Significant mitral regurgitation in patients undergoing <scp>TAVR</scp>: Mechanisms and imaging variables associated with improvement
Bibliographic record
Abstract
Background Significant mitral regurgitation ( MR ) is associated with poorer outcomes in patients undergoing transcatheter aortic valve replacement ( TAVR ). Factors associated with MR improvement have not been studied thoroughly. Methods Retrospective analysis of consecutive patients treated with TAVR with more than mild MR at baseline. MR evolution was assessed at 1–3 and 6–12 months after intervention. MR severity and mechanisms were assessed by echocardiography. Mitral annulus calcification ( MAC ) was quantified using preoperative cardiac CT . Results From 674 consecutive TAVR recipients, 78 with more than mild MR had a 6–12 months follow‐up. Following TAVR , MR improved in 34 patients (43%), remained stable in 38 (49%) and worsened in 6 (8%). Patients with MR improvement had greater tenting area (141 ± 56 vs. 99 ± 40 mm 2 , P < 0.01), tenting height (7.2 ± 1.9 vs. 5.6 ± 1.9 mm, P < 0.01) and lower ejection fraction (43 ± 16 vs. 52 ± 14%, P = 0.01). MAC was frequent (87.7% of patients) and a trend in greater MAC was observed in patients without MR improvement (3560 ± 5587 vs. 2053 ± 2800, P = 0.16). In multivariable analysis, tenting area ( OR per 10 mm 2 increase: 1.012, 95% CI , 1.001–1.024 P = 0.039) and annulus calcifications associated with leaflet restriction ( OR = 0.108, 95% CI , 0.012–0.956, P = 0.045) were independently associated with MR outcome after TAVR . Conclusion Larger mitral valve tenting area was associated with more improvement of MR after TAVR whereas extensive MAC associated with leaflet restriction was associated with less improvement. This may help in the clinical decision‐making process of TAVR candidates with concomitant MR .
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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".