Risk of stroke in patients with type 2 diabetes receiving semaglutide or a dipeptidyl peptidase-4 inhibitor: a real-world US claims database analysis
Bibliographic record
Abstract
Abstract Introduction People with type 2 diabetes (T2D) have a higher risk of stroke than those without, are likely to experience stroke at a younger age, and have worse outcomes. The cardiovascular benefits of glucagon-like peptide-1 receptor agonists (GLP-1 RAs) in T2D have been demonstrated in randomized controlled trials. A meta-analysis of these data has shown that GLP-1 RAs are associated with a significant reduction in the risk of stroke; however, there remains an evidence gap for the real-world effect of semaglutide specifically on stroke risk. Purpose To compare real-world risk of stroke in patients with T2D or T2D + atherosclerotic cardiovascular disease (ASCVD) initiating either semaglutide or a dipeptidyl peptidase-4 inhibitor (DPP-4i). Methods For inclusion, adults (≥18 years) in a US claims database required a claim indicating initiation of either semaglutide or a DPP-4i (index date) during the index period (1/1/18–30/9/20), a diagnosis code for T2D on or before the index date, and 12 months' continuous enrolment pre-index. Exclusion criteria were a claim for semaglutide, DPP-4i or injectable glucose-lowering medication, or diagnosis code for type 1 or secondary diabetes in the 12 months pre-index; or a claim associated with pregnancy or gestational diabetes any time during the study period. Patients were propensity score matched 1:1 on 27 baseline demographic and clinical characteristics. Patients who also had a diagnosis code for ASCVD pre-index were matched separately on 26 variables. Primary outcome was time to first stroke event during follow-up, defined as a medical claim with stroke as primary diagnosis during inpatient or emergency room visit. Patients with no event were censored at end of enrolment or end of study period (30/9/20), whichever was earliest. Results Post-matching, there were 17,920 pairs with T2D and 4234 pairs with T2D+ASCVD. The groups were well matched on baseline characteristics (Table). For T2D, patients initiating semaglutide had a lower risk of stroke than those initiating a DPP-4i (hazard ratio [HR], 0.63; 95% confidence interval [CI]: 0.41–0.95; p=0.029). This trend was more pronounced for T2D+ASCVD (HR, 0.45 [0.24–0.86]; p=0.015). Overall, 34 patients with T2D receiving semaglutide (0.2%) experienced a stroke event (incidence rate [IR] per 100 person-years, 0.25), compared with 60 patients receiving a DPP-4i (0.3%; IR, 0.40; IR ratio [IRR], 0.62; 95% CI: 0.40–0.95). For the groups with T2D+ASCVD, 13 patients receiving semaglutide (0.3%; IR, 0.40) and 32 receiving a DPP-4i (0.8%; IR, 0.90) experienced a stroke event (IRR, 0.44 [0.23–0.85]). The Figure shows cumulative incidence of stroke over follow-up (median 237–258 days). Conclusion This analysis provides initial insights into the potential of semaglutide to reduce real-world stroke risk in patients with T2D. Analyses with additional comparison groups and longer follow-up are needed to determine the broader clinical and economic implications. Funding Acknowledgement Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): This study was funded by Novo Nordisk A/S. Medical writing support was provided by Oxford PharmaGenesis, Oxford, UK with funding from Novo Nordisk A/S.
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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".