American Diabetes Association
eGFRdiff_and_DMCs_Supplementary_Material (1).pdf (559.46 kB)

The Difference between Cystatin C- and Creatinine-Based Estimated Glomerular Filtration Rate and Risk of Diabetic Microvascular Complications among Adults with Diabetes: A population-based cohort study

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posted on 2024-03-12, 18:25 authored by Daijun He, Bixia Gao, Jinwei Wang, Chao Yang, Ming-Hui Zhao, Luxia Zhang

The impact of the difference between cystatin C- and creatinine-based estimated glomerular filtration rate (eGFRdiff) on diabetic microvascular complications (DMCs) remains unknown. We aimed to investigate the associations of eGFRdiff with overall DMCs and subtypes including diabetic retinopathy (DR), diabetic kidney disease (DKD), and diabetic neuropathy (DN).

Research Design and Methods

This prospective cohort study included 25,825 participants with diabetes free of DMCs at baseline (2006 to 2010) from the UK Biobank. eGFRdiff was calculated using both absolute difference (eGFRabdiff) and the ratio (eGFRrediff) between cystatin C- and creatinine-based calculations. Incidence of DMCs was ascertained using electronic health records. Cox proportional hazards regression models were used to evaluate the associations of eGFRdiff with overall DMCs and subtypes.


During a median follow-up of 13.6 years, 5,753 participants developed DMCs, including 2,752 cases of DR, 3,203 DKD, and 1,149 DN. Each standard-deviation decrease of eGFRabdiff was associated with a 28% higher risk of overall DMCs, 14% higher risk of DR, 56% higher risk of DKD, and 29% higher risk of DN. For each 10-percent decrease in eGFRrediff, the corresponding hazard ratios (95% confidence intervals) were 1.16 (1.14, 1.18) for overall DMCs, 1.08 (1.05, 1.11) for DR, 1.29 (1.26, 1.33) for DKD, and 1.17 (1.12, 1.22) for DN respectively. The magnitude of associations was not materially altered in all sensitivity analyses.


Large eGFRdiff was independently associated with risk of DMCs and its subtypes. Our findings suggested monitoring eGFRdiff among diabetes population have potentially beneficial for identification of high-risk patients.


This study was supported by grants from the National Key Research and Development Program of China (2022YFF1203001), National Natural Science Foundation of China (72125009, 81771938, 81900665, 82003529, 82090021), National Key R&D Program of the Ministry of Science and Technology of China (2019YFC2005000), Chinese Scientific and Technical Innovation Project 2030 (2018AAA0102100), Young Elite Scientists Sponsorship Program by CAST (2022QNRC001), CAMS Innovation Fund for Medical Sciences (2019-I2M-5-046), and PKU-Baidu Fund (2020BD004, 2020BD005).