Prognostic impact of atherogenic index of plasma (AIP) in type 2 diabetes mellitus patients with acute coronary syndrome undergoing percutaneous coronary intervention

Abstract Background and purposesThe association of atherogenic index of plasma (AIP), an emerging lipid index which can predict risk for cardiovascular (CV) disease, with adverse outcomes in type 2 diabetes mellitus (T2DM) patients with acute coronary syndrome (ACS) undergoing percutaneous coronary intervention (PCI) has been undetermined. Therefore, the aim of this study was to investigate whether AIP could independently predict adverse CV events in T2DM patients with ACS undergoing PCI.MethodsThis study was a retrospective analysis of a single centre prospective registry involving 826 consecutive T2DM patients who underwent coronary angiography for ACS and were treated with primary or elective PCI at our CV center from June 2016 to November 2017. This study eventually included 798 patients (age, 61 ± 10 years, male, 72.7%). AIP was calculated as the base 10 logarithm of the ratio of plasma concentration of triglycerides to high density lipoprotein-cholesterol (HDL-C). All patients were divided into 4 groups based on the AIP quartiles. The primary endpoint was a composite of all-cause death, non-fatal ischemic stroke, non-fatal myocardial infarction (MI), or unplanned repeat revascularization. The key secondary endpoint was a composite of cardiovascular death, non-fatal ischemic stroke, or non-fatal MI.ResultsDuring a median follow-up period of 927 days, 198 patients developed at least one event. Unadjusted Kaplan–Meier analysis showed the incidence of the primary endpoint increased gradually with rising AIP quartiles (log-rank test, P = 0.001). Adjusted multivariate Cox proportional hazards analyses revealed that compared with the lowest AIP quartile, the top AIP quartile was associated with significantly increased risk for the primary and key secondary endpoints (hazard ratio HR: 2.153; 95% confidence interval CI: 1.355 to 3.421; P = 0.001, and HR: 2.613; 95% CI: 1.024 to 6.666; P = 0.044, respectively). Inclusion of AIP quartiles in a baseline prediction model for the primary endpoint increased the Harrell’s C statistic from 0.697 to 0.707. More importantly, addition of AIP quartiles to the above model significantly improved the continuous net reclassification improvement (continuous NRI = 19.1%, P < 0.001).ConclusionA higher AIP value on admission was independently and strongly associated with adverse CV events in T2DM patients with ACS undergoing PCI.