Impact of Z score system on the management of coronary artery lesions in Kawasaki disease
Bibliographic record
Abstract
BACKGROUND: Coronary artery aneurysms are well-described in Kawasaki disease and the Multisystem Inflammatory Syndrome in Children and are graded using Z scores. Three Z score systems (Boston, Montreal, and DC) are widely used in North America. The recent Pediatric Heart Network Z score system is derived from the largest diverse sample to-date. The impact of Z score system on the rate of coronary dilation and management was assessed in a large real-world dataset. METHODS: Using a combined dataset of patients with acute Kawasaki disease from the Children's Hospital at Montefiore and the National Heart, Lung, and Blood Institute Kawasaki Disease Study, coronary Z scores and the rate of coronary lesions (Z ≥ 2.0) and aneurysms (Z ≥ 2.5) were determined using four Z score systems. Agreement among Z scores and the effect on Kawasaki management were assessed. RESULTS: Of 333 patients analysed, 136 were from Montefiore and 197 from the Kawasaki Disease Study. Age, sex, body surface area, and rate of coronary lesions did not differ between the samples. Among the four Z score systems, the rate of acute coronary lesions varied from 24 to 55%. The mean left anterior descending Z scores from Pediatric Heart Network and Boston had a large uniform discrepancy of 1.3. Differences in Z scores among the four systems may change anticoagulation management in up to 22% of a Kawasaki population. CONCLUSIONS: Choice of Z score system alone may impact Kawasaki disease diagnosis and management. Further research is necessary to determine the ideal coronary Z score system.
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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 | 0.011 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 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".