Rising post-colectomy complications in children with ulcerative colitis despite stable colectomy rates in United States
Bibliographic record
Abstract
BACKGROUND AND AIMS: In children with ulcerative colitis, data on temporal colectomy trends and in-hospital post-colectomy complications are limited. Thus, we evaluated time trends in colectomy rates and post-colectomy complications in children with ulcerative colitis. METHODS: We identified all children (≤18years) with a diagnosis code of ulcerative colitis (ICD-9: 556.X) and a procedure code of colectomy (ICD-9: 45.8 and 45.7) in the Kids' Inpatient Database for 1997, 2000, 2003, 2006 and 2009. The incidence of colectomies for pediatric ulcerative colitis was calculated and Poisson regression analysis was performed to evaluate the change in colectomy rates. In-hospital postoperative complication rates were assessed and predictors for postoperative complications were evaluated using multivariate logistic regression. RESULTS: The annual colectomy rate in pediatric ulcerative colitis was 0.43 per 100,000person-years, which was stable throughout the study period (P>.05). Postoperative complications were experienced in 25%, with gastrointestinal (13%) and infectious (9.3%) being the most common. Postoperative complication rates increased significantly by an annual rate of 1.1% from 1997 to 2009 (P=.01). However, other independent predictors of postoperative complications were not identified. Patients with postoperative complications had significantly longer median length of stay (14.3days vs 8.2days; P<.001) and higher median hospital charges per patient (US $81,567 vs US $55,461; P<.001) compared to those without complications. CONCLUSION: Colectomy rates across the United States in children with ulcerative colitis have remained stable between 1997 and 2009; however, in-hospital postoperative complication rates have increased.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".