F-13 | Lipoprotein(a) Levels and Their Underutilization in Peripheral Artery Disease Diagnosis and Management

This study investigates the levels of Lipoprotein(a) Lp(a) in patients with peripheral artery disease (PAD) and examines the usage of Lp(a) measurements in conjunction with various treatment strategies, utilizing a comprehensive multinational database. Data were sourced from the TriNetX research network, encompassing 76 healthcare organizations, from January 1, 2015, to October 1, 2023. Among the 1,288,003 patients diagnosed with PAD, only 1,788 had documented Lp(a) tests, while 1,286,215 had no record of such tests. To assess the predictive value of Lp(a) for clinical outcomes, researchers implemented a 1:1 propensity score matching, accounting for common cardiology and vascular indicators, medications, and lab results. Patients aged 18 to 90 were stratified into two groups to evaluate disparities. Notable differences were observed in the prevalence of hypertension (77.4% in the Lp(a) group vs. 52.5%), diabetes (42.2% vs. 29.1%), coronary artery disease (CAD) (37.6% vs. 22.2%), and heart failure (28.7% vs. 15.6%), all with P<0.01. After propensity score matching, creating two cohorts of 1,788 patients each, a higher incidence of CAD at 5 years was noted in the Lp(a) group (51% vs. 40.1%, P<0.01). The findings underscore the imperative for further investigation to define the risk thresholds for Lp(a) levels and their impact on PAD. Despite Lp(a) being a recognized independent risk factor for atherosclerotic conditions, its testing is not routinely incorporated into standard PAD diagnostic protocols. The absence of standardized laboratory measures and clear societal guidelines for Lp(a) target levels further complicates this issue. With Lp(a)-lowering medications currently undergoing Phase 3 trials, establishing standardized risk thresholds becomes increasingly important. Educating physicians about the importance of Lp(a) in the context of other lipid profiles, such as ApoB and non-HDL, is critical for PAD management. Validation of this data could significantly enhance PAD surveillance, providing an additional diagnostic and treatment tool.