Early and late outcomes of surgical aortic valve replacement with sutureless and rapid‐deployment valves versus transcatheter aortic valve implantation: Meta‐analysis with reconstructed time‐to‐event data of matched studies
Bibliographic record
Abstract
Sutureless/rapid-deployment (SURD) valves are options different from the stented prostheses included in the pivotal trials comparing surgical aortic valve replacement (AVR) and transcatheter aortic valve implantation (TAVI). We performed a meta-analysis with reconstructed time-to-event data of matched studies published by November 2021 to compare SURD-AVR and TAVI. Primary endpoints were 30-day mortality and overall survival in the follow-up. Secondary endpoints included: 30-day stroke, acute kidney injury (AKI), major bleeding, permanent pacemaker implantation (PPI), paravalvular leak (PVL), prosthesis-patient mismatch (PPM), postoperative aortic valve area (AVA), and mean gradients. Ten studies met our eligibility criteria, including a total of 5134 patients (2567 underwent SURD-AVR and 2567 underwent TAVI). Pooled risk of 30-day mortality did not favor any group (odds ratio [OR]: 0.69; 95% confidence interval [CI]: 0.31-1.53; p = 0.360). Patients undergoing SURD-AVR had lower risk of PVL (OR: 0.09; 95% CI: 0.05-0.17; p < 0.001). No statistically significant differences were observed for 30-day stroke, AKI, major bleeding, PPI, PPM, and postoperative AVA. In the follow-up, we observed a higher risk of mortality (hazard ratio: 1.74; 95% CI: 1.26-2.40; p < 0.001) with TAVI. Patients who underwent SURD-AVR experienced better survival, however, the interpretation of these results warrant caution due to the fact that SURD-AVR patients tended to be younger than TAVI patients. Structural heart surgeons and interventional cardiologists should consider initial risk and life expectancy when referring patients for one approach over the other.
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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 | 0.010 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.042 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".