Balloon-expandable Versus Self-expanding Valves in Patients With Prior Surgical Mitral Valve Replacement Undergoing Transcatheter Aortic Valve Replacement
Bibliographic record
Abstract
BACKGROUND: Pre-existing mitral prosthesis raises technical challenges for transcatheter aortic valve replacement (TAVR) but has been scarcely studied. In this work we sought to compare outcomes of patients with previous surgical mitral valve prostheses undergoing TAVR with balloon-expandable valve (BEV) or self-expanding valve (SEV) systems. METHODS: Patients from the Spanish TAVR registry with pre-existing surgical mitral prostheses were included in this investigation. The primary endpoints were Valve Academic Research Consortium-3 technical and device success, with analysis according to valve type. Transcatheter heart valve (THV) embolization, mitral valve impingement, THV performance, and pacemaker findings were also assessed. RESULTS: A total of 243 patients were included (37% BEVs, 63% SEVs). Overall technical success was 95.9%. Thirty-day device success was higher in BEV patients (94.4% vs 85.0%, P = 0.036), mainly driven by fewer incidences of moderate residual aortic regurgitation (0% vs 5.9%, P = 0.028) and THV embolization (0% vs 3.9%, P = 0.087). BEV recipients exhibited higher mean transvalvular gradients (10.5 vs 8.1 mm Hg, P = 0.002) and lower rates of permanent pacemaker implantation (5.6% vs 15.7%, P = 0.023). There were no differences in mortality, bleeding, or readmission at 30 days. In the multivariate analysis, a mitroaortic distance of ≤ 7 mm and lack of transesophageal echocardiography guidance were associated with increased device failure. CONCLUSIONS: In patients with pre-existing MV prostheses, TAVR was safe and effective regardless of the THV type. Nevertheless, the use of BEVs resulted in an increased rate of device success, driven by lesser THV embolization and residual aortic regurgitation.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.001 | 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".