Celiac Disease in Patients With Type 1 Diabetes
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to investigate screening practices for celiac disease in patients with type 1 diabetes across North America. The research question investigated was whether diabetes centers screen for celiac disease in type 1 diabetes more frequently than other facilities. RESEARCH DESIGN AND METHODS: A survey with 27 questions on screening practices for celiac disease in patients with type 1 diabetes was designed by experts in celiac disease and diabetes. Surveys were sent by email to diabetes educators and dietitians throughout the United States and Canada between December 2010 and May 2011. RESULTS: There were 514 respondents from 484 endocrine clinics, diabetes clinics, private practices, community nutrition centers, and inpatient centers. Thirty-five percent of work locations screened for celiac disease, with endocrine clinics reporting screening at the highest frequency (80%). Tissue transglutaminase was the most common screening test used. The most frequently recommended treatment of confirmed celiac disease was a gluten-free diet. However, only 71% of respondents recommended biopsy in patients with positive serologies. Most respondents (55.3%) reported that the gluten-free diet resulted in symptom improvement in the majority of patients. CONCLUSIONS: Staff at endocrine clinics were more likely to suggest screening for celiac disease in patients with type 1 diabetes. Both low screening frequency as well as inconsistency in management of positive celiac disease serological tests indicated an increase in education regarding celiac disease in patients with type 1 diabetes is required. In addition uniform guidelines should be developed.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".