Time-to-event analysis of the long-term outcome in trials comparing transcatheter and surgical aortic valve implantation: A meta-analysis.
Bibliographic record
Abstract
OBJECTIVE: Indications for TAVI have been widened, although long-term device efficacy is still unclear. We aimed to compare the effectiveness of transcatheter aortic valve implantation (TAVI) vs. surgical aortic valve replacement (SAVR) on a composite of death from any cause or stroke at 5-year follow-up according to risk profiles. METHODS: We performed a systematic literature review for randomized control trials (RCTs) comparing TAVI or SAVR. The primary endpoint was the composite of all-cause mortality or stroke at follow-up. Hazard ratios (HRs) and restricted mean survival time (RMST) differences within high, intermediate and low-risk profiles were estimated by reconstructing time-to-event data from these Kaplan-Meier curves. RESULTS: Eight trials were included (9811 participants). The incidence of composite endpoint increased concordantly with higher baseline risk profiles for both treatments. A time-variant effect was present with transcatheter superior to surgery early, as supported by a cumulative additional time-to-event of 0.77 months at 4 years driven by the high-risk group that is attenuated at 60 months. The benefit of the transcatheter approach increased over time up to 5 years in high-risk patients (RMST difference = 2.39; 95 %CI = -0.23;5.02; p-value = 0.07), while the benefit of the transcatheter approach in intermediate and low-risk patients showed a quadratic association with a smaller increase and attenuation of the observed benefit after 60 months postintervention (low-risk = 0.86; 95 %CI = -0.11,1.84; p-value 0.09; intermediate = 0.45; 95 %CI = -0.66;1.56; p-value = 0.42). CONCLUSIONS: Although an initial benefit of TAVI over SAVR, there are no significant differences at 5 years follow-up independently from the risk profile.
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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 | 0.024 | 0.043 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.052 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".