Long-Term Outcomes of Transcatheter vs Surgical Aortic Valve Replacement: Meta-analysis of Randomized Trials
Bibliographic record
Abstract
Background We aimed to perform a meta-analysis of randomized trials comparing long-term outcomes of patients undergoing transcatheter aortic valve replacement (TAVR) vs surgical aortic valve replacement (SAVR) for severe aortic stenosis. The short-term efficacy and safety of TAVR are proven, but long-term outcomes are unclear. Methods We included randomized controlled trials comparing TAVR vs SAVR at the longest available follow-up. The primary end point was death or disabling stroke. Secondary end points were all-cause mortality, cardiac mortality, stroke, pacemaker implantation, valve thrombosis, valve gradients, and moderate-to-severe paravalvular leaks. The study is registered with PROSPERO (CRD42023481856). Results Seven trials (N = 7785 patients) were included. Weighted mean trial follow-up was 5.76 ± 0.073 years. Overall, no significant difference in death or disabling stroke was observed with TAVR vs SAVR (HR, 1.02; 95% CI, 0.93-1.11; P = .70). Mortality risks were similar. TAVR resulted in higher pacemaker implantation and moderate-to-severe paravalvular leaks compared to SAVR. Results were consistent across different surgical risk profiles. As compared to SAVR, self-expanding TAVR had lower death or stroke risk ( P interaction=.06), valve thrombosis ( P interaction=.06), and valve gradients ( P interaction < .01) but higher pacemaker implantation rates than balloon-expandable TAVR ( P interaction < .01). Conclusions In severe aortic stenosis, the long-term mortality or disabling stroke risk of TAVR is similar to SAVR, but with higher risk of pacemaker implantation, especially with self-expanding valves. As compared with SAVR, the relative reduction in death or stroke risk and valve thrombosis was greater with self-expanding than with balloon-expandable valves.
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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 | 0.030 | 0.043 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.057 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".