Transcatheter Mitral Valve Replacement Versus Medical Therapy for Secondary Mitral Regurgitation: A Propensity Score–Matched Comparison
Bibliographic record
Abstract
Background: Transcatheter mitral valve replacement (TMVR) is an emerging therapeutic alternative for patients with secondary mitral regurgitation (MR). Outcomes of TMVR versus guideline-directed medical therapy (GDMT) have not been investigated for this population. This study aimed to compare clinical outcomes of patients with secondary MR undergoing TMVR versus GDMT alone. Methods: The CHOICE-MI registry (Choice of Optimal Transcatheter Treatment for Mitral Insufficiency) included patients with MR undergoing TMVR using dedicated devices. Patients with MR pathogeneses other than secondary MR were excluded. Patients treated with GDMT alone were derived from the control arm of the COAPT trial (Cardiovascular Outcomes Assessment of the MitraClip Percutaneous Therapy for Heart Failure Patients With Functional Mitral Regurgitation). We compared outcomes between the TMVR and GDMT groups, using propensity score matching to adjust for baseline differences. Results: After propensity score matching, 97 patient pairs undergoing TMVR (72.9±8.7 years; 60.8% men; transapical access, 91.8%) versus GDMT (73.1±11.0 years; 59.8% men) were compared. At 1 and 2 years, residual MR was ≤1+ in all patients of the TMVR group compared with 6.9% and 7.7%, respectively, in those receiving GDMT alone (both P <0.001). The 2-year rate of heart failure hospitalization was significantly lower in the TMVR group (32.8% versus 54.4%; hazard ratio, 0.59 [95% CI, 0.35–0.99]; P =0.04). Among survivors, a higher proportion of patients were in the New York Heart Association functional class I or II in the TMVR group at 1 year (78.2% versus 59.7%; P =0.03) and at 2 years (77.8% versus 53.2%; P =0.09). Two-year mortality was similar in the 2 groups (TMVR versus GDMT, 36.8% versus 40.8%; hazard ratio, 1.01 [95% CI, 0.62–1.64]; P =0.98). Conclusions: In this observational comparison, over 2-year follow-up, TMVR using mostly transapical devices in patients with secondary MR was associated with significant reduction of MR, symptomatic improvement, less frequent hospitalizations for heart failure, and similar mortality compared with GDMT. Registration: URL: https://clinicaltrials.gov ; Unique identifier: NCT04688190 (CHOICE-MI) and NCT01626079 (COAPT).
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".