Abstract 18044: Predictors of Bicuspid Aortic Valve Associated Aortopathy in Pediatric Patients
Bibliographic record
Abstract
Bicuspid aortic valve (BAV) is the most common congenital heart disease and is commonly associated with significant ascending aorta dilation. Valve morphology and function have been proposed as potential risk factors; however evaluating their role is difficult, as BAV morphology and valve function are inherently related. Our objective was to determine whether BAV morphology and function are independently associated with ascending aorta dilation in pediatric patients. We performed a multicenter, retrospective, cross-sectional study of pediatric patients with BAV that were followed after 2003. The last patient echocardiogram prior to valve intervention was analyzed for BAV morphology, presence and severity of aortic stenosis (AS) and insufficiency (AI), and aortic root and ascending aorta dimensions. The relationship of potential risk factors to ascending aorta dimensions at different ages was determined using linear regression. Data was obtained from 1725 patients (68% male). The most common BAV morphology was right-left (R-L) coronary cusp fusion (65%) followed by right-non (R-N) fusion (34%) and left-non fusion (1%). Fourteen percent of patients had at least moderate AS and 7% had at least moderate AI. R-L fusion was associated with coarctation (55%), while R-N fusion was less associated with coarctation (19%) and more associated with valve dysfunction (24% and 12% with at least moderate AS and AI). Twenty-seven percent of patients had significant ascending aorta dilation (Z score >3). AS and AI were associated with more significant ascending aorta dilation and a faster Z-score progression over time. R-N fusion was associated with ascending aorta dilation; however, when valves with AS and AI were excluded, there were no differences related to morphology. In patients with no AS or AI, 15% had significant ascending aorta dilation. In this large pediatric cohort of patients with BAV, we show that valve morphology is not independently associated with ascending aorta dilation. Valve dysfunction (both AS and AI) is associated with more significant dilation; however, even in valves with normal function, there is significant ascending aorta dilation. We suggest that there is an inherent arterial abnormality, possibly modified by aortic flow patterns.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".