A Novel Assessment Technique for Prosthetic Valve Function: Employing a New Laboratory Approach to Characterize Projected Dynamic Valve Area and Vortex Formation Analysis
Bibliographic record
Abstract
The study of heart valve performance (healthy, diseased, and prosthetic) has traditionally involved the examination of transvalvular characteristics, such as pressure gradients and effective and geometric orifice areas. However, recent research has shown that a key downstream flow characteristic, vortex ring formation, should not be overlooked because quantifying this mechanism provides insight into the assessment of valve performance [1]. Vortex ring formation, which is dependent on the valve design [1], is the roll-up of the shear layers shedding past valve leaflets. Governed by a universal time-scale or formation number (FN) that is based on the jet length to diameter ratio (L/D), vortex ring formation provides insight into the kinematics of optimizing effective fluid transport. It has been shown that growth of the leading vortex ring ceases at a FN between 3.5 and 4.5 in various biological systems [2], but most of these studies have assumed a constant or fixed orifice opening. However, incorporating a time-varying jet diameter rather than the constant valve annulus diameter has recently been identified by Dabiri and Gharib as a key factor in the characterization of vortex ring formation and provides a more complete picture of impulse generation and efficiency in vortical flows [2]. This dynamic formation number is governed by the following equation: (L/D)*=∫0tU¯/D¯dt(1) where U is velocity, D is diameter, t is time, and the overbar indicates a time average. Estimating (L/D)* can serve as a powerful evaluation tool in comparison to conventional methods of FN calculation that use either an averaged diameter or the valve annulus diameter. Ideally suited for unsteady flows, such as the opening phase and leaflet motions in heart valves, (L/D)* can provide insight into assessing the performance of natural and prosthetic heart valves (PHVs).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".