Stent frame deformation of self-expanding transcatheter heart valves in bicuspid aortic stenosis and impact on valve performance
Bibliographic record
Abstract
AIMS: To evaluate stent frame expansion and ellipticity of the Evolut™ transcatheter heart valve (THV) and its subsequent impact on valve performance in patients with bicuspid aortic stenosis (AS) using pre- and post-procedural cardiac computed tomography (CT). In transcatheter aortic valve implantation (TAVI) for native bicuspid AS, concerns arise regarding the risk for reduced stent frame expansion and increased ellipticity compared with valves implanted in tricuspid AS. The implications of stent frame under-expansion and eccentricity on THV performance remain unclear. METHODS AND RESULTS: This multi-centre registry included patients with bicuspid AS who underwent TAVI using the self-expanding Evolut™ THV and who had pre- and post-TAVI CT. Stent frame expansion and ellipticity were assessed at the inflow (nodes 0-1) and leaflet level (nodes 5-6). THV performance was evaluated by assessing mean transprosthetic gradient, paravalvular leak, and hypoattenuated leaflet thickening. Among 175 patients included, the inflow level of the Evolut THV had greater stent frame under-expansion (79.9% ± 6.7% vs. 95.4% ± 3.1% and P < 0.001) and ellipticity (1.3 ± 0.3 vs. 1.2 ± 0.1 and P < 0.001) compared to the leaflet level. Leaflet level expansion was unaffected by expansion or ellipticity at the inflow level; however, leaflet level ellipticity increased significantly with inflow under-expansion <75% (P = 0.002) and inflow ellipticity ≥1.3 (P < 0.001). Neither inflow under-expansion nor ellipticity impacted hemodynamic valve performance or leaflet thickening at short-term follow-up. CONCLUSION: The self-expanding Evolut™ THV demonstrates consistent valve performance in bicuspid AS. Stent frame under-expansion and ellipticity at the inflow level do not compromise valve haemodynamics or contribute to leaflet thickening at short-term follow-up.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.005 |
| Bibliometrics | 0.000 | 0.000 |
| 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".