Results of mitral valve reconstruction using substitute extracellular matrix
Bibliographic record
Abstract
Background: During the ongoing search for an ideal patch material for reconstructive heart surgery, several versions of extracellular matrix (ECM) have been used. However, long-term performance in different cardiac positions is unknown. Methods: We performed a retrospective review of outcomes after mitral valve surgery using ECM in 29 patients from 2011 to 2014. Clinical and echocardiographic follow-up was reviewed (mean time, 6.3 ± 2.8 years). Results: ECM was used to reconstruct the posterior mitral annulus in 69% and to repair the mitral leaflet in 65% of the patients. The most prevalent etiology was dystrophic calcification of the annulus (80%) versus endocarditis for leaflet repair (60%). Fifty-five percent of the patients who required annular reconstruction received a mitral valve replacement (MVR). There were 2 perioperative deaths (7%). Long-term data were analyzed according to surgical technique; namely, isolated leaflet repair compared with annular reconstruction with or without MVR. There were 3 late deaths (1 per group). Overall survival was 83% at 7 years. Ninety percent of cases with mitral valve repair with or without annular reconstruction were free from more than mild mitral regurgitation, compared with 45% in the MVR and annular reconstruction group. The mechanism of failure was patch degeneration creating a severe paravalvular leak due to prosthesis dehiscence. Conclusions: ECM used to repair the mitral valve leaflets with or without annular reconstruction offers acceptable results. However, caution should be taken with the use of ECM adjacent to prosthetic valve material because of a high rate of failure associated with patch degeneration.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".