Transcatheter valve-in-valve implantation for degenerated bioprosthetic aortic and mitral valves
Bibliographic record
Abstract
INTRODUCTION: Redo surgery still is the treatment of choice for degenerated bioprosthesis. However, as far as elderly patients with concomitant comorbidities are concerned, the standard reoperation carries additional operative risks and, therefore, minimally invasive procedures must be prioritized. AREAS COVERED: During the last ten years, transcatheter procedures in native valves have become a standard technique in several centers with excellent procedural and mid-term results. Similarly, implantation of transcatheter stent-valves within degenerated aortic and mitral bioprosthesis, the 'valve-in-valve' procedure (V-in-V), represents a valid alternative to redo surgery in patients with high-risk surgical profiles. New challenges for V-in-V are the transcatheter stent-valve deployment in hostile targets (stented bioprosthesis with externally mounted leaflets, stentless valves, small bioprostheses), and avoid complications as delayed atrial embolization of mitral implantation and V-in-V thrombosis. Moreover a continuous ameliorated design of the devices on the market and new transcatheter stent-valves are recently developed in order to improve the outcome and safety of V-in-V treatment. Expert commentary: We reviewed the clinical outcomes and the procedural details of published transcatheter aortic and mitral valve-in-valve series focusing, in particular, on data from the Valve-in-Valve International Data registry (VIVID), and we provide a practical guide for valve sizing and stent-valve positioning.
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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 | 0.003 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".