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Record W4409016278 · doi:10.1093/europace/euaf061

Management of patients with transvalvular right ventricular leads undergoing transcatheter tricuspid valve interventions: a scientific statement of the European Heart Rhythm Association and the European Association of Percutaneous Cardiovascular Interventions of the ESC endorsed by the Heart Rhythm Society, the Asian Pacific Heart Rhythm Society and the Canadian Heart Rhythm Society

2025· article· en· W4409016278 on OpenAlexaffabout
Jean‐Claude Deharo, Julien Dreyfus, Maria-Grazia Bongiorni, Haran Burri, Pascal Defaye, Michael Glikson, Nigel Lever, Antonio Mangieri, Blandine Mondésert, Maully J. Shah, Christoph Starck, Archana Rao, Christophe Leclercq, Fabien Praz

Bibliographic record

VenueEP Europace · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsLondon Health Sciences CentreWestern UniversityUniversité de MontréalMontreal Heart Institute
Fundersnot available
KeywordsMedicineHeart RhythmInternal medicineCardiologyPercutaneousPsychological interventionTricuspid valveImplantable cardioverter-defibrillatorIntensive care medicine

Abstract

fetched live from OpenAlex

Up to one-third of patients referred for transcatheter tricuspid valve intervention (TTVI) have a transvalvular pacemaker (PPM) or implantable cardioverter-defibrillator (ICD) lead in place. Both the electrophysiology and interventional cardiology communities have been alerted to the complexity of decision-making in this situation due to potential interactions between the leads and the TTVI material, including the risk of jailing or damage to the leads. This document, commissioned by the European Heart Rhythm Association and the European Association of Percutaneous Cardiovascular Interventions of the ESC, reviews the scientific evidence to inform Heart Team discussions on the management of patients with a PPM or ICD who are scheduled for or have undergone TTVI.

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)0.007
metaresearch head score (Gemma)0.021
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: Other · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.007
GPT teacher head0.243
Teacher spread0.235 · 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
GenreOther

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

Citations28
Published2025
Admission routes2
Has abstractyes

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