Abstract 16545: Effect of Residual Risk of Inflammation and Lipoprotein(a) on Adverse Cardiovascular Outcomes in Optimally Treated Patients According to Glucose Tolerance Status

Abstract

Introduction: Currently, risks of residual inflammation and residual lipoprotein(a) [Lp(a)] remains in patients with coronary artery disease (CAD) even after lipid-lowering therapy. Hypothesis: This study aims to investigate the association between dual residual risk of inflammation and Lp(a) and adverse cardiovascular events in a large, multicenter cohort with CAD, which has not been investigated. Methods: A total of 3,546 patients with CAD were consecutively enrolled. Based on the Lp(a) and hypersensitive C-reactive protein levels, patients were divided into those with no residual risk, residual Lp(a) risk (RLR), residual inflammatory risk (RIR), and residual cholesterol and inflammatory risk (RLIR). All patients were followed for the major adverse cardiovascular events (MACEs), including all cause mortality, non-fatal myocardial infarction, and non-fatal stroke. Multivariable Cox proportional hazard model was conducted to determine hazard ratio (HR) of MACEs for RIR, RCR, and RCIR with different glucose tolerance status. Results: Over an average of 2.01 years follow-up, 326 MACEs were recorded. Multivariate Cox analysis showed that higher RIR were significantly related to an increased risk of MACEs, while elevated RLR were associated with a slightly but non-significantly increased MACEs risk. Moreover, when participants were subgrouped according to RLR, RIR and glucose tolerance status together, High RLR+High RIR+Diabetes group had significantly higher risk of MACEs [hazard ratio (HR) 2.93, 95% confidence interval (CI) 1.71-5.02] compared with the reference group (Low RLR+Low RIR+Non-diabetes). Conclusions: The combination of RLR, RIR and glucose tolerance status potentiated the adverse effect on MACEs among statin-treated patients with CAD, suggesting that multiple residual risk factors assessment may be a better strategy to improve stratification in very-high risk population.