Echocardiographic Features Defining Right Dominant Unbalanced Atrioventricular Septal Defect
Bibliographic record
Abstract
BACKGROUND: Definition and management of right dominant unbalanced atrioventricular septal defect (AVSD) remains challenging because unbalance entails a spectrum of left heart hypoplasia. Previous work has highlighted atrioventricular valve (AVV) index as a reasonable defining echocardiographic measure. We sought to assess which additional echocardiographic features might provide further characterization. METHODS AND RESULTS: From a multi-institutional cohort of complete AVSD, 52 preoperative echocardiograms of patients with presumed right dominant unbalanced AVSD (based on AVV index) and 60 randomly selected preoperative echocardiograms from patients with presumed balanced AVSD were reviewed. Cluster analysis of echocardiographic variables was used to group patients with similar features. Discriminant function analysis was used to explore which variables differentiated these groups. Three groups were identified from the cluster analysis. Echocardiographic variables that differentiated these groups were right ventricle:left ventricle inflow angle, LV width/LV length, left AVV color diameter at smallest inflow, left AVV color diameter at annulus, right AVV overriding left atrium, and LV width. Based on procedures and outcomes, 1 group likely represented balanced patients, whereas 2 groups with similar outcomes likely represented unbalanced patients. The dominant differentiating echocardiographic variable between the 3 cluster groups was the right ventricle:LV inflow angle (partial R²=0.86), defined as the angle between the base of the right ventricle and LV free wall, using the crest of the ventricular septum as apex of the angle. CONCLUSIONS: The angle of right ventricle/LV inflow and other surrogates of inflow may be important defining echocardiographic measures of right dominant unbalanced AVSD, although confirmation is needed.
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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 | 0.003 |
| 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 | 0.001 |
| 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".