Glucagon-Like Peptide 1 Receptor Agonists and Cardiovascular Disease Risk: Findings from Real-World Data using AI-Powered Outcomes

BackgroundThe SELECT trial showed cardiovascular benefits of glucagon-like peptide-1 receptor agonists (GLP-1 RAs) in obese patients with cardiovascular disease; however, real-world data (RWD) on this benefit remain limited. This study used an artificial intelligence (AI)-generated algorithm and multimodal RWD to evaluate the impact of GLP-1 RAs on cardiovascular disease risk in a population of obese patients with and without preexisting cardiovascular disease. MethodsUsing data from the Dandelion Health RWD library, an Emulated SELECT Cohort was created to include obese patients similar to those in the SELECT trial, but with and without preexisting cardiovascular disease. An AI algorithm developed by Pheiron that used 12-lead electrocardiograms (ECGs) as a predictive biomarker for the risk of major adverse cardiovascular events (MACE) was validated and used to derive MACE risk scores for the Emulated SELECT Cohort. These outcomes were compared over time between patients who used GLP-1 RAs and non-users using inverse-probability weighted linear regression models, adjusting for key covariates. ResultsOut-of-sample validation showed high predictive accuracy of the AI algorithm, with ROC AUCs of 0.81 for myocardial infarction (MI) and 0.75 for stroke. Increased risk scores from the algorithm were correlated with higher MACE incidence in RWD. In the Emulated SELECT Cohort of 20,795 patients, GLP-1 RA use was associated with significant attenuation of MACE risk, with reductions observed in percentile risk score for MI (4%; p<0.001) and stroke (3.6%; p<0.001) per year of use. Differences in GLP-1 RA and non-GLP-1 users were evident as early as 1.7 years, with a 15-20% difference in absolute MACE risk scores between GLP-1 RA users and non-users observed by the end of the study. ConclusionAn AI algorithm using 12-lead ECGs accurately predicted MACE risk and could be used to model risk attenuation associated with GLP-1 RA use. Using this outcome, we find that GLP-1 RA use was associated with significant reductions in MI and stroke risk, in a broader population and within a shorter timeframe than the SELECT trial. These findings suggest potentially significant cardioprotective benefits of GLP-1 RAs in real-world settings and demonstrate a proof-of-concept for utilizing clinical AI to understand these benefits.