Perianal Disease Predicts Changes in Crohn's Disease Phenotype-Results of a Population-Based Study of Inflammatory Bowel Disease Phenotype
Bibliographic record
Abstract
BACKGROUND: The Montreal classification system of inflammatory bowel disease (IBD) provides a framework for describing disease phenotype. OBJECTIVE: We aimed to describe changes in IBD phenotype using the Montreal system and determine predictors of phenotype change in a Caucasian population-based cohort. METHODS: Ninety-two percent of people with IBD in Canterbury, New Zealand were recruited. Clinical notes were reviewed to confirm diagnosis and phenotype. Determinants of phenotype change were analyzed using multivariate analysis. RESULTS: A total of 1,420 (715 Crohn's disease [CD], 668 ulcerative colitis [UC]) patients with IBD were included. Median follow-up was 6.5 and 10.9 yr for CD and UC, respectively. Disease location remained stable in 91% of those with CD. Seventy-three percent of CD patients had inflammatory disease at diagnosis with the proportion of patients with complicated disease increasing over time. Progression to complicated disease was more rapid in those with small bowel than colonic disease location, (P < 0.001). Perianal disease was a significant predictor of change in CD behavior (HR 1.62, P < 0.001). Younger UC patients were more likely to have extensive disease at diagnosis than older patients (P < 0.001). CONCLUSIONS: Although CD location remains relatively stable, behavior changes over time. Perianal disease is a strong predictor of developing more complicated CD. Proctitis is most common in UC patients at diagnosis although younger patients are more likely than older patients to have extensive disease. The Montreal classification provides a clinically useful framework for both researchers and clinicians.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".