Abstract 160: Angiography Based Comparison of Echocardiography Z-value Equations for the Case Definition of Coronary Artery Dilatation Following Kawasaki Disease
Bibliographic record
Abstract
Introduction: Echo-based coronary artery (CA) Z-value is the current standard for the case definition of CA dilatation (Z>2.5) in KD. Extrapolating Z-value equations to selective angiography has not been evaluated. CA to aortic valve (AV) ratio is stable versus BSA (Figure). Methods: CA measurements from selective angiography were compared to echo measurements within 3 months interval, late after KD. Measurements were performed 3-5 mm from CA ostium for patients without aneurysms, and proximal to the aneurysm for the remainder. The AV was measured in the echo long axis and the angio frontal views. Z-values and CA/AV ratios were compared between angio and echo measurements. Results: There were 22 cases with and 55 without CA sequelae. Echo measurements overestimated the smallest CA segments (intercept 0.75 mm), with an error attenuation for larger coronaries (slope 0.74, r 2 0.45). In contrast, CA/AV ratio had a better correlation for all CA size range (intercept 0.04, slope 0.87, r2 0.55). There was a disagreement between echo and angio for the case definition of coronary dilatation for the Z-value equations (p value 0.02 and 0.04), but not for the CA/AV ratio (p value 0.1 and 0.27). The best sensitivity and specificity of echo to predict angio-based CA status were obtained with the CA/AV (100 and 93 percent for the right and 50 and 87 percent for the left coronary, versus 36 and 93 percent and 44 and 87 percent, respectively). Conclusion: CA/AV is a better representative of the angiographic CA status compared to echocardiography based Z-value calculations.
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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 | 0.009 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".