Incidence in pediatric IBD is rising: Help from health administrative data
Bibliographic record
Abstract
Benchimol EI, Guttmann A, Griffiths AM, et al. Increasing incidence of paediatric inflammatory bowel disease in Ontario, Canada: evidence from health administrative data. Gut. 2009;58:1490–1497. The authors aimed, first, to develop and validate a diagnostic algorithm for pediatric inflammatory bowel disease (IBD) using a health administrative database at the Institute for Clinical Evaluation Sciences in Toronto in order to identify subjects with early-onset IBD. This algorithm was then used to assess the incidence and the prevalence of IBD among children in the Ontario region. The database used included: 1) data from all hospital discharges that were reported to the Canadian Institute for Health; 2) billing claims for all physician services from Ontario Health Insurance Plan; and 3) Registered Persons Database (demographic data including region of residence). The authors used the IBD clinical database from SickKids in Toronto to identify patients with childhood-onset IBD in the area of Toronto. With this database the authors identified 183 Toronto children with an IBD diagnosis between 1991 and 1995 to serve as a positive reference standard. In the same time interval more than 930,000 children ages <15 years and who resided in Toronto served as a negative reference standard.
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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 | 0.002 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.004 |
| 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".