Ethnic Variations of Pediatric Inflammatory Bowel Disease Within Canada
Bibliographic record
Abstract
Inflammatory bowel disease (IBD) is a chronic inflammatory condition of the gastrointestinal tract with highest prevalence in the Western world. Up to twenty-five percent of those who develop IBD are diagnosed in their childhood or adolescent years. Recent temporal trends in adult and pediatric populations demonstrate increasing incidence in both developed and developing countries. IBD phenotypes may differ between countries and ethnic/racial groups. Therefore, the aim of this thesis is to examine ethnic and phenotypic variation of children newly diagnosed with IBD in Canada. An analysis of all newly diagnosed pediatric IBD patients enrolled in the multicenter national prospective Canadian Children IBD Network (CIDsCaNN) inception cohort was conducted. Children were categorized into eight different ethnic groups using a modified Statistics Canada classification method. Baseline data such as demographic characteristics, disease phenotype and activity, family history of IBD, surgeries, and hospitalizations were compared between Caucasians and different ethnic groups. Our study demonstrated important differences between Caucasian and non-Caucasian children with IBD in Canada in specific phenotypes of IBD, time to diagnosis, disease location and behavior, family history of IBD, and immigrant status. South Asians had higher odds of ulcerative colitis (UC) compared to Caucasians. Caucasians with UC had a significantly longer time to diagnosis compared to non-Caucasians. Non-Caucasians with UC had a significant inverse correlation with shorter time to diagnosis in higher pediatric ulcerative colitis activity index (PUCAI) scores, whereas there was no significant correlation found for Caucasians. Caucasians had higher odds of having a first-degree family member with IBD compared to non-Caucasians. Caucasians had lower odds of being a First- or Second-Generation Immigrant compared to Non-Caucasians. This thesis aims to explore the ethnic and phenotypic variation of children newly diagnosed with IBD in Canada. Some of the findings in this thesis are supported by the existing literature and some differ; differences may be due to the small sample size of specific ethnic groups in this study. Further studies are required to explore the differences in phenotypes between different ethnic groups as well as to understand differences in treatment responses with a goal of moving towards personalized medicine in IBD.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| 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".