The Experience of a Gluten-free Diet in Children with Type 1 Diabetes and Celiac Disease
Bibliographic record
Abstract
Abstract Objective This study examined overall self-reported adherence to gluten-free diet (GFD) in children with type 1 diabetes and celiac disease (T1DCD) compared to children with celiac disease (CD). Secondary objectives included gaining insight into self-reported symptoms, barriers to adherence, and experience of a GFD between groups. Methods Children <18 years old who had been seen at BC Children’s Hospital for T1DCD or CD were invited to participate in a web-based questionnaire and medical record review. Results A total of 26 children with T1DCD and 46 children with CD participated in the study. The groups’ demographics and symptoms of CD were similar; however, a greater proportion of those with T1DCD were asymptomatic at diagnosis (T1DCD 27%; CD 7%; P = 0.016). Overall adherence to a GFD was high in both groups (T1DCD 92%; CD 100%; P = 0.38) but those with T1DCD reported a significantly less positive effect on their health (P = 0.006) and a significantly greater negative effect on activities from a GFD (P = 0.03). Children with T1DCD reported more significant barriers to eating gluten-free at home and at restaurants, specifically with social pressure, cost and taste compared to those with CD only. Conclusion Children with T1DCD face specific barriers in adherence that are more impactful compared with children living with CD. These children are more often asymptomatic at diagnosis, and they go on to experience different impacts of a GFD spanning across home and social settings. Given the complexity of having a dual diagnosis, CD care should be tailored specifically to children living with T1DCD.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".