Transcatheter mitral valve repair and replacement: the next frontier of transcatheter valve intervention
Bibliographic record
Abstract
PURPOSE OF REVIEW: We summarize the recent developments in transcatheter mitral valve repair (TMVr) and replacement (TMVR), discuss determinants of MitraClip outcomes in various mitral regurgitation causes, and highlight newly emerging devices and randomized trials. RECENT FINDINGS: The discordant results published in the two recent randomized trials for MitraClip, the COAPT and the MITRA-FR trial have led to the emergence of a new conceptual framework such as the proportionate versus disproportionate mitral regurgitation and hemodynamics assessment tools like the real-time continuous left atrial pressure monitoring. Learning curve and volume-outcome analyses and studies examining the MitraClip usage in patients with degenerative mitral regurgitation are recent developments that have influenced MitraClip regulation and coverage. Several trials for TMVr devices that take an alternative approach to the edge-to-edge repair are underway and advancements in the TMVR technologies are continuing to progress to fill the unmet needs of treating high surgical risk patients whose complex valve anatomy make TMVr unfeasible. SUMMARY: Evidence supports careful analysis of the valve area and left ventricular function in addition to the left atrial hemodynamics will improve the MitraClip outcome. Operator experience plays a greater effect when achieving excellent results with 1+ or less residual mitral regurgitation whereas surgical MVr volume did not influence TMVr outcome. Interventions on the complex primary mitral regurgitation remain under the surgical domain, but MITRA high risk (HR) and REPAIR mitral regurgitation trials are underway to evaluate the role of MitraClip in high to intermediate surgical risk patients with primary mitral regurgitation. Despite the slow developments in TMVR, the results of the early trials of its devices are promising.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.045 |
| 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 | 0.001 |
| 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".