Mitral regurgitation in patients undergoing transcatheter aortic valve implantation for degenerated surgical aortic bioprosthesis: Insights from PARTNER 2 Valve‐in‐Valve Registry
Bibliographic record
Abstract
BACKGROUND: Valve-in-valve (VIV) treatment with transcatheter aortic valve replacement (TAVR) is a viable option for patients with failing aortic bioprosthetic valves. Optimal management of those with concomitant mitral regurgitation (MR) remains undetermined. Therefore, we sought to assess the implications of concomitant MR in patients undergoing VIV-TAVR. METHODS AND RESULTS: The PARTNER 2 VIV registry enrolled patients with degenerated surgical aortic bioprosthesis at high risk for reoperation. Patients with core-laboratory echocardiographic assessment of MR were analyzed; severe MR was excluded. We compared patients with ≤mild MR versus moderate MR and assessed changes in MR severity and clinical outcomes. A total of 339 patients (89 initial registry, 250 continued access) underwent VIV procedures; mean age 79.0 ± 10.2 years, mean Society of Thoracic Surgeon score 8.9 ± 4.5%. At baseline, 228/339 (67.3%) had ≤mild MR and 111/339 (32.7%) had moderate MR. In paired analysis, there was significant improvement in ≥moderate MR from baseline to 30 days (32.6% vs. 14.5%, p < .0001 [n = 304]), and no significant change between 30 days and 1 year (13.4% vs. 12.1%, p = .56 [n = 224]) or 1 year and 2 years (11.0% vs. 10.4%, p = .81 [n = 182]). There was no difference in death or stroke between ≤mild MR and moderate MR at 30 days (4.0% vs. 7.2%, p = .20), 1 year (15.5% vs. 15.3%, p = .98) or 2 years (26.5% vs. 23.5%, p = .67). CONCLUSION: Moderate concomitant MR tends to improve with VIV-TAVR, and was not a predictor of long-term adverse outcomes in this cohort. In selected patients undergoing VIV-TAVR, it may be appropriate to conservatively manage concomitant MR. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov NCT# 03225001.
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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) | 0.001 | 0.008 |
| 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".