Kawasaki Disease at the Extremes of the Age Spectrum
Bibliographic record
Abstract
OBJECTIVE: We sought to determine outcomes of Kawasaki disease (KD) and to explore factors associated with poor clinical outcomes for patients diagnosed outside the age range of 1 to 4 years. METHODS: A retrospective review of data for all patients seen between January 1990 and April 2007 was performed. Patients were stratified into 5 groups on the basis of age at diagnosis. RESULTS: A total of 1374 patients were identified; 61 (4%) were <6 months of age at diagnosis, 114 (8%) 6 months to <1 year, 854 (62%) 1 to 4 years, 258 (19%) 5 to 9 years, and 87 (6%) >9 years. Patients <1 year of age and those >9 years of age were more likely to have coronary artery abnormalities than were patients diagnosed between 1 and 4 years of age. Patients diagnosed between the ages of 5 and 9 years were at the lowest risk. Patients at both extremes of the age spectrum were more likely to present with <4 of the classic KD features, but only those <6 months or >5 years of age were at increased risk of being diagnosed >12 days after illness onset. Patients <6 months of age had lower albumin levels, and those <1 year of age had higher white blood cell and platelet counts, all of which are known predictors of coronary artery abnormalities. Patients >9 years of age were less likely to receive intravenous immunoglobulin treatment. CONCLUSION: Outcomes for children diagnosed with KD at either extreme of the age spectrum are suboptimal, although the associated factors are different.
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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 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".