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Record W3099612643 · doi:10.1002/ccd.29365

Initial clinical experience with VersaCross transseptal system for transcatheter mitral valve repair

2020· article· en· W3099612643 on OpenAlexaff
Neila Sayah, François Simon, Patrick Garceau, Anique Ducharme, Arsène Basmadjian, Denis Bouchard, Michel Pellerin, Raoul Bonan, Anita Asgar

Bibliographic record

VenueCatheterization and Cardiovascular Interventions · 2020
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsMontreal Heart Institute
Fundersnot available
KeywordsMedicineMitraClipSurgeryMitral valveMitral valve repairCatheterAdverse effectCardiologyInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: The aim of this study is to describe the initial experience with versacross transseptal (TS) system for transseptal puncture for the transcatheter mitral valve repair using the MitraClip device. BACKGROUND: Transeptal puncture is a key step in transcatheter mitral valve repair (MVR) and the use of the VersaCross system comprised of a sheath, a dilator and a radiofrequency wire has not been previously described. METHODS: Prospective single center study of consecutive patients undergoing transcatheter mitral valve repair with the MitraClip device were included. Targeted TS puncture was performed under transesophageal echocardiographic (TEE) guidance. Baseline demographics, procedural characteristics, and major adverse procedural events were collected. RESULTS: Twenty-five consecutive patients underwent transseptal puncture using the VersaCross TS system. Transseptal puncture was successful in 100% of patients. The mean time for TS puncture was 3 3 ± 1.6 min with no major adverse procedural events. The mean time from insertion of the VersaCross system to insertion of the MitraClip guide catheter was 3.8 ± 3.0 minutes. CONCLUSION: The VersaCross TS system was successful in all patients for MitraClip procedure with no adverse procedural events and may be associated with increased procedural efficiency.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.299
Threshold uncertainty score0.972

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.038
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.068
GPT teacher head0.390
Teacher spread0.322 · 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

Citations12
Published2020
Admission routes1
Has abstractyes

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