Changes in surgical and hospitalization rates in pediatric inflammatory bowel disease in Ontario, Canada (1994-2007).
Bibliographic record
Abstract
Changes to the treatment of children with IBD over the past decade may have resulted in changes in outcomes. We used a large, population-based cohort of pediatric IBD patients to describe trends in medication use, associated health services (physician visits) and outcomes (hospitalization and surgical rates) between 1994-2007 in all children diagnosed with IBD in Ontario. A validated algorithm (Benchimol et al., Gut, 2009) identified all children <18 years diagnosed 1994-2004 with IBD within Ontario's health administrative data comprising all legal residents of Canada's most populous province. Patients were grouped by era of diagnosis (1994-1997, 1998-2000, 2001-2004). Eras were chosen a priori to assess changes in care since the 2000 publication of a trial showing the efficacy of immunomodulators in pediatric Crohn's disease (CD) (Markowitz et al., Gastroenterology, 2000). The earliest group had 3-year outcomes prior to 2000, the middle group straddled 2000, and the latest era group were diagnosed and treated after 2000. Trends in outpatient care provided by physician specialty, hospitalization rates, and risk of surgery within 3 years of diagnosis were evaluated for all children. Medication use in patients on social assistance was assessed. Chi square or McNemar tests evaluated changes in proportions by era group. Poisson and logistic regression multivariable models tested the association between era and hospitalizations and surgery.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".