Bicuspid aortic valve disease associates with abnormal wall shear stress, viscous energy loss, and pressure drop within the ascending thoracic aorta
Bibliographic record
Abstract
Abstract Introduction We use 4D Flow MRI to (1) investigate the effects of bicuspid aortic valve (BAV) disease on downstream pressure drop (PD), wall shear stress (WSS), and viscous energy loss (EL) in the ascending aorta (AAo) and (2) explore the associations between AAo diameter and PD, WSS, and EL. Hypothesis BAV patients show increased PD, WSS, and EL in the AAo compared to age-matched controls Methods 32 healthy controls (41±15 y, 10 female) and 53 BAV patients (44±16 y, 19 female) underwent cardiac MRI at 3T, inclusive of cine imaging and 4D flow. Cross sections were placed along segmented aortas at the: left ventricular outflow tract (LVOT), sinuses of Valsalva (SOV), mid-ascending aorta (MAA), and proximal to first aortic branch (AA1). Locations were analyzed for (i) net flow, (ii) aortic diameter (normalized to BSA), (iii) systolic PD (referenced to LVOT), (iv) systolic EL (measured within LVOT-AA1 volume and normalized by LVOT net flow; mW/mL), and (v) systolic WSS. Sub-vectors of WSS, axial (WSSax) and circumferential (WSScirc), were also analyzed. Results In comparison to controls, BAV patients showed greater PD (e.g. MAA: 9.5±8.0 vs. 2.8±2.4mmHg; p<0.01), EL (0.09±0.05 vs. 0.04±0.01 mW/mL; p≤0.01), and WSScirc (e.g. MAA: 0.3±0.1 vs. 0.2±0.06 Pa; p≤0.01) throughout the AAo (Table 1 and Fig. 1). BAV patients exhibited significantly lower WSS and WSSax only at the SOV. In univariate analyses, AAo diameter was inversely correlated with WSS (R=−0.32, p<0.01) and WSSax (R=−0.51, p≤0.01). In multivariate analyses, AAo diameter was associated with WSS (β=−0.36, p<0.01) and WSSax (β=−0.26, p<0.01). Conclusions BAV patients demonstrate significantly increased PD, EL, and WSScirc in the AAo, and an inverse association between AAo diameter and WSS measures. Funding Acknowledgement Type of funding source: Public Institution(s). Main funding source(s): Alberta Health Services
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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 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".