1348-P: Celiac Disease in Children with T1D Varies among the World: An International, Cross-Sectional Study of 39,425 Patients from the SWEET Registry
Bibliographic record
Abstract
Comorbid celiac disease (CD) may affect the course of type 1 diabetes (T1D). We aimed to compare T1D children with and without CD. This study is based on the SWEET (Better control in Pediatric and Adolescent diabeteS:Working to crEate cEnTers of Reference) database. We included 39 425 patients aged ≤18 y. Regression models adjusted for demographics were applied to compare outcomes. CD was present in 1 804 subjects (4.6%). Prevalence of CD differed among regions: 1.9% Asia/Middle East, 4.3% Northern Europe, 5.1% Southern Europe, 5.3% North America/Canada and 6.1% Australia/New Zealand. Girls were diagnosed with CD significantly more often than boys (p< 0.01). Children with CD were younger at diabetes onset (p< 0.001), also when boys and girls were separately analyzed. CD subjects were significantly shorter (p= 0.002) and had lower BMI-SDS (p< 0.001) (Fig). HbA1c was lower in patients with CD (p< 0.001), even after adjustment for pump use (Fig). Across regions, gender differences in CD prevalence were not shown in Northern Europe and Asia/Middle East. HbA1c was lower in CD patients in Southern Europe and North America/Canada. In contrast, in Asia/Middle East, HbA1c was significantly higher among CD patients (p<0.001). No difference was found in Northern Europe. The frequency, anthropometric as well as metabolic consequences of CD in T1D children differs around the world. Disclosure A. Taczanowska: None. A. Schwandt: None. S. Amed: None. J. Svensson: Advisory Panel; Self; Janssen Pharmaceuticals, Inc., Medtronic. Speaker's Bureau; Self; Novo Nordisk A/S, Sanofi-Aventis. Stock/Shareholder; Self; Novo Nordisk A/S. A. Szypowska: None. C. Kanaka-Gantenbein: None. P. Toth-Heyn: None. S. Krepel Volsky: None.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".