European consensus-based recommendations for the diagnosis and treatment of Kawasaki disease – the SHARE initiative
Bibliographic record
Abstract
OBJECTIVES: The European Single Hub and Access point for paediatric Rheumatology in Europe initiative aimed to optimize care for children with rheumatic diseases. Kawasaki disease (KD) is the most common cause of acquired heart disease in children and an important cause of long-term cardiac disease into adulthood. Prompt diagnosis and treatment of KD is difficult due to the heterogeneity of the disease but is crucial for improving outcome. To date, there are no European internationally agreed, evidence-based guidelines concerning the diagnosis and treatment of KD in children. Accordingly, treatment regimens differ widely. The aim of this study is to provide consensus-based, European-wide evidence-informed recommendations for diagnosis and treatment of children with KD. METHODS: Recommendations were developed using the EULAR's standard operating procedures. An extensive systematic literature search was performed, and evidence-based recommendations were extrapolated from the included papers. These were evaluated by a panel of international experts via online surveys and subsequently discussed in three consensus meetings, using nominal group technique. Recommendations were accepted when ⩾80% agreed. RESULTS: In total, 17 recommendations for diagnosis and 14 for treatment of KD in children were accepted. Diagnostic recommendations included laboratory and imaging workup for complete as well as incomplete KD. Treatment recommendations included the importance of early treatment in both complete and incomplete KD, use of intravenous immunoglobulin, aspirin, corticosteroids for high-risk cases, and other treatment options for those with resistant disease. CONCLUSION: The Single Hub and Access point for paediatric Rheumatology in Europe initiative provides international evidence-based recommendations for diagnosing and treating KD in children, facilitating improvement and uniformity of care.
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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 | 0.073 | 0.106 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.010 |
| Bibliometrics | 0.012 | 0.007 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.008 | 0.006 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".