RESOURCE UTILIZATION FOR CHILDREN WITH NEWLY DIAGNOSED INFLAMMATORY BOWEL DISEASE
Bibliographic record
Abstract
Purpose: To describe resource utilization in the first year after diagnosis for children with IBD in the US and Canada. Methods: Data originated from the Pediatric IBD Collaborative Research Group Registry, a prospective, observational study of children <16 yrs with newly diagnosed IBD. Patient evaluation/treatment are dictated by each physician and not by protocol. Resources studied included: office visits, endoscopy beyond diagnostic procedures, hospitalizations and inpatient therapies. ANOVA and Fisher's exact test (FET) compared data between US and Canada. Results: 385 patients (264 Crohn's disease (CD), 95 ulcerative colitis (UC) and 26 indeterminate colitis (IC)) completed one year of follow-up. Data are shown for CD and UC. 71 patients were hospitalized at least once. Most patients were hospitalized 1-5 days total (mean 11.6, median 5.5, range 1-83). Conclusions: In the first year after IBD diagnosis, 68% of children had ≤5 office visits. Only 10% underwent endoscopy beyond primary diagnostic procedures, <20% were hospitalized and only 4% of CD and 3% of UC patients had a surgical procedure. The resource utilization for these patients was no different in the US compared to Canada, except for greater IV steroid use for hospitalized CD patients in the US.Table: Outpatient visits and endoscopic proceduresTable: Inpatient therapies
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".