Incidence, causes, correlates, and outcome of bioprosthetic valve dysfunction and failure following transcatheter aortic valve implantation
Bibliographic record
Abstract
AIMS: Bioprosthetic valve dysfunction (BVD) is a major concern regarding transcatheter aortic valve implantation (TAVI) durability. We aimed to assess incidence, correlates, causes, and outcome of early to mid-term BVD after TAVI in relation to patient's life expectancy. METHODS AND RESULTS: Consecutive TAVI recipients (2007-20) with a follow-up ≥1 year were prospectively included. BVD and bioprosthetic valve failure (BVF) were assessed according to Valve-Academic-Research-Consortium-3. BVD/BVF and all-cause death served as endpoints. Average life expectancy was calculated from National Open Health Data and patients were stratified according to tertiles (1st: <6.85 years, 2nd: 6.85-9.7 years, 3rd: >9.7 years). Of 1047 patients (81.6 ± 6.8 years old, EuroSCORE II 4.5 ± 2.5), ≥2 follow ups were available from 622 (serial echo cohort). After a median echo follow up of 12.2 months, incidence rates of BVD/BVF were 8.4% (95% confidence interval 6.7-10.3), and 3.5% (2.5-4.9) per valve-year, respectively, without differences between life expectancy tertiles. The incidence of BVD was two-fold higher within the first year of implant (9.9% per valve-year) vs. beyond (4.8% per valve-year). Valve-in-valve procedure and residual stenosis, but not age/life expectancy predisposed for BVD. BVD/BVF were independently associated with outcome for patients in the first [adjusted hazard ratio (AHR) 1.72 (1.06-2.88)/2.97 (1.72-6.22)] and second [AHR 1.96 (1.02-3.73)/2.31 (1.00-5.30)], but not the third tertile of life expectancy (P = n.s.). CONCLUSIONS: In this large prospective observational cohort, early to mid-term BVD after TAVI occurred at the same rate across the spectrum of life expectancy and was associated with increased mortality in patients with short but not in those with the longest life expectancy.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.005 |
| 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".