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Record W3120626375 · doi:10.1097/hco.0000000000000807

Resurgence of the edge-to-edge repair of the mitral valve

2020· review· en· W3120626375 on OpenAlexaff
Ahmad Makhdoum, Aleksander Dokollari, Malak Elbatarny, Subodh Verma, Bobby Yanagawa

Bibliographic record

VenueCurrent Opinion in Cardiology · 2020
Typereview
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMitral valve repairMedicineMitral regurgitationCardiologyMitral valveStenosisInternal medicineSurgery

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: To provide a critical review of the application and outcomes of surgical edge-to-edge (E2E) or Alfieri repair for mitral valvulopathy. RECENT FINDINGS: The E2E repair is a surgical technique to address mitral regurgitation, particularly suited when the responsible mechanism is bileaflet prolapse combined with enlarged annular area. It can also be used for a range of mitral valve pathologies. Surgically, the technique has been employed as a bailout for unsuccessful repair including residual mitral regurgitation because of systolic anterior motion (SAM). E2E repair should be accompanied by a ring annuloplasty for long-term repair durability. The simplicity of this approach makes it an ideal strategy during minimally-invasive mitral valve repair. It may also be performed via a transaortic approach at the time of aortic valve surgery to address less-than-severe mitral regurgitation or to address residual SAM following myectomy for hypertrophic obstructive cardiomyopathy. We review the surgical indication, potential complications including risk of mitral stenosis and the long-term outcomes of E2E repair. SUMMARY: The E2E surgical repair is a simple and effective surgical strategy to address a wide range of mitral regurgitation. This is an important technique in the surgical armamentarium especially in cases of minimally-invasive mitral valve surgery.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.822
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.014
Bibliometrics0.0000.001
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 head0.110
GPT teacher head0.450
Teacher spread0.340 · 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 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

Citations5
Published2020
Admission routes1
Has abstractyes

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