The Temporal Relationship Between the Onset of Type 1 Diabetes and Celiac Disease: A Study Based on Immunoglobulin A Antitransglutaminase Screening
Bibliographic record
Abstract
OBJECTIVE: The association of celiac disease (CD) and type 1 diabetes is now clearly documented. Immunoglobulin A (IgA) antitransglutaminase antibodies were measured to determine the prevalence of celiac disease in a diabetic population of children and to determine the temporal relationship between type 1 diabetes onset and CD. METHODS: We measured IgA antitransglutaminase antibodies using human recombinant antigen in parallel with classical markers (IgA and IgG antigliadin, IgA antiendomysium) in 284 children with diabetes. RESULTS: In the population studied, the prevalence of CD was 3.9% (11 of 284). Two cases of CD were diagnosed before the onset of diabetes, and in 8 patients, the diagnoses of CD and diabetes were concomitant, suggesting that CD was present before the onset of diabetes. In 1 case, a girl who presented with thyroiditis, serology for CD became positive after diabetes had been diagnosed. CONCLUSION: An excellent correlation was observed between IgA antiendomysium and IgA antitransglutaminase antibodies. We therefore propose using IgA antitransglutaminase as a screening test for practical reasons. Furthermore, IgA antitransglutaminase levels and mucosa abnormalities were closely correlated. The presence of antitransglutaminase antibodies should alert pediatricians to the atypical forms of CD. This study indicates that CD is most often present before the onset of diabetes.
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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 | 0.003 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".