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Record W4319461936 · doi:10.1161/jaha.122.027504

Percutaneous MitraClip Device or Surgical Mitral Valve Repair in Patients With Primary Mitral Regurgitation Who Are Candidates for Surgery: Design and Rationale of the REPAIR MR Trial

2023· article· en· W4319461936 on OpenAlexaff
Patrick M. McCarthy, Brian Whisenant, Anita Asgar, Gorav Ailawadi, James Hermiller, Mathew Williams, Andrew Morse, Michael Rinaldi, Paul Grayburn, James D. Thomas, Randolph P. Martin, Federico M. Asch, Yu Shu, Kartik S. Sundareswaran, Neil Moat, Saibal Kar

Bibliographic record

VenueJournal of the American Heart Association · 2023
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsMontreal Heart Institute
FundersLivaNovaAbbott VascularBoston Scientific CorporationAtriCureEdwards Lifesciences
KeywordsMedicineMitraClipPercutaneousMitral regurgitationSurgeryMitral valve repairMitral valveCardiologyInternal medicine

Abstract

fetched live from OpenAlex

Background The current standard of care for the treatment of patients with primary mitral regurgitation (MR) is surgical mitral valve repair. Transcatheter edge-to-edge repair with the MitraClip device provides a less invasive treatment option for patients with both primary and secondary MR. Worldwide, >150 000 patients have been treated with the MitraClip device. However, in the United States, MitraClip is approved for use only in primary patients with MR who are at high or prohibitive risk for mitral valve surgery. The REPAIR MR (Percutaneous MitraClip Device or Surgical Mitral Valve Repair in Patients With Primary Mitral Regurgitation Who Are Candidates for Surgery) trial is designed to compare early and late outcomes associated with transcatheter edge-to-edge repair with the MitraClip and surgical repair of primary MR in older or moderate surgical risk patients. Methods and Results The REPAIR MR trial is a prospective, randomized, parallel-controlled, open-label multicenter, noninferiority trial for the treatment of severe primary MR (verified by an independent echocardiographic core laboratory). Patients with severe MR and indications for surgery because of symptoms (New York Heart Association class II-IV), or without symptoms with left ventricular ejection fraction ≤60%, pulmonary artery systolic pressure >50 mm Hg, or left ventricular end-systolic diameter ≥40 mm are eligible for the trial provided they meet the moderate surgical risk criteria as follows: (1) ≥75 years of age, or (2) if <75 years of age, then the subject has a Society of Thoracic Surgeons Predicted Risk Of Mortality score of ≥2% for mitral repair (or Society of Thoracic Surgeons replacement score of ≥4%), or the presence of a comorbidity that may introduce a surgery-specific risk. The local surgeon must determine that the mitral valve can be surgically repaired. Additionally, an independent eligibility committee will confirm that the MR can be reduced to mild or less with both the MitraClip and surgical mitral valve repair with a high degree of certainty. A total of 500 eligible subjects will be randomized in a 1:1 ratio to receive the MitraClip device or to undergo surgical mitral valve repair (control group). There are 2 co-primary end points for the trial, both of which will be evaluated at 2 years. Each subject will be followed for 10 years after enrollment. The study has received approval from both the Food and Drug Administration and the Centers for Medicare and Medicaid Services, and enrolled its first subject in July 2020. Conclusions The REPAIR MR trial will determine the safety and effectiveness of transcatheter edge-to-edge repair with the MitraClip in patients with primary MR who are at moderate surgical risk and are candidates for surgical MV repair. The trial will generate contemporary comparative clinical evidence for the MitraClip device and surgical MV repair. Registration https://clinicaltrials.gov/ct2/show/NCT04198870; NCT04198870.

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)0.009
metaresearch head score (Gemma)0.007
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: Protocol · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.007
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0080.002

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 head0.018
GPT teacher head0.298
Teacher spread0.280 · 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
GenreProtocol

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

Citations66
Published2023
Admission routes1
Has abstractyes

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