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Transcatheter Mitral Valve Repair for Functional Mitral Regurgitation: Coronary Sinus Approach

2007· review· en· W1991615267 on OpenAlexaff
Nicolò Piazza, Raoul Bonan

Bibliographic record

VenueJournal of Interventional Cardiology · 2007
Typereview
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsMontreal Heart Institute
Fundersnot available
KeywordsMedicineMitral regurgitationCardiologyInternal medicineCoronary sinusMitral annulusMitral valvePerioperativeMitral valve annuloplastyMyocardial infarctionFunctional mitral regurgitationMitral valve repairHeart failureSurgeryEjection fractionDiastoleBlood pressure

Abstract

fetched live from OpenAlex

Mitral regurgitation has become recognized as an important health problem. More specifically, functional mitral regurgitation is associated with worse outcomes in heart failure, postmyocardial infarction, and perioperative coronary artery bypass surgery patients. Many patients with severe mitral regurgitation are denied or refused mitral valve surgery. A less invasive procedure with possibly fewer potential complications may thus be attractive for patients with severe mitral regurgitation. Devices used for coronary sinus (CS) mitral annuloplasty are directed toward patients with functional mitral regurgitation. Because of its easy accessibility and close relationship to the posterior mitral annulus (MA), alterations of the CS geometry with percutaneous devices may translate to displacement of the posterior annulus and correct mitral leaflet coaptation. This review will focus on the contemporary CS annuloplasty devices: (1) Edwards MONARC system; (2) Cardiac Dimensions CARILLON; and (3) Viacor Shape Changing Rods system. In addition, important information obtained from recent imaging studies describing the relationship between the CS, MA, and coronary arteries will be reviewed.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.003

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 head0.108
GPT teacher head0.424
Teacher spread0.316 · 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

Citations32
Published2007
Admission routes1
Has abstractyes

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