Transcatheter Aortic Valve Implantation for Bioprosthetic Valve Failure: Placement of Aortic Transcatheter Valves 3 Aortic Valve-in-Valve Study
Why this work is in the frame
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Bibliographic record
Abstract
Background: Transcatheter aortic valve implantation is safe and effective for high-risk patients with bioprosthetic valve failure (BVF) but has not been studied in low- and intermediate-risk patients. One year outcomes of the PARTNER 3 Aortic Valve-in-valve (AViV) Study were evaluated. Methods: This prospective, single-arm, multicenter study enrolled 100 patients from 29 sites with surgical BVF. The primary endpoint was a composite of all-cause mortality and stroke at 1 year. The key secondary outcomes included mean gradient, functional capacity, and rehospitalization (valve-related, procedure-related, or heart failure related). Results: A total of 97 patients underwent AViV with a balloon-expandable valve from 2017 to 2019. Patients were 79.4% male with a mean age of 67.1 years and Society of Thoracic Surgeons score of 2.9%. The primary endpoint occurred in 2 patients (2.1%) who had strokes; there was no mortality at 1 year. Five patients (5.2%) had valve thrombosis events, and 9 patients (9.3%) had rehospitalizations, including 2 (2.1%) for strokes, 1 (1.0%) for heart failure, and 6 (6.2%) for aortic valve reinterventions (3 explants, 3 balloon dilations, and 1 percutaneous paravalvular regurgitation closure). From baseline to 1 year, New York Heart Association class III/IV decreased from 43.3% to 4.5%, mean gradient from 39.1 ± 18.2 mm Hg to 19.7 ± 7.6 mm Hg, and ≥moderate aortic regurgitation from 41.1% to 1.1%. Conclusions: AViV with a balloon-expandable valve improved hemodynamic and functional status at 1 year and can provide an additional therapeutic option in selected low- or intermediate-risk patients with surgical BVF, although longer term follow-up is necessary.
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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) | 0.001 | 0.001 |
| 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) | 0.001 | 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 it