Association of sulfonylureas with the risk of dementia: A population‐based cohort study
Bibliographic record
Abstract
BACKGROUND: Sulfonylureas are oral glucose-lowering medications positioned as a second-line therapy for type 2 diabetes. Evidence relating them to cognitive decline has been mixed. The objective was to determine whether sulfonylurea use was associated with a differential risk of dementia compared with dipeptidyl peptidase-4 (DPP4) inhibitor use. METHODS: Using administrative data from residents in Ontario, Canada, adults aged ≥66 years who were new users of a sulfonylurea or a DPP4 inhibitor from June 14, 2011, to March 31, 2021 entered this population-based retrospective cohort study. Dementia was ascertained using a validated algorithm for Alzheimer's disease and related dementias. Propensity-score weighted Cox proportional hazards models were used to obtain adjusted hazard ratios (aHR) and confidence intervals (CI) for time to incident dementia. The observation window started at 1 year after cohort entry to mitigate protopathic bias due to delayed diagnosis. The primary analysis used an intention-to-treat exposure definition. A separate propensity-score weighted analysis was conducted to explore within-class differences in dementia risk among sulfonylurea new users selected from the primary cohort. RESULTS: Among 107,806 DPP4 inhibitor new users and 37,030 sulfonylurea new users, sulfonylureas compared with DPP4 inhibitors were associated with a higher risk of dementia (18.4/1000 person-years; aHR [95% CI] = 1.09 [1.04-1.15]) over a mean follow-up of 4.82 years from cohort entry. Glyburide compared to gliclazide exhibited a higher dementia risk (aHR [95% CI] = 1.17 [1.03-1.32]). CONCLUSION: New use of a sulfonylurea especially glyburide was associated with a higher dementia risk compared with new use of a DPP4 inhibitor in older adults with 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Research integrity | 0.001 | 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".