Right ventricular dysfunction predicts outcome after transcatheter mitral valve repair for primary mitral valve regurgitation
Bibliographic record
Abstract
AIMS: Right ventricular dysfunction (RVD), as expressed by right ventricular to pulmonary artery coupling, has recently been identified as a strong outcome predictor in patients undergoing mitral valve edge-to-edge repair (M-TEER) for secondary mitral regurgitation (MR). The aim of this study was to define RVD in patients undergoing M-TEER for primary MR (PMR) and to evaluate its impact on procedural MR reduction, symptomatic development and 2-year all-cause mortality. METHODS AND RESULTS: This multicentre study included patients undergoing M-TEER for symptomatic PMR at nine international centres. The study cohort was divided into a derivation (DC) and validation cohort (VC) for calculation and validation of the best discriminatory value for RVD. A total of 648 PMR patients were included in the study. DC and VC were comparable regarding procedural success and outcomes at follow-up. Sensitivity analysis identified RVD as an independent predictor for 2-year mortality in the DC (hazard ratio [HR] 2.37, 95% confidence interval [CI] 1.47-3.81, p < 0.001), which was confirmed in the VC (HR 2.06, 95% CI 1.36-3.13, p < 0.001). Procedural success (MR ≤2+) and symptomatic improvement at follow-up (New York Heart Association [NYHA] class ≤II) were lower in PMR patients with RVD (MR ≤2+: 82% vs. 93%, p = 0.002; NYHA class ≤II: 57.3% vs. 66.5%, p = 0.09 for with vs. without RVD). In all PMR patients, the presence of RVD significantly impaired 2-year survival after M-TEER (HR 2.23, 95% CI 1.63-3.05, p < 0.001). CONCLUSIONS: Mitral valve edge-to-edge repair is an effective treatment option for PMR patients. The presence of RVD is associated with less MR reduction, less symptomatic improvement and increased 2-year mortality. Accordingly, RVD might be included into pre-procedural prognostic considerations.
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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) | 0.000 | 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".