Nationwide Temporal Trends in Incidence of Hospitalization and Surgical Intestinal Resection in Pediatric Inflammatory Bowel Diseases in the United States from 1997 to 2009
Bibliographic record
Abstract
BACKGROUND: Data are limited on temporal trends in outcomes of hospitalization and surgery in pediatric Crohn's disease (CD) and ulcerative colitis (UC). Thus, we evaluated the U.S. nationwide temporal trends for incidence of hospitalization and intestinal resection along with associated resource utilization. METHODS: We used the Kids' Inpatient Database (1997, 2000, 2003, 2006, and 2009) to identify all admissions for children aged 18 years or younger with a primary CD (International Classification of Diseases, Ninth Revision [ICD-9]: 555.X) or UC (ICD-9: 556.X) diagnosis or a secondary CD or UC diagnosis and procedural code of intestinal resection. Poisson regression analysis was performed to evaluate time trends in the incidence of hospitalization, intestinal resection, and hospital resource utilization. RESULTS: The annual incidence of hospitalization was 5.7 and 3.5 per 100,000 children for CD and UC, respectively, with significant increases over time for CD (annual percent increase [API], 3.8%; 95% confidence interval [CI], 3.0%-4.5%) and UC (API, 4.5%; 95% CI, 4.3%-4.7%). Median hospital days per hospitalization for CD and UC remained stable, whereas median charge per hospitalization increased for CD (API, 4.1%; 95% CI, 2.6%-5.6%) and UC (API, 4.7%; 95% CI, 3.5%-5.9%). The annual incidence of intestinal resection remained stable for UC at 0.6 per 100,000 children but climbed for CD (API, 2.1%; 95% CI, 0.1-4.2). CONCLUSIONS: The annual incidence of hospitalization is climbing in pediatric inflammatory bowel diseases, accompanied by rising intestinal resection rates for CD and stable colectomy rates for UC. With escalating resource utilization, the economic and health burden of pediatric inflammatory bowel diseases is substantial.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".