Disease Behavior in Children with Crohn's Disease: The Effect of Disease Duration, Ethnicity, Genotype and Phenotype
Bibliographic record
Abstract
Objectives: The Vienna classification divides Crohn's disease (CD) into 3 behavior groups, inflammatory, stricturing, and penetrating types. The aim of our study was to evaluate the effect of genotype and phenotype on disease behavior in pediatric CD. Study design: Evaluation of 128 pediatric onset CD was followed by analysis of 235 pediatric and adult onset CD patients, all with at least two years of follow-up (mean 4.9 and 6.4 years respectively). Phenotype, ethnicity, and disease duration were recorded. Patients were genotyped for polymorphisms in the NOD2/CARD15 gene. Results: Patients under the age of 9 had more colonic involvement. Pediatric disease at end of follow-up was classified as inflammatory (78%), penetrating (6%) and stricturing (17%), while 31% had perianal disease. Duration of follow-up was associated with more stricturing and penetrating disease. NOD2 was associated with ileal disease. There was no association between mean age of onset and NOD2/CARD15, or one of these with disease behavior. These observations were identical in the final mixed adult pediatric cohort. Sephardic Jewish origin was inversely correlated with inflammatory behaviour (p=0.006), independent of NOD2 genotype. Conclusions: Duration of disease and ethnicity, irrespective of NOD2/CARD15 genotype, were the only predictors for penetrating or stricturing disease.
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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".