ArticleMetabolites2025
Integrative Assessment of TyG Index, FIB-4, and eGFR as Composite Predictors of Metabolic Risk Clusters in Adults.
Article in Metabolites, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 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
- Age-Stratified Differences in Cardio-Reno-Metabolic Risk Profiles.Geriatrics (Basel, Switzerland) · 2026Article
- Psychiatric Comorbidity and Metabolic Heterogeneity in a Multimorbid Cardiometabolic Cohort: An Exploratory Real-World Analysis.Healthcare (Basel, Switzerland) · 2025Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
backgroundMetabolic syndrome involves interconnected disturbances in insulin sensitivity, hepatic function, and renal performance. Simple, integrative indices may improve early detection of multisystem metabolic risk.
methodsIn this cross-sectional study, adults were stratified into metabolic risk categories (scores 2-11) and evaluated using the triglyceride-glucose (TyG) index, the fibrosis-4 (FIB-4) score, and estimated glomerular filtration rate (eGFR). Correlation analyses and multivariate regression models (HC3 robust standard errors) were applied to identify independent predictors of hepatic (FIB-4) and renal (eGFR) function.
resultsTyG and FIB-4 increased significantly with higher metabolic risk (ANOVA
conclusionsThe combined use of TyG, FIB-4, and eGFR provides complementary insight into the metabolic-hepatic-renal continuum. These indices highlight progressive insulin resistance, hepatic stress, and subclinical renal involvement, supporting their utility as accessible tools for early identification of high-risk metabolic phenotypes.
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