SynthesisBMC cardiovascular disorders2025
Association between atherogenic index of plasma and various metabolic conditions: an umbrella review on meta-analyses.
Synthesis in BMC cardiovascular disorders, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Atherogenic Index of Plasma for the Prediction of Delirium in ICU Patients: A Retrospective Cohort Study Based on the MIMIC-IV Database.Brain and behavior · 2026Article
- Atherogenic index of plasma and the severity of coronary artery stenosis in patients with type 2 diabetes mellitus: a retrospective cross-sectional study.Frontiers in endocrinology · 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
- Association of plasma homocysteine with the atherogenic index of plasma and modification by body mass index: a cross-sectional study.Frontiers in cardiovascular medicine · 2026Article
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11 authors.
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Abstract
BACKGROUND AND
objectiveThe Atherogenic Index of Plasma (AIP) is increasingly recognized as a key indicator of lipid disturbances and an important predictor of cardiovascular disease (CVD) risk. Due to its ability to reflect outcomes linked to insulin resistance (IR), dyslipidemia, and atherosclerosis, this umbrella review seeks to compile evidence from multiple meta-analyses to assess clinical significance of AIP across different conditions.
methodsA comprehensive search was conducted in PubMed, Scopus, and Web of Science. Statistical analyses were performed using Comprehensive Meta-Analysis (CMA) software to aggregate results and assess the strength of the associations.
resultsThe results revealed substantial associations between AIP and various health outcomes. AIP was significantly associated with major adverse cardiovascular events (MACE) in acute coronary syndrome (ACS) (RR: 1.54, 95% CI: 1.30-1.82, P < 0.01). AIP was significantly associated with coronary artery disease (CAD), both as a categorical variable (OR: 2.74, 95% CI: 2.05-3.66, P < 0.01) and as a continuous variable (OR: 2.94, 95% CI: 1.85-4.66, P < 0.01). A higher AIP was significantly associated with myocardial infarction (MI) in CAD (RR: 2.21, 95% CI: 1.55-3.13, P < 0.01), coronary artery plaque (CAP) progression (OR: 1.49, 95% CI: 1.17-1.90, P < 0.01), and the development of multivessel lesions (OR: 2.04, 95% CI: 1.50-2.77, P < 0.01). Furthermore, revascularization in CAD was significantly associated with AIP (RR: 1.63, 95% CI: 1.34-1.97, P < 0.01). AIP was significantly associated with MACE in CAD, both as a categorical variable (RR: 1.66, 95% CI: 1.38-2.00, P < 0.01) and as a continuous variable (RR: 1.54, 95% CI: 1.30-1.82, p < 0.01). A higher AIP was significantly associated with CVD death in CAD (RR: 1.74, 95% CI: 1.09-2.77, p = 0.02). Additionally, the no-reflow phenomenon in CAD was significantly associated with AIP (RR: 3.12, 95% CI: 1.09-8.97, P = 0.03). For metabolic outcomes, a higher AIP was significantly associated with obstructive sleep apnea (OSA) (SMD: 0.71, 95% CI: 0.45-0.98, P < 0.01), type 2 diabetes mellitus (T2DM) (SMD: 1.78, 95% CI: 1.05-2.51, P< 0.01), and metabolic syndrome (MetS) (SMD: 0.78, 95% CI: 0.53-1.03, P< 0.01). All-cause mortality in CAD, stroke in CAD, and non-alcoholic fatty liver disease (NAFLD) were not significantly associated with AIP (RR: 1.15, 95% CI: 0.56-2.36, P = 0.69; RR: 1.03, 95% CI: 0.69-1.52, P = 0.90; SMD: 0.16, 95% CI: -0.18-0.50, P = 0.36, respectively).
conclusionAIP is significantly associated with a range of CVD and metabolic disorders. These findings suggest that AIP could serve as a valuable biomarker for diagnosing and assessing risk in CVD and metabolic conditions. However, AIP was not significantly associated with all-cause mortality in CAD, stroke in CAD, or NAFLD, highlighting the need for further research to evaluate its clinical utility in diverse patient populations. Clinicians may consider incorporating AIP into broader risk assessment strategies, particularly for patients with existing CVD or metabolic conditions. Additionally, AIP holds potential as a screening tool for large populations, offering clinicians a simple and cost-effective way to identify individuals at higher risk.
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