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Record W4413099620 · doi:10.1510/mmcts.2025.080

Re-operative minimally invasive endoscopic mitral valve repair after partial atrioventricular canal repair

2025· article· en· W4413099620 on OpenAlexaff
Satoshi Arimura, Michael Chu

Bibliographic record

VenueMultimedia Manual of Cardio-Thoracic Surgery · 2025
Typearticle
Languageen
FieldMedicine
TopicTrauma Management and Diagnosis
Canadian institutionsUniversity Hospital
Fundersnot available
KeywordsMedicineMitral valve repairSurgeryAtrioventricular valveMitral valveAtrioventricular canalFibrous jointMinimally invasive cardiac surgeryMitral regurgitationCardiologyHeart diseaseCardiac surgery

Abstract

fetched live from OpenAlex

Re-operation following previous congenital heart repair can be challenging. We present a 38-year-old female with a history of partial atrioventricular septal defect repair in infancy who developed severe mitral regurgitation due to a cleft anterior mitral leaflet. Given her anatomy and prior sternotomy, we performed a redo minimally invasive endoscopic mitral valve repair via right anterolateral minithoracotomy access. We meticulously closed the cleft using precise suture placement to restore leaflet integrity and function and performed an annuloplasty to reinforce the annulus and optimize leaflet coaptation. The minimally invasive approach minimized surgical trauma, while endoscopic visualization allowed for a precise and effective repair. This case highlights the feasibility of this approach in patients with complex congenital heart disease, offering a viable alternative to sternotomy with potential benefits for both short- and long-term outcomes.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.021
GPT teacher head0.309
Teacher spread0.289 · 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 designCase report
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

Citations0
Published2025
Admission routes1
Has abstractyes

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