Non-conventional lipid parameters predict the risk of rapid kidney function decline in patients with cardiovascular-kidney-metabolic syndrome: The first cohort study evidence from CHARLS

This study evaluates the predictive value of three novel lipid-derived biomarkers: non-HDL-to-HDL cholesterol ratio (NHHR); natural logarithm of remnant cholesterol (lnRC); and cholesterol, high-density lipoprotein, and glucose index (CHG) for rapid kidney function decline (RKFD) in patients with cardiovascular-kidney-metabolic (CKM) syndrome. Using data from the China Health and Retirement Longitudinal Study (CHARLS, 2011-2015), we evaluated 2734 CKM patients (stages 1-4) using RKFD as the primary endpoint. We assessed the associations of NHHR, lnRC, and CHG with renal outcomes using Logistic regression models. Restricted cubic spline and subgroup analyses were used to explore nonlinear relationships and consistency across population strata. Receiver operating characteristic (ROC) curve analysis compared the predictive performance of these indices. Fully adjusted Logistic models showed that a unit increase in NHHR was associated with a 19 % increased RKFD risk (p < 0.001). LnRC and CHG demonstrated more pronounced effects, with risks increasing by 112 % and 125 % per unit, respectively (both p < 0.001). Restricted cubic splines analysis revealed a linear relationship for NHHR and "J-shaped" associations for lnRC and CHG. ROC analysis showed improved discriminative capacity, with receiver operating characteristic curve values of 0.694 (NHHR), 0.734 (lnRC), and 0.695 (CHG). NHHR, lnRC, and CHG are significantly associated with RKFD in CKM patients and are robust predictors of renal function deterioration.