Division of Nephrology, Internal Medicine Services, Landspitali - The National University Hospital of Iceland, Reykjavik, Iceland.
Nephron Clin Pract. 2013;123(1-2):22-7. doi: 10.1159/000351130. Epub 2013 Jun 6.
Differences in body composition may lead to imprecision in estimates of glomerular filtration rate (eGFR) derived from serum creatinine. Our aims were to examine the relationship between eGFR and anthropometric and body composition measures and handgrip strength.
We analyzed data from a cross-sectional study comprising 1,630 randomly selected community-dwelling adults. The Modification of Diet in Renal Disease (MDRD) and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations were used to calculate eGFR from IMDS-standardized serum creatinine. Body mass index and body surface area were calculated from measured height and weight. Body composition was determined by dual-energy x-ray absorptiometry, handgrip strength measured by a hand-held dynamometer. Regression analysis was used to examine the association between eGFR and other factors.
In women, eGFR determined by the MDRD equation was inversely associated with height (β = -0.08; p = 0.012), lean mass percentage (β = -0.06; p = 0.047) and handgrip strength (β = -0.15; p < 0.001) and eGFR calculated using the CKD-EPI equation was inversely associated with handgrip strength (β = -0.08; p = 0.001). In men, there was an inverse association between eGFR by the MDRD equation and lean mass percentage (β = -0.10; p = 0.013) and handgrip strength (β = -0.12; p = 0.022) and between eGFR by the CKD-EPI equation and lean mass percentage (β = -0.07; p = 0.018). The R(2) for these variables was <0.02.
The inverse relationship between eGFR and measures of lean mass percentage and handgrip strength suggests that incorporation of these variables might improve eGFR prediction from serum creatinine in the general population. This effect appears to be small however and needs to be examined in studies that include measured GFR.
身体成分的差异可能导致基于血清肌酐的肾小球滤过率(eGFR)估计不准确。我们的目的是检查 eGFR 与人体测量学和身体成分测量及握力之间的关系。
我们分析了一项横断面研究的数据,该研究包括 1630 名随机选择的社区居住成年人。使用改良肾脏病膳食研究(MDRD)和慢性肾脏病流行病学合作(CKD-EPI)方程,根据 IMDS 标准化的血清肌酐计算 eGFR。体重指数和体表面积由测量的身高和体重计算得出。身体成分通过双能 X 射线吸收法确定,握力通过手持测力计测量。回归分析用于检查 eGFR 与其他因素之间的关系。
在女性中,MDRD 方程计算的 eGFR 与身高(β=-0.08;p=0.012)、瘦体重百分比(β=-0.06;p=0.047)和握力(β=-0.15;p<0.001)呈负相关,CKD-EPI 方程计算的 eGFR 与握力呈负相关(β=-0.08;p=0.001)。在男性中,MDRD 方程计算的 eGFR 与瘦体重百分比(β=-0.10;p=0.013)和握力(β=-0.12;p=0.022)呈负相关,CKD-EPI 方程计算的 eGFR 与瘦体重百分比(β=-0.07;p=0.018)呈负相关。这些变量的 R²<0.02。
eGFR 与瘦体重百分比和握力等指标之间的负相关关系表明,将这些变量纳入一般人群中基于血清肌酐的 eGFR 预测可能会有所改善。然而,这种影响似乎很小,需要在包括测量 GFR 的研究中进行检验。