Impact of Paravalvular Leak on Outcomes After Transcatheter Aortic Valve Implantation: Meta-Analysis of Kaplan-Meier-derived Individual Patient Data
Bibliographic record
Abstract
Background: Paravalvular leak (PVL) after transcatheter aortic valve implantation (TAVI) is frequent and the impact of mild PVL on outcomes remains uncertain. Our study aimed to evaluate the impact of PVL on TAVI outcomes. Methods: To analyze late outcomes of patients after TAVI according to the presence and severity of PVL, PubMed/MEDLINE, EMBASE and Google Scholar were searched for studies that reported rates of all-cause mortality/survival and/or rehospitalization and/or cardiovascular mortality accompanied by at least one Kaplan-Meier curve for any of these outcomes. We adopted a 2-stage approach to reconstruct individual patient data based on the published Kaplan-Meier graphs. Results: < 0.001) during follow-up. Conclusions: Patients with PVL, even if mild, experience higher risk of all-cause mortality, rehospitalization, and cardiovascular mortality following TAVI. These findings provide support to the implementation of procedural strategies to prevent any degree of PVL at the time of TAVI.
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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 | 0.020 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.040 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 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".