Inflammatory Bowel Disease Among Canadian Children: Comparison Between Children of Non-European Descent and Children of European Descent
Bibliographic record
Abstract
BACKGROUND: Inflammatory bowel disease (IBD) phenotypes may differ between countries and ancestral groups. The study aim was to examine ancestry and subtype variations of children newly diagnosed with IBD. METHODS: Children newly diagnosed with IBD enrolled into the Canadian Children Inflammatory Bowel Disease Network inception cohort study were categorized into 8 ancestral groups. Prospectively collected data at diagnosis and follow-up were compared between ancestral groups. RESULTS: Among 1447 children (63.2% Crohn's disease, 30.7% ulcerative colitis), 67.8% were European, 9.4% were South Asian, 3.8% were West Central Asian and Middle Eastern, 2.3% were African, 2.2% were East/South East Asian, 2.0% were Caribbean/Latin/Central/South American, 9.9% were mixed, and 2.6% were other. Children of African descent with ulcerative colitis had an older age of diagnosis compared with children of European descent (median 15.6 years vs 13.3 years; P = .02). Children of European descent had a higher proportion of positive family history with IBD (19.3% vs 12.1%; P = .001) compared with children of non-European descent. Children of European descent also had a lower proportion of immigrants and children of immigrants compared with children of non-European descent (9.8% vs 35.9%; P < .0001; and 3.6% vs 27.2%; P < .0001, respectively) . CONCLUSIONS: Important differences exist between different ancestral groups in pediatric patients with IBD with regard to age of diagnosis, family history, and immigrant status. Our study adds to the knowledge of the impact of ancestry on IBD pathogenesis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".