The Effect of Beta-Blockers on Hemodynamic Parameters in Patient-Specific Blood Flow Simulations of Type-B Aortic Dissection: An Virtual Study
Bibliographic record
Abstract
Abstract Type-B aortic dissection (AD) is one of the greatest complex and fatal conditions with co-occurring disorders, challenging to treat. The initial treatment for patients presenting with AD is medical intervention to stabilize the condition. In the present study, a patient-specific geometry of type-B AD is generated from computed tomography images, and a three-element Windkessel lumped parameter model is implemented at the outlets to realistic boundary conditions. According to the physiological response of the antihypertensive drugs in the reduction of aortic blood flow and heart rate, three case studies with different heart rates have been created. Hemodynamic distributions including wall shear stress indicators, velocity and pressure are investigated and compared in each model. Results show that there is a considerable reduction in pressure furthermore, time-averaged wall shear stress (TAWSS) values decreased by 25% and 30%, respectively. Main goal is to critically analysis the use of biomechanical and computational simulation tools to measure hemodynamic parameters in the absence and presence of antihypertensive drugs. It would be of significant use to clinicians to improve diagnostic and treatment planning.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".