Non-invasive determination of transcatheter pressure gradient in stenotic aortic valves: An analytical model
Bibliographic record
Abstract
Aortic stenosis (AS), in which the opening of the aortic valve is narrowed, is the most common valvular heart disease. Cardiac catheterization is considered the reference standard for definitive evaluation of AS severity, based on instantaneous systolic value of transvalvular pressure gradient (TPG). However, using invasive cardiac catheterization might carry high risks knowing that undergoing multiple cardiac catheterizations for follow-up in patients with AS is common. The objective of this study was to suggest an analytical description of the AS that estimates TPG without a need for high risk invasive data collection. For this purpose, Navier-Stokes equation coupled with the elastic-deformation equation was solved analytically. The estimated TPG resulted from the suggested analytical description was validated against published in vivo and in vitro measurement data. Very good concordances were found between TPG obtained from the analytical formulation and in vivo (maximum root mean square error: 3.8 mmHg) and in vitro (maximum root mean square error: 9.4 mmHg). The analytical description can be integrated to non-invasive imaging modalities to estimate AS severity as an alternative to cardiac catheterization to help preventing its risks in patients with AS.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".