Association Between the Atherogenic Index of Plasma and Risk of Large-Artery Atherosclerotic Ischemic Stroke

Wen Zhong¹Nini Zhu¹Xiaozhu Shen^1*Zhonglin Ge²Xiguang Liu³Guanghui Zhang⁴Qi Fang⁵Jingxian Liao^6*

• ¹Department of Geriatrics, Lianyungang Hospital Affiliated to Jiangsu University, Lianyungang, China, Lianyungang, China
• ²Second People's Hospital of Lianyungang, Lianyungang, Jiangsu Province, China
• ³The First People’s Hospital of Lianyungang, Lianyungang, Jiangsu Province, China
• ⁴Department of Neurology, Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu Province, China
• ⁵Department of Neurology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu Province, China
• ⁶Department of Geriatrics, Second People's Hospital of Lianyungang, Lianyungang, China

Objective: Ischemic stroke caused by large artery atherosclerosis (LAA) is a major subtype of ischemic stroke and poses a heavy public health burden. Plasma atherogenic index (AIP) reflects the balance between pro-and anti-atherogenic lipid components and has emerged as a potential biomarker of cardiovascular disease. The aim of this study was to investigate the role of AIP in predicting ischemic stroke caused by LAA.Methods: This retrospective, cross-sectional study involved 2382 ischemic stroke patients. AIP values were measured, and subjects were further stratified according to AIP levels. Univariate and multivariate logistic regression analyses were conducted to explore the relationship between AIP and the risk of LAA. Restricted cubic spline (RCS) analysis was used to detect the potential nonlinear relationship, and receiver operating characteristic (ROC) curve analysis was performed to evaluate the predictive ability of AIP. Subgroup analyses were carried out to identify specific populations with a higher risk of LAA.Results: Individuals with consistently high levels of AIP were at increased risk of developing LAA, and this risk increased progressively with increasing levels of AIP. RCS analyses showed a threshold of 0.10 for the AIP index, a significant increase in the probability of LAA above this threshold, and a nonlinear relationship between AIP and LAA. Univariate and multivariate logistic regression analyses showed that, as a continuous variable, each unit increase in AIP was significantly associated with an elevated risk of LAA. When divided into quartiles, the risk of LAA was higher in Q4 compared with the lowest quartile (Q1), and ROC curve analyses confirmed that AIP had moderate sensitivity and specificity in predicting LAA. Subgroup analyses showed that among individuals with consistently high AIP levels, those aged ≥ 60 years with a history of diabetes and low-density lipoprotein cholesterol (LDL-C) <3.4 mmol/L were at higher risk of developing LAA.Herein, we found that elevated AIP levels are significantly associated with increased LAA risk and are an important biomarker to help identify patients at high risk for LAA.