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Record W7130719894 · doi:10.5167/uzh-291738

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· W7130719894 on OpenAlexaboutno aff
Jean‐Claude Deharo, Julien Dreyfus, Maria-Grazia Bongiorni, Haran Burri, Pascal Defaye, Michael Glikson, Nigel Lever, Antonio Mangieri, Blandine Mondésert, Jens Cosedis Nielsen, Maully Shah, Christoph Thomas Starck, Archana Rao, Christophe Leclercq, Fabien Praz, Sergio Richter, Nicolas Amabile, Alexander Breitenstein, Óscar Cano, Karol Čurila, Jamie Manlucu, Robert Schaller, Hung-Fat Tse, Christian Veltmann, Zachary Whinnett

Bibliographic record

VenueUniversität Zürich, ZORA · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsHeart RhythmPercutaneousPsychological interventionTricuspid valveGuidelineValve replacementPercutaneous coronary intervention

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.368
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.008
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.006
GPT teacher head0.223
Teacher spread0.216 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueUniversität Zürich, ZORASame topicCardiac Valve Diseases and TreatmentsFrench-language works237,207