NDT Advance Access originally published online on December 21, 2007
Nephrology Dialysis Transplantation 2008 23(6):1940-1945; doi:10.1093/ndt/gfm897
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
A differential diagnostic model of diabetic nephropathy and non-diabetic renal diseases
1 Department of Nephrology, Institute of Nephrology of Chinese PLA, General Hospital of Chinese PLA, Beijing, People's Republic of China 2 Department of Pathology, Nippon Medical School, Tokyo, Japan 3 Department of Medical Statistics, General Hospital of Chinese PLA, Beijing, People's Republic of China
Correspondence and offprint requests to: Xiangmei Chen, Institute of Nephrology of Chinese PLA, General Hospital of Chinese PLA, Fuxing Road 28, Beijing 100853, People's Republic of China. Tel: +86-10-66937011; Fax: +86-10-68130297; E-mail: xmchen301{at}126.com
 |
Abstract |
|---|
Background. Renal diseases in diabetes include diabetic nephropathies (DN) and non-diabetic renal diseases (NDRD). The clinical differentiation between these two categories is usually not so clear and effective. This study aims to develop a quantified differential diagnostic model.
Methods. We consecutively screened the diabetic patients with overt proteinuria but no severe renal failure for kidney biopsy from 1993 to 2003. The finally enrolled 110 patients were divided into two groups according to pathological features (60 in DN group and 50 in NDRD group). Clinical and laboratory data were compared between two groups. Then a diagnostic model was developed based on the logistic regression analysis.
Results. Forty-six percent of patients were NDRD including a variety of pathological types. Many differences between DN and NDRD were found by comparison of the clinical indices. In the final logistic regression analysis, only diabetes duration (Dm), systolic blood pressure (Bp), HbA1c (Gh), haematuria (Hu) and diabetic retinopathy (Dr) showed statistical significance. Based on the logistic regression model: 
= ez/(1 + ez), a diagnostic model was constructed as follows: PDN = exp(–13.5922 + 0.0371Dm + 0.0395Bp + 0.3224Gh – 4.4552Hu + 2.9613Dr)/ [1 + exp(–13.5922 + 0.0371Dm + 0.0395Bp + 0.3224Gh – 4.4552Hu + 2.9613Dr)]. PDN was the probability of DN diagnosis (PDN 
0.5 as DN, PDN < 0.5 as NDRD). Validation tests showed that this model had good sensitivity (90%) and specificity (92%).
Conclusions. This diagnostic model may be helpful to clinical differentiation of DN and NDRD in type 2 diabetic patients with overt proteinuria.
Keywords: diabetic nephropathies; differential diagnosis; discriminant analysis; type 2 diabetes mellitus
Received for publication: 17. 5.07
Accepted in revised form: 26.11.07