Estimated glucose disposal rate and mortality risk in cardiovascular-kidney-metabolic syndrome: a population-based
Zheng Zhang1, Chao Fu1, Yiyi Chai1
1Department of Cardiology, The Second Affiliated Hospital of Harbin Medical University, No. 148, Baojian Road, Harbin, Heilongjiang Province, 150086, China.
Background:
Cardiovascular-kidney-metabolic (CKM) syndrome is a systemic disorder characterized by the interrelated dysfunction of metabolic abnormalities, chronic kidney disease, and cardiovascular injury, significantly increasing the risk of cardiovascular events and all-cause mortality. Insulin resistance (IR) plays an important role in the development and progression of CKM syndrome, but the relationship between estimated glucose disposal rate (eGDR) and mortality risk in CKM syndrome patients remains unclear, particularly across different glucose metabolic states.
Methods:
This cohort study used data from the National Health and Nutrition Examination Survey (NHANES 1999-2018) for CKM syndrome patients. We employed Cox regression and restricted cubic spline (RCS) analysis to assess the relationship between eGDR and mortality. Stratified analyses by glucose metabolism status and ROC curves compared the predictive performance of eGDR with TyG and HOMA-IR.
Results:
eGDR was significantly associated with all-cause and cause-specific mortality (P < 0.05). RCS analysis revealed a nonlinear relationship between eGDR and all-cause (P for non-linear = 0.041) and diabetes-specific mortality (P for non-linear = 0.003), while a linear relationship was found with cardiovascular mortality P for non-linear = 0.278). Stratified analysis showed eGDR's strongest predictive value for all-cause mortality in diabetes, cardiovascular mortality in prediabetes, and multiple mortality outcomes in normal glucose regulation (all P < 0.05). ROC analysis demonstrated superior predictive performance of eGDR compared to TyG and HOMA-IR, especially in the CKM syndrome and normal glucose regulation groups.
Conclusion:
Lower eGDR levels were independently associated with increased risks of all-cause, cardiovascular-specific, and diabetes-specific mortality in CKM syndrome patients. The relationship between eGDR and mortality was nonlinear for some outcomes. eGDR showed superior predictive performance, especially in individuals with normal glucose regulation and prediabetes, suggesting its potential as a biomarker for risk re-stratification and early intervention in CKM syndrome.
Clinical Trial Number:
Not applicable.
More Related Videos
09:40Phosphorus-31 Magnetic Resonance Spectroscopy: A Tool for Measuring In Vivo Mitochondrial Oxidative Phosphorylation Capacity in Human Skeletal Muscle
Published on: January 19, 2017
06:04Author Spotlight: Assessing the Cardiovascular Profile of Patients with Metabolic Syndrome
Published on: September 27, 2024
Related Concept Videos
01:28Drug Dosing in Renal Diseases: Estimation of Glomerular Filtration Rate Based on Serum Creatinine Concentration
01:17Factors Affecting Renal Clearance: Renal Impairment
One condition associated with renal failure is uremia. Uremia is characterized by impaired glomerular filtration and fluid accumulation in the body. This condition hinders the renal clearance of drugs, resulting in drug accumulation and potential...
01:15Diabetes: Symptoms, Diagnosis, and Complications
01:18Pharmacokinetics in Geriatric Patients: Effect of Age on Drug Excretion
01:25Drug Dosing in Renal Diseases: Measurement of Serum Creatinine Concentration and Clearance
01:23Renal Clearance
Renal clearance refers to the volume of plasma cleared of a specific substance, such as creatinine, per unit of time. To measure clearance, urine samples are collected over a 24-hour period during each bladder voiding, followed by a single blood sample at the...