Obesity and Outcomes of Kawasaki Disease and COVID-19–Related Multisystem Inflammatory Syndrome in Children
Bibliographic record
Abstract
Importance: Obesity may affect the clinical course of Kawasaki disease (KD) in children and multisystem inflammatory syndrome in children (MIS-C) associated with COVID-19. Objective: To compare the prevalence of obesity and associations with clinical outcomes in patients with KD or MIS-C. Design, Setting, and Participants: In this cohort study, analysis of International Kawasaki Disease Registry (IKDR) data on contemporaneous patients was conducted between January 1, 2020, and July 31, 2022 (42 sites, 8 countries). Patients with MIS-C (defined by Centers for Disease Control and Prevention criteria) and patients with KD (defined by American Heart Association criteria) were included. Patients with KD who had evidence of a recent COVID-19 infection or missing or unknown COVID-19 status were excluded. Main Outcomes and Measures: Patient demographic characteristics, clinical features, disease course, and outcome variables were collected from the IKDR data set. Using body mass index (BMI)/weight z score percentile equivalents, patient weight was categorized as normal weight (BMI <85th percentile), overweight (BMI ≥85th to <95th percentile), and obese (BMI ≥95th percentile). The association between adiposity category and clinical features and outcomes was determined separately for KD and MIS-C patient groups. Results: Of 1767 children, 338 with KD (median age, 2.5 [IQR, 1.2-5.0] years; 60.4% male) and 1429 with MIS-C (median age, 8.7 [IQR, 5.3-12.4] years; 61.4% male) were contemporaneously included in the study. For patients with MIS-C vs KD, the prevalence of overweight (17.1% vs 11.5%) and obesity (23.7% vs 11.5%) was significantly higher (P < .001), with significantly higher adiposity z scores, even after adjustment for age, sex, and race and ethnicity. For patients with KD, apart from intensive care unit admission rate, adiposity category was not associated with laboratory test features or outcomes. For patients with MIS-C, higher adiposity category was associated with worse laboratory test values and outcomes, including a greater likelihood of shock, intensive care unit admission and inotrope requirement, and increased inflammatory markers, creatinine levels, and alanine aminotransferase levels. Adiposity category was not associated with coronary artery abnormalities for either MIS-C or KD. Conclusions and Relevance: In this international cohort study, obesity was more prevalent for patients with MIS-C vs KD, and associated with more severe presentation, laboratory test features, and outcomes. These findings suggest that obesity as a comorbid factor should be considered at the clinical presentation in children with MIS-C.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".