Spectrum of Coronary Artery Involvement With Multisystem Inflammatory Syndrome in Children Versus Kawasaki Disease
Bibliographic record
Abstract
Background There is significant overlap in clinical features between multisystem inflammatory syndrome in children (MIS‐C) and Kawasaki disease (KD). We sought to compare the prevalence, severity, and associated factors for coronary artery (CA) involvement. Methods and Results From January 1, 2020 through January 31, 2023, 1191 patients with MIS‐C and 554 patients contemporaneously diagnosed with KD were enrolled into the International Kawasaki Disease Registry. Demographic and clinical features, laboratory values, maximum Z score in any CA branch at any time point, and worst left ventricular ejection fraction, were compared between groups. Factors associated with CA aneurysms (maximum Z score in any CA branch +2.5 or greater) were determined separately for each diagnosis using multivariable logistic regression analyses. The prevalence of CA aneurysms was lower for MIS‐C versus KD (16% versus 25%, respectively; P <0.001) and less severe by size category (1.2% with medium/large CA aneurysm versus 9.6%, respectively). Male sex and lower nadir hemoglobin levels were associated with greater odds of CA aneurysms for both groups. Additional associated factors for KD patients included age<6 months, fewer clinical KD criteria (more incomplete presentation), presentation with shock, and greater total days of fever. There were no additional associated factors for patients with MIS‐C. Using exploratory splines, there was a trend of improvement in Z scores within 30 days of illness for both MIS‐C and KD for CA involvement other than large aneurysms. Conclusions CA involvement for patients with MIS‐C was less prevalent and milder in severity compared with contemporaneous patients with KD, with fewer associated factors, and a high prevalence of regression to a normal luminal dimension.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".