Clinical outcomes of transcatheter mitral valve replacement: two-year results of the CHOICE-MI Registry
Bibliographic record
Abstract
BACKGROUND: Transcatheter mitral valve replacement (TMVR) using dedicated devices is an alternative therapy for high-risk patients with symptomatic mitral regurgitation (MR). AIMS: This study aimed to assess the 2-year outcomes and predictors of mortality in patients undergoing TMVR from the multicentre CHOICE-MI Registry. METHODS: The CHOICE-MI Registry included consecutive patients with symptomatic MR treated with 11 different dedicated TMVR devices at 31 international centres. The investigated endpoints included mortality and heart failure hospitalisation rates, procedural complications, residual MR, and functional status. Multivariable Cox regression analysis was applied to identify independent predictors of 2-year mortality. RESULTS: A total of 400 patients, median age 76 years (interquartile range [IQR] 71, 81), 59.5% male, EuroSCORE II 6.2% (IQR 3.8, 12.0), underwent TMVR. Technical success was achieved in 95.2% of patients. MR reduction to ≤1+ was observed in 95.2% at discharge with durable results at 1 and 2 years. New York Heart Association Functional Class had improved significantly at 1 and 2 years. All-cause mortality was 9.2% at 30 days, 27.9% at 1 year and 38.1% at 2 years after TMVR. Chronic obstructive pulmonary disease, reduced glomerular filtration rate, and low serum albumin were independent predictors of 2-year mortality. Among the 30-day complications, left ventricular outflow tract obstruction, access site and bleeding complications showed the strongest impact on 2-year mortality. CONCLUSIONS: In this real-world registry of patients with symptomatic MR undergoing TMVR, treatment with TMVR was associated with a durable resolution of MR and significant functional improvement at 2 years. Two-year mortality was 38.1%. Optimised patient selection and improved access site management are mandatory to improve outcomes.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".