Metabolic Indices of Atherogenicity, Insulin Resistance, and Inflammation (AIP, TyG, and CTI) and the Risk of Renal Function Decline in Early-Stage CKM Syndrome: A Nationwide Prospective Cohort Study
TL;DR
Monitoring these composite indices and maintaining them within observed metabolic ranges may aid in early renal risk stratification and monitoring, though the exploratory statistical inflection points identified require validation in independent cohorts before clinical application.
Abstract
Background/Objectives: Cardiovascular–kidney–metabolic (CKM) syndrome, characterized by disturbances in glucose and lipid metabolism as its core pathophysiological feature, is a major driver of target organ damage. While early risk stratification in CKM stages 0–3 is critical to intercept renal decline, the practical utility of accessible metabolic surrogates remains poorly characterized. This study evaluated and compared the prospective capacity of the atherogenic index of plasma (AIP), triglyceride-glucose (TyG) index, and C-reactive protein–triglyceride glucose index (CTI) for predicting renal deterioration in early-stage CKM. Methods: Data were extracted from the China Health and Retirement Longitudinal Study (2011–2015). In total, 4064 participants aged ≥ 45 with CKM stages 0–3 (with exclusion of participants with baseline CKM stage 4) were prospectively followed. Renal function decline was defined as an estimated glomerular filtration rate (eGFR) decrease of ≥30% over 4 years, calculated using the CKD-EPI 2012 cystatin C equation. Multivariable logistic regression, restricted cubic splines (RCSs), and receiver operating characteristic (ROC) curves were applied. Results: Overall, 122 participants developed the renal outcome. In fully adjusted models, AIP, TyG, and CTI were valid independent risk factors for renal decline, with the lipid-driven AIP exhibiting the strongest association (OR = 5.54, 95% CI: 3.30–9.29; TyG: OR = 1.97, 95% CI: 1.49–2.59; CTI: OR = 1.63, 95% CI: 1.30–2.05; all p < 0.001). RCS analysis demonstrated significant non-linear dose–response trajectories, with renal risk escalating sharply past specific exploratory inflection points (AIP = 0.97, TyG = 7.80, CTI = 8.07). ROC curves confirmed robust predictive performance (AUCs > 0.75), with AIP performing optimally (AUC = 0.773). Conclusions: AIP, TyG, and CTI are independent longitudinal predictors of renal decline in early-stage CKM, with AIP demonstrating superior discriminatory power. Monitoring these composite indices and maintaining them within observed metabolic ranges may aid in early renal risk stratification and monitoring, though the exploratory statistical inflection points identified require validation in independent cohorts before clinical application.