Bileaflet Prosthetic Heart Valve Disease: Numerical Approach Using 3-D Fluid-Structure Interaction Model With Realistic Aortic Root
Bibliographic record
Abstract
Surgical replacement, in the incidence of severely diseased heart valve, is vital in order to restore the normal heart function. Every year around 280,000 valve replacements occur around the world, half of them are bileaflet mechanical heart valves (BMHVs). Despite the remarkable improvement in valve design resulting in minimizing prosthetic valve complications (thromboembolic events or pannus formation), these complications are still possible with BMHV Implantation. As a consequence, an obstruction in one or both MHV leaflets could happen and threaten the patient life. In the present study, an obstructed bileaflet MHV with different percentages of malfunction was simulated assuming 3-D fluid structure interaction (FSI) adapting k-w turbulence as a robust model for the transitional flow using 2.5 million elements and creating a realistic aortic root model with three sinuses. Velocity contours for different percentages of malfunction were compared mainly at B-datum plane and the perpendicular plane to the B-Datum. Also, the development of coherent structures was investigated. Clinically, the maximum pressure gradients were estimated by mimicking the Echo Doppler assumptions (using the simplified Bernoulli equation).
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".