Guideline‐directed medical therapy in patients undergoing transcatheter edge‐to‐edge repair for secondary mitral regurgitation
Bibliographic record
Abstract
AIMS: Guideline-directed medical therapy (GDMT), based on the combination of beta-blockers (BB), renin-angiotensin system inhibitors (RASI), and mineralocorticoid receptor antagonists (MRA), is known to have a major impact on the outcome of patients with heart failure with reduced ejection fraction (HFrEF). Although GDMT is recommended prior to mitral valve transcatheter edge-to-edge repair (M-TEER), not all patients tolerate it. We studied the association of GDMT prescription with survival in HFrEF patients undergoing M-TEER for secondary mitral regurgitation (SMR). METHODS AND RESULTS: EuroSMR, a European multicentre registry, included SMR patients with left ventricular ejection fraction <50%. The outcome was 2-year all-cause mortality. Of 1344 patients, BB, RASI, and MRA were prescribed in 1169 (87%), 1012 (75%), and 765 (57%) patients at the time of M-TEER, respectively. Triple GDMT prescription was associated with a lower 2-year all-cause mortality compared to non-triple GDMT (hazard ratio [HR] 0.74; 95% confidence interval [CI] 0.60-0.91). The association persisted in patients with glomerular filtration rate <30 ml/min, ischaemic aetiology, or right ventricular dysfunction. Further, a positive impact of triple GDMT prescription on survival was observed in patients with residual mitral regurgitation of ≥2+ (HR 0.62; 95% CI 0.44-0.86), but not in patients with residual mitral regurgitation of ≤1+ (HR 0.83; 95% CI 0.64-1.08). CONCLUSION: Triple GDMT prescription is associated with higher 2-year survival after M-TEER in HFrEF patients with SMR. This association was consistent also in patients with major comorbidities or non-optimal results after M-TEER.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".