1737-P: Prevalence of Autoimmune Diseases in Longstanding Diabetes: Results from the Canadian Study of Longevity in Type 1 Diabetes
Bibliographic record
Abstract
Objective: Type 1 diabetes (T1D) predisposes to higher lifetime autoimmune (AI) disease risk; the magnitude of this risk is not known with certainty. To approximate lifetime risk, we aimed to determine the prevalence of AI diseases in those exceeding 50 years T1D duration, as well as to explore sex-specific differences and associations with complications. Methods: Descriptive analysis of the Canadian Study of Longevity in T1D, a nationwide questionnaire study initiated in 2013 that recruited 374 T1D participants with duration >50 years. The questionnaire collected diabetes management variables, general medical history with a focus on AI disease, and diabetes-related complications. Clinical and laboratory data were obtained from primary care providers. The χ2-test and Student’s t-test were used for simple comparisons. Results: The 374 participants with longstanding T1D had median age of 66 [59, 71] years, T1D duration 53 [51, 58] years and HbA1c 7.5±1.0%. AI diseases were reported in 184/374 (49.3%). Thyroid disease was most prevalent, 154/374 (41.2%) reported thyroid disease or was prescribed thyroid hormone replacement therapy. Addison’s disease or prescribed glucocorticoid and mineralocorticoid therapy was reported in 5/374 (1.3%). Autoimmune polyendocrine syndrome type 2 (APS-2), defined by the presence of thyroid disease, Addison’s disease and T1D, was present in 3/374 (0.8%). We observed a sex-specific difference in AI disease prevalence (34.6 females vs. 14.8% in males; p<0.0001), driven by the difference in thyroid disease (29.5 females vs. 11.5% males, p<0.0001). No difference in HbA1c was observed (7.5±1.1 vs. 7.6±1.0%, p=0.62). There was a trend toward lower CAD prevalence among those with AI disease (12.1 vs. 16.9%, p=0.05). Conclusions: We estimate that in a population with longstanding T1D, the lifetime risk of AI disease approaches half, driven primarily by the presence of autoimmune thyroid disease, and with greater risk in females. Disclosure N. Cardinez: None. L. Lovblom: None. A. Orszag: None. D. Cherney: Other Relationship; Self; AbbVie Inc., AstraZeneca, Bayer AG, Boehringer Ingelheim International GmbH, Janssen Pharmaceuticals, Inc., Merck & Co., Inc., Mitsubishi Tanabe Pharma Corporation, Prometic Life Sciences Inc., Sanofi. B.A. Perkins: Advisory Panel; Self; Abbott, Boehringer Ingelheim International GmbH, Boehringer Ingelheim International GmbH, Insulet Corporation. Research Support; Self; Boehringer Ingelheim International GmbH. Other Relationship; Self; Abbott, Boehringer Ingelheim International GmbH, Lilly Diabetes, Medtronic, Novo Nordisk Inc., Sanofi. Funding JDRF (17-2013-312)
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".