Redo aortic valve replacement vs valve-in-valve trans-catheter aortic valve implantation: a UK propensity-matched analysis
Bibliographic record
Abstract
This study sought to compare the morbidity and mortality of redo aortic valve replacement (redo-AVR) versus valve-in-valve trans-catheter aortic valve implantation (valve-in-valve TAVI) for patients with a failing bioprosthetic valve. A multicenter UK retrospective study of redo-AVR or valve-in-valve TAVI for patients referred for redo aortic valve intervention due to a degenerated aortic bioprosthesis. Propensity score matching was performed for confounding factors. From July 2005 to April 2021, 911 patients underwent redo-AVR and 411 patients underwent valve-in-valve TAVI. There were 125 pairs for analysis after propensity score matching. The mean age was 75.2±8.5 years. In-hospital mortality was 7.2% (n=9) for redo-AVR versus 0 for valve-in-valve TAVI, p=0.002. Surgical patients suffered more post-operative complications, including intra-aortic balloon pump support (p=0.02), early re-operation (p<0.001), arrhythmias (p<0.001), respiratory and neurological complications (p=0.02 and p=0.03) and multi-organ failure (p=0.01). The valve-in-valve TAVI group had a shorter intensive care unit and hospital stay (p<0.001 for both). However, moderate aortic regurgitation at discharge and higher post-procedural gradients were more common after valve-in-valve TAVI (p<0.001 for both). Survival probabilities in patients who were successfully discharged from the hospital were similar after valve-in-valve TAVI and redo-AVR over the 6-year follow-up (log-rank p=0.26). In elderly patients with a degenerated aortic bioprosthesis, valve-in-valve TAVI provides better early outcomes as opposed to redo-AVR, although there was no difference in mid-term survival in patients successfully discharged from the hospital.
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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 | 0.002 | 0.008 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".