Factors Associated With Shock at Presentation in Kawasaki Disease Versus Multisystem Inflammatory Syndrome in Children Associated With Covid-19
Bibliographic record
Abstract
BACKGROUND: While clinical overlap between Kawasaki disease (KD) and multisystem inflammatory syndrome in children (MIS-C) has been evident, information regarding those presenting with shock has been limited. We sought to determine associations with shock within and between diagnosis groups. METHODS: The International KD Registry enrolled contemporaneous patients with either KD or MIS-C from 39 sites in 7 countries from January 1, 2020, to January 1, 2023. Demographics, clinical features and presentation, management, laboratory values, and outcomes were compared between the diagnosis and shock groups. RESULTS: Shock at presentation was noted for 19 of 672 KD patients (2.8%) and 653 of 1472 MIS-C patients (44%; P < 0.001). Within both groups, patients with shock were significantly more likely to be admitted to the intensive care unit, to receive inotropes, and to have greater laboratory abnormalities indicative of hyperinflammation and organ dysfunction, including abnormal cardiac biomarkers. Patients with KD and shock had a greater maximum coronary artery z score (median +2.62) vs KD patients without shock (+1.36; P < 0.001) and MIS-C patients with shock (+1.45 [vs +1.32 for MIS-C patients without shock]; P < 0.001). They were also more likely to have large coronary artery aneurysms. In contrast, MIS-C patients with shock had lower left ventricular ejection fraction (mean 51.6%) vs MIS-C patients without shock (56.6%; P < 0.001) and KD patients with shock (56.7% [vs 62.8% for KD patients without shock]; P = 0.04). CONCLUSIONS: Although patients with KD presenting with shock are clinically similar to patients with MIS-C, especially those with shock, they have more severe coronary artery involvement, whereas MIS-C patients with shock have lower left ventricular ejection fraction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".