Balloon versus self‐expandable transcatheter aortic valve implantation for bicuspid aortic valve stenosis: A meta‐analysis of observational studies
Bibliographic record
Abstract
BACKGROUND: There is a rising trend for transcatheter aortic valve implantation (TAVI) in bicuspid aortic stenosis patients. Data on the use of self-expandable (SEV) vs. balloon-expandable (BEV) valves in these patients are scarce. Therefore, we systematically compared clinical outcomes in bicuspid aortic stenosis patients treated with SEV and BEV. METHODS: Data were extracted from PubMed/MEDLINE, EMBASE, CENTRAL/CCTR, ClinicalTrials.gov, SciELO, LILACS, Google Scholar and reference lists of relevant articles. Eight studies published from 2013 to 2020 including a total of 1,080 patients (BEV: n = 620; SEV: n = 460) were selected. Primary endpoints were procedural, 30-day and 1-year mortality. Secondary endpoints were new pacemaker implantation, annular rupture, coronary obstruction, moderate-to-severe paravalvular leak, need of second valve, stroke and acute kidney injury. RESULTS: We found no statistically significant difference in mortality between patients treated with BEV vs. SEV during index procedure, at 30 days and at 1 year. BEVs showed a statistically significant higher risk of annulus rupture (2.5%) in comparison with SEV (0%) (OR 5.81 [95% CI, 3.78-8.92], p < .001). New generation BEVs were also associated with significantly less paravalvular leak when compared to new generation SEVs (OR 0.08 [95% CI, 0.02-0.35], p = .001). CONCLUSIONS: This meta-analysis of observational studies of TAVI for bicuspid valves, showed no difference in short- and mid-term TAVI mortality with BEVs and SEVs. BEVs presented a higher risk of annular rupture in comparison with SEV.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.118 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".