Flow Dynamics in Children With Bicuspid Aortic Valve: A Blood Speckle Tracking Study
Bibliographic record
Abstract
OBJECTIVE: Bicuspid aortic valve (BAV) is associated with progressive aortic dilation. Although the etiology is complex, altered flow dynamics is thought to play an important role. Blood speckle tracking (BST) allows for visualization and quantification of complex flow, which could be useful in identifying patients at risk of root dilation and could aid in surgical planning. The aims of this study were to assess and quantify flow in the aortic root and left ventricle using BST in children with bicuspid aortic valves. METHODS AND RESULTS: A total of 38 children <10 y of age were included (24 controls, 14 with BAV). Flow dynamics were examined using BST in the aortic root and left ventricle. Children with BAV had altered systolic flow patterns in the aortic root and higher aortic root average vorticity (25.9 [23.4-29.2] Hz vs. 17.8 [9.0-26.2] Hz, p < 0.05), vector complexity (0.17 [0.14-0.31] vs. 0.05 [0.02-0.13], p < 0.01) and rate of energy loss (7.9 [4.9-12.1] mW/m vs. 2.7 [1.2-7.4] mW/m, p = 0.01). Left ventricular average diastolic vorticity (20.9 ± 5.8 Hz vs. 11.4 ± 5.2 Hz, p < 0.01), kinetic energy (0.11 ± 0.05 J/m vs. 0.04 ± 0.02 J/m, p < 0.01), vector complexity (0.38 ± 0.1 vs. 0.23 ± 0.1, p < 0.01) and rate of energy loss (11.1 ± 4.8 mW/m vs. 2.7 ± 1.9 mW/m, p < 0.01) were higher in children with BAV. CONCLUSION: Children with BAV exhibit altered flow dynamics in the aortic root and left ventricle in the absence of significant aortic root dilation. This may represent a substrate and potential predictor for future dilation and diastolic dysfunction.
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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".