Degenerated Transcatheter Aortic Valve Replacement: Investigation and Management Options
Bibliographic record
Abstract
With the expansion of transcatheter aortic valve replacement (TAVR) to younger and lower-surgical-risk patients, many younger and less comorbid patients will be treated with TAVR and are expected to have a life expectancy that will exceed the durability of their transcatheter heart valve. Consequently, the number of patients requiring reintervention will undoubtedly increase in the near future. Redo-TAVR and TAVR explantation followed by surgical aortic valve replacement are the different therapeutic options in the event of bioprosthetic valve failure and the need for reintervention. Patients often anticipate being able to benefit from a redo-TAVR in the event of bioprosthetic valve failure after TAVR, despite the lack of long-term data and the risk of unfavourable anatomy. Our understanding of the feasibility of redo-TAVR is constantly improving thanks to bench test studies and growing worldwide experience. However, much remains unknown. In clinical practice, one of the heart team's objectives is to anticipate the need to reaccess the coronary arteries and implant a second or even a third valve when life expectancy may exceed the durability of the transcatheter heart valve. In this review, we address key definitions in the diagnosis of structural valve deterioration and bioprosthetic valve failure, as well as patient selection and procedural planning for redo-TAVR to reduce periprocedural risk, optimise hemodynamic performance, and maintain coronary access. We describe the bench testing and literature in the redo-TAVR and TAVR explantation fields.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".