Intestinal histopathology in pediatric PSC‐IBD: Characterization of phenotype and assessment of the Nancy Index
Bibliographic record
Abstract
OBJECTIVES: We aimed to characterize the histologic gut phenotype of pediatric primary sclerosing cholangitis (PSC)-associated inflammatory bowel disease (IBD) against non-PSC colitis, and to assess Nancy Index (NI) performance in pediatric PSC-IBD. METHODS: Single-center retrospective cohort study including children diagnosed with PSC-IBD or non-PSC colitis (ulcerative colitis [UC] or IBD-unclassified) from 2000 to 2018, with diagnostic intestinal biopsies. Biopsies were re-reviewed by two independent pathologists who assessed microscopic disease distribution, NI scores, and specific histological features in the right and left colons, overall and stratified by endoscopic severity (moderate-severe vs. no more than mild). We examined NI inter-rater reliability with Fleiss' weighted (quadratic) kappa and NI construct validity against global endoscopic severity (Spearman correlation) and clinical outcomes (logistic regression). RESULTS: Fifty children with PSC-IBD and 81 colitis controls were included. Histologically, pancolitis (84% vs. 55%), right colon-predominant colitis (48% vs. 3%), and backwash ileitis (53% vs. 12%) (all p < 0.01) were significantly more common in PSC-IBD; histologic rectal sparing occurred at similar rates (6% vs. 10%, p = 0.54). Lamina propria-predominant neutrophils, prominent eosinophilic infiltration (left colon), and surface villiform change (right colon) were more common in PSC-IBD than colitis controls (p < 0.01). NI showed excellent inter-rater reliability (kappa > 0.9) and correlated moderately with global endoscopic severity but poorly with clinical activity in PSC-IBD. CONCLUSIONS: Pediatric PSC-IBD has a distinct histologic phenotype that largely mirrors the endoscopic phenotype in distribution and includes a greater frequency of features not included in conventional UC histologic activity indices. Future work should investigate whether a PSC-IBD-specific index incorporating these features is warranted.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".