Correlation between retinal vascular geometric parameters and pathologically diagnosed type 2 diabetic nephropathy

Author:

Liu Fang12ORCID,Chen Xiaoniao3,Wang Qian1,Lin Wenwen12,Li Ying3,Zhang Ruimin14,Huang Hui12,Jiang Shuangshuang1,Niu Yue1,Liu Weicen1,Wang Liqiang3,Zhang Weiguang1,Zheng Ying1,Cao Xueying1,Wang Yong1,Wu Jie1,Zhang Li1,Tang Li1,Zhou Jianhui1,Chen Pu1,Cai Guangyan1,Dong Zheyi1ORCID

Affiliation:

1. Department of Nephrology, First Medical Center of Chinese PLA General Hospital, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research , Beijing , China

2. First Clinical Medical College, Guangdong Pharmaceutical University , Guangzhou , China

3. Senior Department of Ophthalmology, Third Medical Center, Chinese PLA General Hospital , Beijing , China

4. College of Basic Medical Sciences, Chengdu University of Traditional Chinese Medicine , Chengdu , China

Abstract

ABSTRACT Background Diabetic nephropathy (DN) and diabetic retinopathy (DR) are common microvascular complications of diabetes. The purpose of this study was to investigate the correlation between retinal vascular geometric parameters and pathologically diagnosed type 2 DN and to determine the capacity of retinal vascular geometric parameters in differentiating DN from non-diabetic renal disease (NDRD). Methods The study participants were adult patients with type 2 diabetes mellitus (T2DM) and chronic kidney disease who underwent a renal biopsy. Univariate and multivariable regression analyses were performed to evaluate associations between retinal vessel geometry parameters and pathologically diagnosed DN. Multivariate binary logistic regression analyses were performed to establish a differential diagnostic model for DN. Results In total, 403 patients were examined in this cross-sectional study, including 152 (37.7%) with DN, 157 (39.0%) with NDRD and 94 (23.3%) with DN combined with NDRD. After univariate logistic regression, total vessel fractal dimension, arteriolar fractal dimension and venular fractal dimension were all found to be associated with DN. In multivariate analyses adjusting for age, sex, blood pressure, diabetes, DR and other factors, smaller retinal vascular fractal dimensions were significantly associated with DN (P < .05). We developed a differential diagnostic model for DN combining traditional clinical indicators and retinal vascular geometric parameters. The area under the curve of the model established by multivariate logistic regression was 0.930. Conclusions Retinal vessel fractal dimension is of great significance for the rapid and non-invasive differentiation of DN. Incorporating retinal vessel fractal dimension into the diagnostic model for DN and NDRD can improve the diagnostic efficiency.

Funder

Science and Technology Project of Beijing, China

Beijing Natural Science Foundation

National Natural Science Foundation of China

Postdoctoral Innovative Talents Support Program of China

Publisher

Oxford University Press (OUP)

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