Abstract 9861: Establishing Normal Pediatric Aortic Valve Cusp Effective Height Utilizing the Pediatric Heart Network Normal Echo Z Score Project Echocardiograms
Bibliographic record
Abstract
Introduction: Standard echocardiographic dimensions provide little geometric insight into aortic valve (AV) function. The height difference between cusp insertion and free edge, known as AV cusp effective height (eH), can be assessed from the parasternal long axis view and is a surrogate measure of leaflet geometry. This is useful data when planning valve repair although normal values and methods of indexing eH have not been established in pediatric patients. Images from the Pediatric Heart Network (PHN) Normal Echocardiogram Database were analyzed to establish normal pediatric eH ranges and to assess relationship to typical AV and aortic root measures, age, and body size. Methods: AV eH and annulus diameter were retrospectively measured from 600 PHN echocardiograms divided into equal sized groups based on categories of age, sex, and race proportions in the primary study. Subset size was determined utilizing similar methods and presumed margin of error to primary study. Normal ranges were calculated and eH was compared to PHN AV annulus and aortic root dimensions, age groups, and BSA using Pearson correlation. Interobserver and intraobserver reliability was assessed. Regression equations were created using BSA and/or annulus diameter as the independent variables. Results: AV eH increases predictably with age in children (Fig 1). It correlates strongly with aortic dimensions (all r>0.82) and indexes incorporating BSA 0.5 (r=0.85). It is reproducible, with good interobserver (ICC=0.66, 0.11-0.85) and excellent intraobserver (ICC=0.82, 0.74-0.88) reliability. Regression equation created is eH=0.7+5.74* BSA 0.5 . Conclusions: Normal eH correlates well with age, standard aortic dimensions, and BSA 0.5 in healthy children and regression equations can be used to predict mean eH values in this population. Understanding these relationships will help in evaluating patient-specific valvular morphology when developing a surgical repair strategy.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".