Abstract 15148: How Reassuring is an Initial Echocardiogram With Normal Coronary Arteries for Patients Presenting With Acute Kawasaki Disease?
Bibliographic record
Abstract
Background: We sought to determine the utility of current echocardiography surveillance recommendations for coronary artery (CA) involvement for children with Kawasaki disease (KD) with normal baseline studies. Methods: The International KD Registry enrolled 1200 patients (36 sites, 7 countries) with a site diagnosis of KD from 01/2020 to 01/2023; 139 with positive/possible COVID-19 infection/exposure and 174 with no echo within 10 days of admission were excluded, leaving 887 patients for analysis of results of serial echos and associated factors. Results: An initial echo was performed within 5 days of admission for 96% and within 10 days of symptom onset for 83% of patients; the max Z score in any CA branch at initial echo was normal (Z <2) 78.9%, dilation (Z 2-<2.5) 6.6%, small aneurysm (CAA; Z 2.5-<5) 10.5%, medium CAA (Z 5-<10) 2.9% and large CAA (Z ≥10) for 1.2% of patients. Higher CA Z score/Z score category were both significantly related to greater time from symptom onset to echo (p<0.001). For those with initial normal CAs, a second echo (median of 16 days after admission) was normal for 94.2%, dilation 1.9%, small CAA 2.7%, medium CAA 0.6%, and large CAA for 0.6%. For those with 2 normal echos, a third echo (median of 44 days after admission) was normal for 97.6%, dilation 1.4%, small CAA 0.5%, and 1 patient each with medium and large CAA. Additionally, after up to 6 normal echos, 3 patients had developed small CAA, 1 medium and 1 large CAA. Overall, a total of 24 (2.8%) patients had large CAA (13 admitted >10 days after symptom onset). Of these, 10 had large CAA evident at initial echo performed at day 0-3 after admission, 9 had lesser involvement at initial echo that then progressed to large CAA, and 5 had normal initial and subsequent echos and then were noted to have large CAA at an echo performed 14, 17, 21, 23 and 53 days after admission (the patient with a large CAA first detected at 53 days had no interim echos performed since their first normal echo). Conclusions: Current recommendations for serial echo assessment are effective in detecting all patients with large CAA. For rare patients, despite a normal initial echo large CAA may nonetheless develop. Additionally, important CA involvement may be evident at presentation (often delayed presentation), precluding prevention.
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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 | 0.003 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| 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".