Redo aortic valve replacement vs valve-in-valve trans-catheter aortic valve implantation: a UK propensity-matched analysis
Why this work is in the frame
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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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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.010 |
| Bibliometrics | 0.001 | 0.001 |
| 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 it