Back

Pre-stroke glucagon-like peptide-1 receptor agonist use and outcomes after acute ischemic stroke: a propensity score-matched retrospective cohort study

Negida, Y.; Khand, Y.; Hawas, Y.; Yadav, V.; Mohamed, K. M. H.; Saha, R.

2026-05-01 neurology
10.64898/2026.04.29.26352109 medRxiv
Show abstract

BackgroundGlucagon-like peptide-1 receptor agonists (GLP-1 RAs) have demonstrated cardiovascular benefits in type 2 diabetes mellitus (T2DM); however, their association with post-stroke outcomes following acute ischemic stroke (AIS) remains uncertain. MethodsWe conducted a retrospective propensity score-matched (PSM) cohort study using the TriNetX Global Collaborative Network. Adults with T2DM and AIS between January 2020 and January 2025 were included. Pre-stroke GLP-1 RA users were compared with non-users. Primary outcomes were all-cause mortality, intracerebral hemorrhage (ICH), ICD-10-coded stroke severity (NIHSS categories), and transient ischemic attack (TIA). ResultsAfter PSM, GLP-1 RA use was associated with significantly lower all-cause mortality at all time points (RR 0.44-0.52; HR 0.43-0.45; all p<0.001). ICH risk was reduced within 1-3 days (RR 0.683; 95% CI 0.496-0.940; p=0.019) and within 7 days (RR 0.575; 95% CI 0.516-0.641; p<0.001). A severity-dependent gradient was observed across NIHSS categories, with risk reductions ranging from 37% for minor strokes (NIHSS 0-5; RR 0.626) to 67% for very severe strokes (NIHSS >20; RR 0.327; all p<0.001). TIA risk was 29% lower (RR 0.712; 95% CI 0.668-0.759; p<0.001). E-value analysis demonstrated that an unmeasured confounder would need to be associated with both GLP-1 RA use and 30-day mortality by a risk ratio of at least 3.95 to fully explain the observed association, and by a risk ratio of at least 3.53 to shift the confidence interval to include the null. ConclusionsIn this large real-world cohort, pre-stroke GLP-1 RA use was associated with lower post-stroke mortality, reduced ICH, and a severity-dependent reduction in ICD-10-coded stroke severity among patients with T2DM. Residual confounding cannot be excluded, and these findings warrant confirmation in prospective randomized trials.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.