title: Assessing glomerular filtration rate (GFR) in elderly Chinese patients with chronic kidney disease (CKD): a comparison of various predictive equations.
abstract: The aim of this study was to evaluate the applicability of formulas based on serum creatinine (SC) levels in elderly Chinese patients with CKD. A total of 103 elderly CKD patients were investigated. The GFR was estimated with Cockcroft-Gault-equation, MDRD1-equation, abbreviated MDRD-equation, Jelliffe-1973-equation, Mawer-equation, Hull-equation, Jelliffe-1971-equation, SC-reciprocal-equation, Gate-equation and Bjornsson-equation. The accuracy of estimated GFR (eGFR) values was compared with the 99mTc-DTPA-GFR (standardized GFR=sGFR) in elderly CKD patients. Bland-Altman analysis demonstrated that Hull-equation, Cockcroft-Gault-equation and Bjornsson-equation were better than the other ones. However, the agreement limits of all the equations exceeded the prior acceptable tolerances defined as 60 ml/min/(1.73 m(2)). Linear regressions showed that the slopes of Jelliffe-1973-equation, Cockcroft-Gault-equation and Bjornsson-equation were closer to the identical line. The median of difference of MDRD1-equation, abbreviated MDRD-equation and Gate-equation were smaller. Accuracy of Jelliffe-1973-equation, Cockcroft-Gault-equation and Hull-equation were better than those of the other equations. But 30% accuracy of all the equations were less than 70%. When compared the bias as well as accuracy of eGFR with sGFR values in different stages of CKD, GFR estimated by MDRD1-equation, Hull-equation, Cockcroft-Gault-equation and Jelliffe-1973-equation showed good results. These results suggested that when SC was checked with enzymatic method, GFR-estimation equations may show great bias in elderly Chinese CKD patients. Further improved formulas are needed to evaluate renal function in elderly Chinese patients with CKD.
authors.affiliation: Division of Nephrology, Department of Internal Medicine, The Third Affiliated Hospital of Sun Yet-sun University, Guangzhou, China.
authors.forename: Liu
authors.initials: L
authors.lastname: Xun
authors.forename: Wang
authors.initials: W
authors.lastname: Cheng
authors.forename: Tang
authors.initials: T
authors.lastname: Hua
authors.forename: Shi
authors.initials: S
authors.lastname: Chenggang
authors.forename: Chen
authors.initials: C
authors.lastname: Zhujiang
authors.forename: Ye
authors.initials: Y
authors.lastname: Zengchun
authors.forename: Lou
authors.initials: L
authors.lastname: Tanqi
mesh_terms: D000368:Aged; D044466:Asian People / Q000706:statistics & numerical data*; D002391:Catchment Area, Health; D002681:China / Q000453:epidemiology; D002908:Chronic Disease; D005260:Female; D005919:Glomerular Filtration Rate / Q000502:physiology*; D006801:Humans; D007674:Kidney Diseases / Q000175:diagnosis / Q000453:epidemiology / Q000503:physiopathology; D008297:Male; D008954:Models, Biological; D011237:Predictive Value of Tests; D011446:Prospective Studies; D012720:Severity of Illness Index