science and technology studies0.0010.002
Scholarly communication0.0050.005
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.004

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 head0.038
GPT teacher head0.323
Teacher spread0.285 · 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 designNot applicable
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

Citations117
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueEP EuropaceSame topicAtrial Fibrillation Management and OutcomesFrench-language works237,207