Histopathological changes in anatomical distribution of inflammatory bowel disease in children: a retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: Anatomical progression of pediatric inflammatory bowel disease is under-reported. The aim of this work was to examine possible changes in the anatomical distribution of IBD in pediatric patients at diagnosis and at follow up. METHODS: In a retrospective cohort study, the medical records of children with inflammatory bowel disease were examined. Patients who had at least 2 endoscopic/colonoscopic examinations were included. Primary outcome was histopathological progression based on histopathological examination of biopsies taken during endoscopic and colonoscopic bowel examination. Factors predictive of disease progression were also examined. RESULTS: A total of 98 patients fulfilled inclusion criteria (49 female, 54 with ulcerative colitis, range 2 - 17 years, mean age at diagnosis was 10.6 years, SD ± 3.67), the mean duration of follow up was 32.9 months (range 0.1 - 60 months, SD ± 8.54). In the ulcerative colitis group, 41% had disease progression and none of the examined variables (age, gender, laboratory markers, growth and disease activity at diagnosis) appeared to effect disease progression. In the Crohn's disease group, 75% had disease progression. Girls (OR = 0.13, 95% CI 0.02 - 0.79) and patients with high erythrocytic sedimentation rate (OR=0.942, 95% CI 0.894 - 0.99) were predictive for disease progression. CONCLUSIONS: Despite maximum therapy, the majority of children with Crohn's disease appeared to have histopathological disease progression. Female sex and high erythrocytic sedimentation rate seemed to be predictive for disease progression. None of the factors analyzed seemed predictive of disease progression in ulcerative colitis.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".