Nguyen H T, Shannon A G, Coates P A, Owens D R
University of Technology, Sydney, NSW, Australia.
IMA J Math Appl Med Biol. 1997 Jun;14(2):151-60.
The aim of this research was to develop an estimation of glomerular filtration rates (GFRs) from a combination of simple parameters in a large group of type II diabetic patients. We selected 122 newly presenting, previously untreated, type II patients whose GFR was determined from the plasma clearance of 51Cr-ethylenediamine tetraacetic acid (51Cr-EDTA) and simultaneous measurements of demographic variables, including fasting plasma glucose concentration, HbA1c, blood pressure, lipids, age, weight, body-mass index, body surface area, urea, and plasma creatinine concentration. The actual GFR values were compared with estimated values obtained from multiple regression and the Cockroft-Gault equations. Out of all the demographic variables, only plasma creatinine concentration (r = -0.56, p < 0.001), age (r = -0.50, p < 0.001), urea (r = -0.28, p < 0.01), and systolic blood pressure (r = -0.21, p < 0.05) showed significant correlations with the actual GFR values, for which the mean and standard deviation were 117.5 +/- 22.0 ml min-1 x 1.73 m-2. The estimated values are highly correlated with the actual values (r = 0.70), having an identical mean value of 117 +/- 15.3 and an unbiased regression relation (y = 0.000 + 1.000x). As standard measurements of the GFR are very time consuming and expensive, the use of the simple equation GFR1 = 218.1 - 0.916 x Age - 0.635 x Creatinine is recommended. The classification of GFR values into three ranges has also revealed the nonlinear characteristics of GFR in relation to other demographic variables: age and creatinine are the dominant variables in the middle GFR range, while the body-mass index and urea are dominant in the high and low ranges, respectively.
本研究的目的是通过一组简单参数来估算一大群II型糖尿病患者的肾小球滤过率（GFR）。我们选取了122例新诊断的、未经治疗的II型患者，通过51Cr-乙二胺四乙酸（51Cr-EDTA）血浆清除率测定其GFR，并同时测量人口统计学变量，包括空腹血糖浓度、糖化血红蛋白（HbA1c）、血压、血脂、年龄、体重、体重指数、体表面积、尿素和血浆肌酐浓度。将实际GFR值与通过多元回归和Cockcroft-Gault方程获得的估算值进行比较。在所有人口统计学变量中，只有血浆肌酐浓度（r = -0.56，p < 0.001）、年龄（r = -0.50，p < 0.001）、尿素（r = -0.28，p < 0.01）和收缩压（r = -0.21，p < 0.05）与实际GFR值显示出显著相关性，实际GFR值的均值和标准差为117.5 +/- 22.0 ml min-1 x 1.73 m-2。估算值与实际值高度相关（r = 0.70），均值相同，为117 +/- 15.3，且具有无偏回归关系（y = 0.000 + 1.000x）。由于GFR的标准测量非常耗时且昂贵，建议使用简单方程GFR1 = 218.1 - 0.916 x年龄 - 0.635 x肌酐。将GFR值分为三个范围也揭示了GFR与其他人口统计学变量之间的非线性特征：年龄和肌酐是中等GFR范围内的主要变量，而体重指数和尿素分别是高GFR范围和低GFR范围内的主要变量。
