Coapting COAPT and MOMENTUM 3: Advancing heart failure, secondary mitral regurgitation, and the crossroads of therapies
Bibliographic record
Abstract
The use of transcatheter edge-to-edge repair (TEER) for patients with heart failure and reduced ejection fraction (HFrEF) with secondary mitral regurgitation has increased exponentially. While TEER has shown favorable outcomes compared to medical therapy, the outcomes in the clinical trial that resulted in the approval of TEER for secondary mitral regurgitation remain suboptimal, with a two-year mortality of almost thirty percent. In contrast, a comparison of contemporary durable left ventricular assist device (LVAD) outcomes to TEER in patients with advanced heart failure suggests that numerically greater improvements in survival and functional status may be achieved with LVAD vs. TEER. Taken together, many patients with persistent symptoms despite optimal medical therapy being considered for TEER for secondary mitral regurgitation likely have advanced heart failure. Therefore, evaluation for TEER for HFrEF patients should include a multidisciplinary heart team, including a heart failure physician, to facilitate best-shared decision-making with selection of the therapy most likely to meet the patient's long-term care goals.
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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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.015 | 0.028 |
| Insufficient payload (model declined to judge) | 0.010 | 0.008 |
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".