Mechanics Post-TAVR for Trileaflet vs Bicuspid Aortic Valves
Bibliographic record
Abstract
BACKGROUND: Bicuspid aortic valve (BAV) disease is the most common congenital heart defect and is associated with elliptical openings and excess calcification. Limited data are available on long-term efficacy of transcatheter aortic valve replacement (TAVR) for BAV patients. OBJECTIVES: The purpose of this study was to compare simulated mechanical metrics post-TAVR between BAV and trileaflet patients with calcific aortic stenosis. METHODS: Pre-TAVR computed tomography scans of trileaflet (n = 22) and BAV (n = 25) were used to segment the aortic valve. Simulated balloon-expandable stent deployment was performed from a previously developed protocol. The bioprosthetic leaflets were then pressurized under a physiological pressure. Stent waist expansion ratio, aspect ratio (AR), leaflet systolic normalized geometric orifice area (GOA), and maximum leaflet diastolic stress were measured. RESULTS: BAVs had lower waist expansion ratio (87.8% ± 2.6% vs 89.4% ± 1.4%; P < 0.001), lower waist AR (94.6% ± 2.8% vs 98.2% ± 1.0%; P < 0.001), lower normalized GOA (88.9% ± 0.8% vs 89.5% ± 0.7%; P < 0.01), and higher maximum stress (2.81 ± 0.44 vs 2.29 ± 0.25 MPa; P < 0.001) on average compared to trileaflet patients, respectively. Within the BAV group, calcium volume was correlated with waist AR (r = -0.75, P < 0.001), normalized GOA (r = -0.68, P < 0.001), and maximum stress (r = 0.66, P < 0.001). CONCLUSIONS: Balloon-expandable TAVR for BAV has worse simulated mechanical metrics compared to TAVR for trileaflet aortic valve patients and is associated with high calcium volume.
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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) | 0.000 | 0.001 |
| 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".