Abstract 11464: Spectrum and Associated Factors for Coronary Artery Involvement in Kawasaki Disease versus Multisystem Inflammatory Syndrome in Children Associated With Covid-19
Bibliographic record
Abstract
Introduction: Kawasaki disease (KD) and Multisystem Inflammatory Syndrome in Children (MIS-C) associated with COVID-19 share clinical features and are both associated with coronary artery (CA) involvement. Methods: From January 2020 through January 2022, n=2566 contemporaneous KD, MIS-C and acute COVID-19 pediatric patients from 39 sites in 8 countries were enrolled into the International KD Registry. The study population was confined to 875 MIS-C patients meeting CDC criteria with confirmed or probable COVID-19 infection, and 492 KD patients meeting AHA guideline criteria without COVID-19 infection who had sufficient echo data. CA involvement was defined by maximum Z score in any branch at any timepoint (maxCAZ). Associated factors for each diagnosis were determined with multivariable logistic regression for maxCAZ>2. Results: Median maxCAZ was higher for KD (+1.43) vs MIS-C patients (+1.33; p=0.004). The groups did not differ regarding the incidence of maxCAZ>2 (KD 26% vs MIS-C 24%; p=0.42), although MIS-C patients had less severe Z score categories of involvement (FIGURE). In univariate analyses, higher peak troponin I (p<0.05) and NTproBNP (p=0.06) were associated with maxCAZ>2 for MIS-C but not KD patients. Lower LV ejection fraction was likewise associated with maxCAZ>2 for MIS-C (p=0.009) but not KD patients. For KD patients, independent factors associated with maxCAZ>2 were male sex, age <6 months, greater total days of fever, shock presentation, and higher peak platelet count and CRP (c-statistic 0.69). In contrast, for MIS-C patients the only independent factor associated with maxCAZ>2 was male sex (c-statistic 0.56). Conclusions: Compared to KD patients, MIS-C patients have a similar incidence but lesser severity of CA involvement with few associated factors, male sex being the only one in common. CA involvement was significantly associated with higher cardiac biomarkers and lower LV ejection fraction for MIS-C patients only.
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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 | 0.001 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".