ArticleFrontiers in neurology2025
Association between the atherogenic index of plasma and risk of large-artery atherosclerotic ischemic stroke.
Article in Frontiers in neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Joint association of triglyceride-glucose (TyG) and atherogenic index of plasma (AIP) with stroke risk: findings from a nationwide prospective cohort.Cardiovascular diabetology · 2026Article
- Fasting blood glucose trajectories and atherosclerosis risk: a longitudinal cohort study with threshold analysis in Chongqing, China.Journal of health, population, and nutrition · 2026Article
- Association between non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR), atherogenic index of plasma and acute ischemic stroke classified by CISS.Frontiers in neurology · 2026Article
- Association between the atherogenic index of plasma and prehypertension or hypertension among adults in Fujian, China: a population-based cross-sectional study.Frontiers in cardiovascular medicine · 2026Article
- Nonlinear relationship between incidence of new-onset stroke and plasma atherosclerotic index in middle-aged and older adults.Frontiers in neurology · 2025Article
- Identifying metabolic parameters as key indicators of hyperuricemia and ischemic stroke comorbidity via interpretable Clinlabomics models.Frontiers in endocrinology · 2025Article
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8 authors.
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Abstract
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 2,382 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 non-linear 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 non-linear 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. Conclusion: 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.
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