Transcatheter valve‐in‐valve versus redo surgical aortic valve replacement for the treatment of degenerated bioprosthetic aortic valve: A systematic review and meta‐analysis
Bibliographic record
Abstract
Abstract Objective To determine the safety and efficacy of valve‐in‐valve transcatheter aortic valve replacement (ViV) versus redo surgical aortic valve replacement (SAVR) for the treatment of previously failed aortic bioprostheses. Background Valve‐in‐valve has emerged as a treatment option for patients with a failed aortic bioprosthesis. Evidence for safety and efficacy remains limited to small studies. Methods Medline and Embase were searched to 2017 for studies that directly compared ViV to redo SAVR. A random effects meta‐analysis was performed. Results Four unadjusted ( n = 298) and two propensity‐matched ( n = 200) observational studies were included. Valve‐in‐valve patients were 2.85‐years older ( P = 0.03) and were 23% higher in predicted mortality risk (ratio of means: 1.23, 95% confidence interval (95%CI): 1.02–1.48). There was no difference in peri‐operative mortality (4.4% vs. 5.7%, P = 0.83; I 2 = 0%) or late mortality, reported at median one year follow‐up (incident rate ratio (IRR) 0.93, 95%CI: 0.74–1.16, P = 0.51, I 2 = 0%) between ViV and redo SAVR. The incidence of permanent pacemaker implantation (8.3% vs 14.6%; P = 0.05; I 2 = 0%) and dialysis (3.2% vs. 10.3%; P = 0.03; I 2 = 0%) were lower in ViV. There was a reduction in the incidence of severe patient‐prosthesis mismatch (3.3% vs 13.5%; P = 0.03; I 2 = 0%) and mild or greater paravalvular leak (5.5% vs 21.1%; P = 0.03; I 2 = 37%) in the redo SAVR group compared to ViV. Conclusions Despite higher predicted surgical risk of ViV patients, there was no difference in mortality but less permanent pacemaker implantation and dialysis compared to redo SAVR. Choice of treatment must be individualized for both anatomical and patient risk factors; in high risk patients with favorable previous prosthesis size, valve‐in‐valve may be preferred.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.026 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".