title: Development and validation of new glomerular filtration rate predicting models for Chinese patients with type 2 diabetes.
abstract: BACKGROUND
  Previous researches has depicted that the performance of the recommended glomerular filtration rate (GFR)-estimating equations in the type 2 diabetic population is inferior to that in the non-diabetic population. We attempted to develop new GFR-predicting models for use in Chinese patients with type 2 diabetes in this study.
  
  
  METHODS
  We enrolled 519 type 2 diabetic patients including a development data-set (n = 276), an internal validation data-set (n = 138) and an external validation data-set (n = 105) to establish new GFR-predicting models. 99mTc-DTPA-GFR revised by the dual sample method was referred to as the gold GFR standard.
  
  
  RESULTS
  Based on sex, age, serum creatinine and new predictor variables [body mass index (BMI), hemoglobinA1C, and urinary albumin creatinine ratio], eight new regression models and eight artificial neural network (ANN) models were developed. In the external validation group, only ANN3 was superior in both precision and accuracy over the original CKD-EPI equation (precision, 20.5 vs. 24.2 mL/min/1.73 m(2), P < 0.001; 30 % accuracy, 88.6 vs. 80.6 %, P = 0.02).
  
  
  CONCLUSIONS
  ANN3 based on sex, age, serum creatinine and BMI is the optimal model for GFR estimation in Chinese patients with type 2 diabetes.
authors.affiliation: Division of Nephrology, Department of Internal Medicine, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510630, China. chenjinxiaweikang@163.com.|Institute of Nephrology, Guangdong Medical College, Zhanjiang, Guangdong, China. chenjinxiaweikang@163.com.
authors.forename: Jinxia
authors.initials: J
authors.lastname: Chen
authors.affiliation: Division of Nephrology, Department of Internal Medicine, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510630, China. dialysiscenter@163.com.
authors.forename: Hua
authors.initials: H
authors.lastname: Tang
authors.affiliation: Department of Cardiology, Guangdong Province Key Laboratory of Arrhythmia and Electrophysiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China. huanghui765@hotmail.com.
authors.forename: Hui
authors.initials: H
authors.lastname: Huang
authors.affiliation: Operation Room, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China. lv.linsheng@163.com.
authors.forename: Linsheng
authors.initials: L
authors.lastname: Lv
authors.affiliation: Division of Nephrology, Department of Internal Medicine, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510630, China. wangyanni0707@126.com.
authors.forename: Yanni
authors.initials: Y
authors.lastname: Wang
authors.affiliation: Division of Nephrology, Department of Internal Medicine, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510630, China. naturestyle@163.com.
authors.forename: Xun
authors.initials: X
authors.lastname: Liu
authors.affiliation: Division of Nephrology, Department of Internal Medicine, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510630, China. lou.tq@163.com.
authors.forename: Tanqi
authors.initials: T
authors.lastname: Lou
mesh_terms: D000328:Adult; D000368:Aged; D000418:Albumins / Q000032:analysis; D015992:Body Mass Index; D002681:China; D003404:Creatinine / Q000097:blood; D055316:Cystatin C / Q000097:blood; D003924:Diabetes Mellitus, Type 2 / Q000097:blood* / Q000150:complications / Q000175:diagnosis*; D005260:Female; D005919:Glomerular Filtration Rate; D006442:Glycated Hemoglobin / Q000378:metabolism; D006801:Humans; D007444:Inulin / Q000378:metabolism; D000069550:Machine Learning; D008297:Male; D008875:Middle Aged; D016571:Neural Networks, Computer; D011897:Random Allocation; D012044:Regression Analysis; D051436:Renal Insufficiency, Chronic / Q000097:blood* / Q000150:complications* / Q000175:diagnosis; D015203:Reproducibility of Results; D001613:beta 2-Microglobulin / Q000097:blood
chemical_list: D000418:Albumins; D003404:Creatinine; D055316:Cystatin C; D006442:Glycated Hemoglobin; D007444:Inulin; D001613:beta 2-Microglobulin; C517652:hemoglobin A1c protein, human