ArticleLipids in health and disease2025
Atherogenic index of plasma and subclinical vascular disease: predictive value for coronary and carotid atherosclerosis in a health screening population.
Article in Lipids in health and disease, 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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6 citing papers in PubMed.
- Atherogenic Index of Plasma as Predictor for Cardiovascular Events and Cardiometabolic Diseases:Findings from the PAMELA Study.High blood pressure & cardiovascular prevention : the official journal of the Italian Society of Hypertension · 2026Article
- Associations of cumulative exposure and dynamic trajectories of the combined atherogenic and frailty index with incident cardiometabolic multimorbidity: a longitudinal analysis based on the China Health and Retirement Longitudinal Study (CHARLS).Cardiovascular diabetology · 2026Article
- Article
- Association between the cumulative atherogenic index of plasma and cardiometabolic multimorbidity: the mediating effects of the TyG index and body mass index.Lipids in health and disease · 2026Article
- The correlation between the atherogenic index of plasma and aortic valve calcification in the general population: a retrospective observational cohort study.Frontiers in endocrinology · 2026Observational
- UHR as a systemic sensor of cumulative heat exposure and subclinical cardiovascular injury: evidence from 64,088 adults.Frontiers in public health · 2026Article
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5 authors.
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Abstract
objectiveTo evaluate the predictive value of the atherogenic index of plasma (AIP) for coronary artery calcification (CAC), carotid atherosclerosis (CA), and their coexistence, and to develop a multidimensional risk prediction model to optimize early cardiovascular disease (CVD) screening.
methodsA total of 32,992 individuals who underwent carotid intima-media thickness (CIMT) measurement and coronary CT calcium scoring at Sichuan Provincial People's Hospital between January and December 2023 were enrolled. Participants were classified into healthy, CAC, CA, and combined groups. AIP quartiles were derived from the cohort distribution. Nonparametric tests, Spearman correlation, and multivariable logistic regression with sequential covariate adjustments (Models 1-4) were applied. Predictive performance was assessed by sROC curves, AUC, and validated using bootstrap resampling and ten-fold cross-validation.
resultsAIP levels differed significantly across groups, being lowest in healthy individuals (0.01) and highest in the CAC and combined groups (0.09 and 0.06, respectively). Spearman correlations between AIP and atherosclerotic burden were strongest in healthy participants (ρ = 0.89) and progressively attenuated in CAC (ρ = 0.64) and combined groups (ρ = 0.43). Higher AIP quartiles were associated with increased risk of CA, CAC, and combined lesions, with Model 4 showing the highest predictive performance (AUC = 0.91 for combined lesions). Bootstrap and cross-validation confirmed model stability.
conclusionAIP may help identify early subclinical coronary and carotid atherosclerosis, and sequential adjustment with metabolic indicators improves predictive performance. External validation is warranted.
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