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Record W4409011864 · doi:10.1093/europace/euaf050

European Society of Cardiology (ESC) clinical consensus statement on indications for conduction system pacing, with special contribution of the European Heart Rhythm Association of the ESC and endorsed by the Asia Pacific Heart Rhythm Society, the Canadian Heart Rhythm Society, the Heart Rhythm Society, and the Latin American Heart Rhythm Society

2025· article· en· W4409011864 on OpenAlexaffabout
Michael Glikson, Haran Burri, Amr Abdin, Óscar Cano, Karol Čurila, Jan De Pooter, Juan Carlos Díaz, Inga Drossart, Weijian Huang, Carsten W. Israel, Marek Jastrzębski, Jacqueline Joza, Jarkko Karvonen, Daniel Keene, Christophe Leclercq, Wilfried Müllens, Margarida Pujol‐López, Archana Rao, Kevin Vernooy, Pugazhendhi Vijayaraman, Francesco Zanon, Yoav Michowitz, Lucas V.A. Boersma, Carina Blomström‐Lundqvist, Mads Brix Kronborg, Mina K. Chung, Hung‐Fat Tse, Habib Khan, Francisco Leyva, Ulises Rojel-Martínez, Marcin Ruciński, Niraj Varma

Bibliographic record

VenueEP Europace · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiac pacing and defibrillation studies
Canadian institutionsWestern UniversityMcGill University Health Centre
Fundersnot available
KeywordsHeart RhythmRhythmMedicineCardiologyInternal medicineStatement (logic)Political science

Abstract

fetched live from OpenAlex

Conduction system pacing (CSP) is being increasingly adopted as a more physiological alternative to right ventricular and biventricular pacing. Since the 2021 European Society of Cardiology pacing guidelines, there has been growing evidence that this therapy is safe and effective. Furthermore, left bundle branch area pacing was not covered in these guidelines due to limited evidence at that time. This Clinical Consensus Statement provides advice on indications for CSP, taking into account the significant evolution in this domain.

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)0.011
metaresearch head score (Gemma)0.025
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.025
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0090.006

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 head0.022
GPT teacher head0.291
Teacher spread0.269 · 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
GenreEditorial

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

Citations116
Published2025
Admission routes2
Has abstractyes

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