Journal of Southern Medical University ›› 2023, Vol. 43 ›› Issue (9): 1585-1590.doi: 10.12122/j.issn.1673-4254.2023.09.16

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Validation and comparison of diabetic retinopathy-based diagnostic models for diabetic nephropathy

LI Ying, WANG Qian, CHEN Xiaoniao, XI Yue, YANG Jian, LIU Xiaomin, WANG Yuanda, ZHANG Li, CAI Guangyan, CHEN Xiangmei, DONG Zheyi   

  1. Senior Department of Ophthalmology, Third Medical Center of Chinese PLA General Hospital, Beijing 100039, China; Department of Nephrology, First Medical Center of Chinese PLA General Hospital, Nephrology Institute of the Chinese People's Liberation Army, National Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Disease Research, Beijing 100853, China
  • Online:2023-09-20 Published:2023-09-28

Abstract: Objective To validate and compare the efficacy of two noninvasive diagnostic models for diabetic nephropathy (DN) based on diabetic retinopathy (DR). Methods A total of 565 patients with type 2 diabetes undergoing kidney biopsy in the Department of Nephrology, PLA General Hospital from January, 1993 to December, 2014 were studied. The patients were divided into DN group and non-diabetic nephropathy (NDRD) group according to renal pathological diagnosis. The data from the 22-year period were divided into 3 stages based on chronological order: early stage (from 1993 to 2003), middle stage (from 2004 to April, 2012), and late stage (from May, 2012 to December, 2014). The changes in clinical features and pathological diagnosis of the patients with renal biopsy over the 22 years were analyzed. The published DNT model and JDB model, both based on DR, were validated and compared for diagnostic effectiveness of DN, and the characteristics of the misdiagnosed cases were analyzed. Results The incidences of hypertension and DR and levels of glycosylated hemoglobin (HbA1c), creatinine and 24-h urinary protein were all significantly higher, while hemoglobin and triglyceride levels were lower in DN group than in NDRD group (P<0.05). The proportion of NDRD cases increased gradually over time, with IgA nephropathy and membranous nephropathy as the main pathological types. The AUC of JDB model was 0.946, similar to that of NDT model (0.925; P=0.198). The disease course of diabetes, hematuria and incidence of DR were important clinical features affecting the diagnostic accuracy of the models. Conclusion The clinical features and pathological diagnosis of DR change over time. The non-invasive diagnostic models based on DR have good diagnostic efficacy for DN.

Key words: diabetic nephropathy; diabetic retinopathy; diagnostic models