Management of myocardial infarction in children with Kawasaki disease
Bibliographic record
Abstract
Kawasaki disease is an acute, systemic vasculitis of unknown cause affecting mainly neonates (infants) and young children. Despite treatment during the acute phase with intravenous immunoglobulin and aspirin, up to 5% of those affected will develop coronary aneurysms, predisposing them to thrombotic complications that could result in myocardial infarction and/or death. There are treatment protocols in place for the management of myocardial infarction in adults, but the practical nature of medication is unclear in children. To date, there are no clinical trials or specific recommendations on the dosing of thrombolytic therapy for the treatment of myocardial infarction in Kawasaki pediatric patients. However, there are reports of the use of thrombolytic agents, including streptokinase, urokinase and tissue plasminogen activator, as well as the monoclonal platelet glycoprotein (GP)IIb/IIIa receptor inhibitor, abciximab, that have been used to treat myocardial infarction in children with Kawasaki disease. The outcomes in these reports are varied. This review provides a summary of the available data on the management of children with Kawasaki disease suffering from myocardial infarction or thrombotic complications that can potentially lead to myocardial infarction.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".