852-P: Factors Associated with the Use of Adjunct-to-Insulin Glucose-Lowering Agents in Patients with Type 1 Diabetes Mellitus
Bibliographic record
Abstract
Introduction and Objective: Adjunct-to-insulin metformin, Glucagon-Like Peptide-1 receptor agonists (GLP1-RA), and Sodium Glucose Co-transporter 2 inhibitors (SGLT2i), mostly off-label, are used by people with type 1 diabetes (PwT1D) to address the challenges of glucose control and other outcomes. We investigated the socio-demographic and disease-related characteristics associated with their use. Methods: Cross-sectional comparison of self-reported demographic and clinical variables between adjunct-to-insulin users vs. non-users in the Canadian BETTER registry were made (by Chi square for categorical and Mann-Whitney U test for non-normally distributed continuous variables). Results: Among 1463 participants (67.1% women, median [IQR] age 44.0 years [31.0, 56.0], BMI 25.6 kg/m2 [22.7, 29.1], 30.6% with HbA1c < 7.0%, 45.2% insulin pump users), 221 (15.1%) reported using adjunct-to-insulin medication (metformin 41.2%; GLP1-RA 25.8%; iSGLT2 18.1%; combination 14.9%). Users were older (47.0 [40.0, 56.0] vs. 43.0 [30.0, 56.0] years, p < 0.001), had higher BMI (29.1 [25.2, 33.3] vs. 25.1 [22.5, 28.3] kg/m2, p < 0.001), if multiple daily injection therapy had higher basal insulin dose (0.29 [0.19, 0.41] vs. 0.24 [0.17, 0.31] U/kg/day, p = 0.003) compared to non-users. Adjunct-to-insulin use was also associated with presence of cardiovascular disease (10.9% vs. 6.76%, p = 0.045), use of antihypertensive medication (41.6% vs. 29.1%, p < 0.001), and use of lipid-lowering drugs (65.6% vs. 41.4%, p < 0.001). HbA1c level, diabetes duration, and total daily insulin dosage did not differ between users and non-users. SGLT2i users reported similar diabetic ketoacidosis rates as non-users. Conclusion: The contemporary use of adjunct-to-insulin glucose-lowering drugs is common in adult PwT1D, and strongly associated with the presence of cardiometabolic risk factors. Disclosure J. Liu: None. M.K. Talbo: Other Relationship; Dexcom, Inc. M. Lebbar: None. V. Messier: None. C. Leroux: None. A. Bonhoure: None. N. Taleb: Speaker's Bureau; Novo Nordisk. B.A. Perkins: Other Relationship; Abbott, Novo Nordisk, Sanofi. Advisory Panel; Abbott, Insulet Corporation, Sanofi, Novo Nordisk, Nephris, Vertex Pharmaceuticals Incorporated. Research Support; Novo Nordisk. A. Brazeau: Speaker's Bureau; Dexcom, Inc. Research Support; Canadian Institutes of Health Research. Speaker's Bureau; Juvenile Diabetes Research Foundation (JDRF). Research Support; Juvenile Diabetes Research Foundation (JDRF), Diabète Québec, Fonds de recherches du Québec-Santé, Mitacs. R.P.R. Rabasa-Lhoret: Advisory Panel; Abbott, Eli Lilly and Company, Novo Nordisk, Sanofi, Insulet Corporation. Other Relationship; Medtronic. Advisory Panel; Bayer Pharmaceuticals, Inc.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".