Abstract

Semaglutide is often optimized for weight loss, but whether longer-term cardiovascular benefit tracks achieved weight loss or therapeutic exposure levels remains unclear. Using a federated deidentified U.S. electronic health record network of 29 million patients, including 505,874 semaglutide-treated individuals, we leveraged multimodal AI technologies to analyze 47,199 patients with baseline cardiovascular disease. We quantified dose escalation and weight change during the 0-2-year period after semaglutide initiation (landmark period) and assessed cardiovascular outcomes during the 2-4-year period (post-landmark). In propensity-matched comparisons during the landmark period, semaglutide was associated with lower cardiovascular events than metformin, DPP-4 and SGLT2 inhibitors. Higher maximum semaglutide dose was associated with greater weight loss during the landmark period (3.15% additional weight loss per 1 mg increase; r=0.97, P<0.001), and lower post-landmark risk of all-cause mortality (RR 0.42, p<0.001), composite cardiovascular events (death, myocardial infarction, or stroke; RR 0.51, p<0.001), cerebrovascular disease (RR 0.50, p<0.001), heart failure (RR 0.55, p<0.001), and valvular/rheumatic heart disease (RR 0.71, p=0.025). In contrast, greater achieved weight loss during the landmark period did not show a consistent monotonic association with lower post-landmark cardiovascular risk (All-cause mortality p-value=0.14, composite cardiovascular endpoint p-value=0.55). Integrating insights from a single cell GLP1R expression atlas was used to infer how semaglutide pharmacology may tie into heart-specific signaling, beyond what is reflected by body-weight reduction alone. The strongest prevalence-weighted GLP1R signal was observed in the pancreas, followed by the heart, where GLP1R engagement potential (GEP) was considerable across cardiomyocyte, cardiac endothelial, and rarer immune cell populations. Together, semaglutide cardiovascular benefit appears organized more by maximum dose attained than by achieved weight-loss magnitude, setting the stage for beyond-obesity trial designs that integrate whole-body spatial intelligence.