Treatment with glucagon‐like peptide‐1 receptor agonists and incidence of dementia: Data from pooled double‐blind randomized controlled trials and nationwide disease and prescription registers
Bibliographic record
Abstract
INTRODUCTION: People with type 2 diabetes have increased risk of dementia. Glucagon-like peptide-1 (GLP-1) receptor agonists (RAs) are among the promising therapies for repurposing as a treatment for Alzheimer's disease; a key unanswered question is whether they reduce dementia incidence in people with type 2 diabetes. METHODS: We assessed exposure to GLP-1 RAs in patients with type 2 diabetes and subsequent diagnosis of dementia in two large data sources with long-term follow-up: pooled data from three randomized double-blind placebo-controlled cardiovascular outcome trials (15,820 patients) and a nationwide Danish registry-based cohort (120,054 patients). RESULTS: Dementia rate was lower both in patients randomized to GLP-1 RAs versus placebo (hazard ratio [HR]: 0.47 (95% confidence interval [CI]: 0.25-0.86) and in the nationwide cohort (HR: 0.89; 95% CI: 0.86-0.93 with yearly increased exposure to GLP-1 RAs). DISCUSSION: Treatment with GLP-1 RAs may provide a new opportunity to reduce the incidence of dementia in patients with type 2 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 | 0.032 | 0.064 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.016 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".