Exploring Anthropometric and Laboratory Differences in Children of Varying Ethnicities with Celiac Disease
Bibliographic record
Abstract
BACKGROUND: Celiac disease (CD) is a common autoimmune disorder with an increasing prevalence, including in ethnic minorities. OBJECTIVE: To report the frequency of CD diagnosis in ethnic minorities presenting to a Canadian pediatric celiac clinic and to determine whether ethnic differences exist at diagnosis or follow-up. METHODS: Patients with biopsy-proven CD diagnosed at a multidisciplinary celiac clinic between 2008 and 2011 were identified through the clinic database. Data at referral, and six-month and 12-month follow-ups were collected. These included demographics, self-reported ethnicity, symptoms, anthropometrics and laboratory investigations, including serum immunoglobulin antitissue transglutaminase (aTTG). RESULTS: A total of 272 patients were identified; 80% (n = 218) were Caucasian (group 1) and 20% (n = 54) were other ethnicities. South Asians (group 2) comprised 81% (n = 44) of the minority population. No differences in age or sex were found between the two groups. Group 1 patients presented more often with gastrointestinal symptoms (71% versus 43%; P < 0.001), while patients in group 2 presented more often with growth concerns (21% versus 68%; P < 0.001). At diagnosis, serum aTTG level was consistently lower in group 1 compared with group 2 (367 IU⁄mL versus 834 IU⁄mL; P = 0.030). Both groups reported symptom improvement at six months and one year. At the end of one year, aTTG level was more likely to be normal in group 1 compared with group 2 (64% versus 29%; P < 0.001). CONCLUSION: Although they represent a minority group, South Asian children comprised a significant proportion of CD patients presenting to a Canadian celiac clinic. South Asian children were more likely to present with growth concerns, which has important implications for timely diagnosis in this population. In addition, the apparent delay in normalization of aTTG levels suggests that careful follow-up and culturally focused education supports should be developed for South Asian children with CD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".