Characteristics and outcomes of patients screened for transcatheter mitral valve implantation: <scp>1‐year</scp> results from the <scp>CHOICE‐MI</scp> registry
Bibliographic record
Abstract
AIMS: Transcatheter mitral valve implantation (TMVI) represents a novel treatment option for patients with mitral regurgitation (MR) unsuitable for established therapies. The CHOICE-MI registry aimed to investigate outcomes of patients undergoing screening for TMVI. METHODS AND RESULTS: From May 2014 to March 2021, patients with MR considered suboptimal candidates for transcatheter edge-to-edge repair (TEER) and at high risk for mitral valve surgery underwent TMVI screening at 26 centres. Characteristics and outcomes were investigated for patients undergoing TMVI and for TMVI-ineligible patients referred to bailout-TEER, high-risk surgery or medical therapy (MT). The primary composite endpoint was all-cause mortality or heart failure hospitalization after 1 year. Among 746 patients included (78.5 years, interquartile range [IQR] 72.0-83.0, EuroSCORE II 4.7% [IQR 2.7-9.7]), 229 patients (30.7%) underwent TMVI with 10 different dedicated devices. At 1 year, residual MR ≤1+ was present in 95.2% and the primary endpoint occurred in 39.2% of patients treated with TMVI. In TMVI-ineligible patients (n = 517, 69.3%), rates of residual MR ≤1+ were 37.2%, 100.0% and 2.4% after bailout-TEER, high-risk surgery and MT, respectively. The primary endpoint at 1 year occurred in 28.8% of patients referred to bailout-TEER, in 42.9% of patients undergoing high-risk surgery and in 47.9% of patients remaining on MT. CONCLUSION: This registry included the largest number of patients treated with TMVI to date. TMVI with 10 dedicated devices resulted in predictable MR elimination and sustained functional improvement at 1 year. In TMVI-ineligible patients, bailout-TEER and high-risk surgery represented reasonable alternatives, while MT was associated with poor clinical and functional outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".