Association between the atherogenic index of plasma and long-term prognosis in acute ST-elevation myocardial infarction patients undergoing percutaneous coronary intervention: a retrospective cohort study.

Abstract

This study was aimed to evaluate the association between the atherogenic index of plasma (AIP) and long-term major adverse cardiovascular events (MACEs) in ST-segment elevation myocardial infarction (STEMI) patients undergoing percutaneous coronary intervention (PCI). A retrospective cohort study. The study utilised data from two tertiary care centres in China, which were retrospectively analysed. This retrospective cohort study initially enrolled 953 adult (≥18 years) patients with acute STEMI undergoing PCI. After applying exclusion criteria (including prior myocardial infarction, severe hepatic/renal dysfunction, lost follow-up and so on), 784 participants with complete clinical data comprised the final cohort and were divided into three AIP groups based on tertiles of AIP levels: low AIP group (n=260), medium AIP group (n=261) and high AIP group (n=263). High AIP patients exhibited significantly higher 2-year MACEs rates versus lower tertiles (p<0.05). After adjusting for age, sex, smoking and other factors, high AIP remained an independent MACEs predictor (OR:2.44; 95% CI 1.55 to 3.84; p<0.001). After adjustment, each one-unit increment in the AIP was associated with an adjusted OR of 3.295 (95% CI 1.683 to 6.449; p=0.001) for MACEs. In subgroup analyses, the high AIP level was a risk factor for the development of MACEs in patients of all ages, males, smokers, non-diabetic group and high low-density lipoprotein cholesterol group (p<0.05). Restricted cubic spline analysis showed a linear association between AIP levels and MACEs (p overall <0.05, p non-linear >0.05). Our study demonstrates the AIP independently predicts 2-year MACEs in STEMI patients post-PCI, particularly recurrent acute coronary syndrome, suggesting its utility as a cost-effective prognostic tool complementary to traditional lipid metrics.