Long-term outcomes after transcatheter aortic valve implantation in failed bioprosthetic valves
Bibliographic record
Abstract
AIMS: Due to bioprosthetic valve degeneration, aortic valve-in-valve (ViV) procedures are increasingly performed. There are no data on long-term outcomes after aortic ViV. Our aim was to perform a large-scale assessment of long-term survival and reintervention after aortic ViV. METHODS AND RESULTS: A total of 1006 aortic ViV procedures performed more than 5 years ago [mean age 77.7 ± 9.7 years; 58.8% male; median STS-PROM score 7.3% (4.2-12.0)] were included in the analysis. Patients were treated with Medtronic self-expandable valves (CoreValve/Evolut, Medtronic Inc., Minneapolis, MN, USA) (n = 523, 52.0%), Edwards balloon-expandable valves (EBEV, SAPIEN/SAPIEN XT/SAPIEN 3, Edwards Lifesciences, Irvine, CA, USA) (n = 435, 43.2%), and other devices (n = 48, 4.8%). Survival was lower at 8 years in patients with small-failed bioprostheses [internal diameter (ID) ≤ 20 mm] compared with those with large-failed bioprostheses (ID > 20 mm) (33.2% vs. 40.5%, P = 0.01). Independent correlates for mortality included smaller-failed bioprosthetic valves [hazard ratio (HR) 1.07 (95% confidence interval (CI) 1.02-1.13)], age [HR 1.21 (95% CI 1.01-1.45)], and non-transfemoral access [HR 1.43 (95% CI 1.11-1.84)]. There were 40 reinterventions after ViV. Independent correlates for all-cause reintervention included pre-existing severe prosthesis-patient mismatch [subhazard ratio (SHR) 4.34 (95% CI 1.31-14.39)], device malposition [SHR 3.75 (95% CI 1.36-10.35)], EBEV [SHR 3.34 (95% CI 1.26-8.85)], and age [SHR 0.59 (95% CI 0.44-0.78)]. CONCLUSIONS: The size of the original failed valve may influence long-term mortality, and the type of the transcatheter valve may influence the need for reintervention after aortic ViV.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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".