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Record W2999218741 · doi:10.1177/1556984519890602

Contemporary Status of Percutaneous Transcatheter Edge-to-Edge Repair: Is It a Complement or Replacement to Mitral Surgery?

2020· review· en· W2999218741 on OpenAlexaff
Hunbo Shim, Edward Percy, Sameer Hirji, Tsuyoshi Kaneko

Bibliographic record

VenueInnovations Technology and Techniques in Cardiothoracic and Vascular Surgery · 2020
Typereview
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMitral regurgitationMedicinePercutaneousMitral valve repairSurgeryMitral valveCardiac surgeryGeneral surgery

Abstract

fetched live from OpenAlex

Transcatheter mitral valve repair devices borrow from the concept of surgical edge-to-edge approximation and are becoming increasingly used in patients with both primary and functional mitral regurgitation. The application of these new devices is expanding globally; however, debates between which patients are amenable to surgery vs. percutaneous approaches are ongoing. As new trials and regulatory approvals have evolved, the indications for transcatheter approaches have expanded, in a way that is complementaty to existing indications for surgical repair. In general, the treatment of mitral regurgitation should be stratified based on underlying pathophysiology and anatomy by a multidisciplinary team including cardiac surgeons and interventional cardiologists. This review aims to provide practical approaches to patient selection and treatment strategies for mitral regurgitation based on historical data and recently published trials, with a focus on the distinction between surgical and transcatheter mitral therapies.

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)0.001
metaresearch head score (Gemma)0.002
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
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.077
GPT teacher head0.406
Teacher spread0.329 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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