title: A differential diagnostic model of diabetic nephropathy and non-diabetic renal diseases.
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: pi = e(z)/(1 + e(z)), a diagnostic model was constructed as follows: P(DN) = 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)]. P(DN) was the probability of DN diagnosis (P(DN) >or= 0.5 as DN, P(DN) < 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.
authors.affiliation: Department of Nephrology, Institute of Nephrology of Chinese PLA, General Hospital of Chinese PLA, Beijing, People's Republic of China.
authors.forename: Jianhui
authors.initials: J
authors.lastname: Zhou
authors.forename: Xiangmei
authors.initials: X
authors.lastname: Chen
authors.forename: Yuansheng
authors.initials: Y
authors.lastname: Xie
authors.forename: Jianjun
authors.initials: J
authors.lastname: Li
authors.forename: Nobuaki
authors.initials: N
authors.lastname: Yamanaka
authors.forename: Xinyuan
authors.initials: X
authors.lastname: Tong
mesh_terms: D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D000368:Aged; D001707:Biopsy, Needle; D002681:China; D003928:Diabetic Nephropathies / Q000175:diagnosis* / Q000453:epidemiology / Q000473:pathology; D003937:Diagnosis, Differential; D005260:Female; D006801:Humans; D007150:Immunohistochemistry; D015994:Incidence; D007668:Kidney / Q000473:pathology*; D007674:Kidney Diseases / Q000175:diagnosis / Q000453:epidemiology / Q000473:pathology; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D015999:Multivariate Analysis; D011336:Probability; D012372:ROC Curve; D012680:Sensitivity and Specificity; D017678:Sex Distribution