Abstract O.06: Epidemiology of Kawasaki Disease in Canada (2004-2011)
Bibliographic record
Abstract
Introduction: We have previously documented in consecutive triennial systematic surveillances a rise in the incidence of KD in Ontario, Canada between 1995 and 2004 followed by a stabilization at 24-26 cases per 100,000 children <5 year old per year between 2004 and 2009. Previous studies have been limited to the province of Ontario; we sought to determine the incidence of KD across Canada and by province. Methods: We queried the Canadian hospital discharge database (Canadian Institute for Health Information) for hospital admissions associated with a discharge diagnosis of KD (either primary or secondary) between 2004 and 2011. Multiple admissions for a given patient were not counted as separate incident cases unless >2 months from the original admission and associated with IVIG treatment. Denominators were derived from population data from the 2001, 2006 and 2011 Censuses. Results: The annual incidence of KD during the study period was 21.9, 6.8 and 1.1 cases per 100,000 children <5 years, 5-9 years and 10-14 years old, respectively (4,340 cases total). Stratification by region showed the lowest incidence to be in Saskatchewan (11.8/100,000 children <5 year old), followed by Manitoba (17.3), Alberta (17.7), Quebec (18.1), British Columbia (20.6), Atlantic Provinces (22.5) and finally Ontario (27.5, similar to that noted on previous systematic surveillances). The incidence remained stable over the study period, confirming the plateau reached in the previous systematic Ontario surveillance between 2004-2009. An increased incidence was noted for children <5 years old, male gender and winter months. There was a moderate correlation between proportion of the provincial population of Asian descent and KD incidence (r=0.58). Coronary artery aneurysms affected 5.8% of patients, and 1.9% experienced major cardiac complications or had cardiac interventions. Conclusions: The previous increase in the incidence of KD has plateaued, indicating that the true annual incidence fluctuates between 20-22 and 24-27 cases per 100,000 children <5 years for Canada as a whole, and 24-27 cases for the province of Ontario. Differences in annual incidence observed between provinces remain to be explained, but may reflect racial, genetic or environmental factors.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".