Mitraclip Therapy in Patients with Functional Mitral Regurgitation and Missing Leaflet Coaptation: Is it Still an Exclusion Criterion?
Bibliographic record
Abstract
AIMS: The aim of this study was to investigate the feasibility, safety, and efficacy of Mitraclip therapy in patients with functional mitral regurgitation (MR) and missing leaflet coaptation (MLC). METHODS AND RESULTS: ; P = 0.019) and sphericity index (0.80 ± 0.11 vs. 0.71 ± 0.10; P = 0.003). MLC patients were treated with pharmacological/mechanical support in order to improve leaflet coaptation and to prepare the mitral valve apparatus for grasping. Implantation of >1 clip and device time were comparable in patients with and without MLC (61.9% vs. 47.5%; P = 0.284 and 101 ± 39 vs. 108 ± 69 min; P = 0.646, respectively). No significant differences were observed between the two cohorts in technical success (95.5% vs. 97.5%, P = 0.667), 30-day device success (85.7% vs. 78.9%; P = 0.525), procedural success (81.8% vs. 75%; P = 0.842), and 1-year patient success (52.9% vs. 44.1%; P = 0.261), defined according to the MVARC (Mitral Valve Academic Research Consortium) criteria. The long-term composite endpoint of cardiovascular death and heart failure hospitalization was similar in the two groups (49.9% vs. 44.4%; P = 0.348). A significant improvement of MR and NYHA functional class and a lack of reverse remodelling were observed up to 2 years in both arms. CONCLUSION: The Mitraclip procedure could be extended to patients with functional MR who do not fulfil the coaptation length EVEREST II criterion and who would otherwise be excluded from this treatment.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".