Transcatheter edge-to-edge repair in secondary mitral regurgitation
Bibliographic record
Abstract
Secondary mitral regurgitation (SMR) is frequent among patients with heart failure (HF) with reduced ejection fraction (HFrEF), and it is strongly associated with increased mortality, frequent hospitalisations, and poor quality of life. The mechanisms underlying SMR are multifactorial. While guideline-directed medical therapy and cardiac resynchronisation therapy remain the cornerstone of HFrEF management, many patients with significant SMR continue to experience significant symptoms and adverse outcomes. Managing SMR within the context of HF necessitates a multifaceted approach. Transcatheter edge-to-edge repair (TEER) has emerged as a transformative intervention, demonstrating improvements in survival, functional capacity, and HF-related hospitalisations in clinical trials and real-world registries in selected patients. This review provides a comprehensive overview of the evidence supporting TEER, focusing on procedural and follow-up outcomes, and its role in reshaping the therapeutic approach for HF patients with SMR. Additionally, we highlight the critical role of patient selection and identify predictors of poor outcomes as key determinants of TEER success.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".