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
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Updated: Jan 17, 2026
Assessment of Vascular Function in Patients With Chronic Kidney Disease
Published on: June 16, 2014
Mengying Dong1, Xueqi Chen2, Jiangen Liu3
1Department of Cardiology, the First Affiliated Hospital with Nanjing Medical University, 300 Guangzhou Road, Nanjing, 210029, Jiangsu, China.
Insights
Three novel lipid biomarkers, non-HDL-to-HDL cholesterol ratio (NHHR), natural logarithm of remnant cholesterol (lnRC), and cholesterol, high-density lipoprotein, and glucose index (CHG), predict rapid kidney function decline in cardiovascular-kidney-metabolic syndrome patients.
Area of Science:
- Cardiovascular Medicine
- Nephrology
- Metabolic Syndrome Research
Background:
- Cardiovascular-kidney-metabolic (CKM) syndrome poses a significant health burden.
- Identifying early predictors of kidney function decline in CKM patients is crucial.
Purpose of the Study:
- To evaluate the predictive value of three novel lipid-derived biomarkers for rapid kidney function decline (RKFD).
- Biomarkers assessed include non-HDL-to-HDL cholesterol ratio (NHHR), natural logarithm of remnant cholesterol (lnRC), and cholesterol, high-density lipoprotein, and glucose index (CHG).
Main Methods:
- Utilized data from the China Health and Retirement Longitudinal Study (CHARLS, 2011-2015).
- Analyzed 2734 CKM patients (stages 1-4) with RKFD as the primary endpoint.
- Employed Logistic regression, restricted cubic splines, subgroup analyses, and ROC curve analysis.
Main Results:
- Increased NHHR, lnRC, and CHG were significantly associated with higher RKFD risk (p < 0.001).
- lnRC and CHG showed more pronounced effects than NHHR.
- ROC analysis indicated improved discriminative capacity for these indices (AUCs: 0.694-0.734).
Conclusions:
- NHHR, lnRC, and CHG are robust predictors of renal function deterioration in CKM patients.
- These novel lipid biomarkers can aid in identifying patients at risk for RKFD.
Background:
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.
Methods:
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.
Results:
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).
Conclusions:
NHHR, lnRC, and CHG are significantly associated with RKFD in CKM patients and are robust predictors of renal function deterioration.
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