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身体成分分析有助于预测慢性肾病患者的尿肌酐排泄及肾功能。

Body Composition Analysis Allows the Prediction of Urinary Creatinine Excretion and of Renal Function in Chronic Kidney Disease Patients.

作者信息

Donadio Carlo

机构信息

Department of Clinical and Experimental Medicine, Division of Nephrology, University of Pisa, I-56100 Pisa, Italy.

出版信息

Nutrients. 2017 May 28;9(6):553. doi: 10.3390/nu9060553.

Abstract

The aim of this study was to predict urinary creatinine excretion (UCr), creatinine clearance (CCr) and the glomerular filtration rate (GFR) from body composition analysis. Body cell mass (BCM) is the compartment which contains muscle mass, which is where creatinine is generated. BCM was measured with body impedance analysis in 165 chronic kidney disease (CKD) adult patients (72 women) with serum creatinine (SCr) 0.6-14.4 mg/dL. The GFR was measured (Tc-DTPA) and was predicted using the Modification of Diet in Renal Disease (MDRD) formula. The other examined parameters were SCr, 24-h UCr and measured 24-h CCr (mCCr). A strict linear correlation was found between 24-h UCr and BCM ( = 0.772). Multiple linear regression (MR) indicated that UCr was positively correlated with BCM, body weight and male gender, and negatively correlated with age and SCr. UCr predicted using the MR equation (MR-UCr) was quite similar to 24-h UCr. CCr predicted from MR-UCr and SCr (MR-BCM-CCr) was very similar to mCCr with a high correlation ( = 0.950), concordance and a low prediction error (8.9 mL/min/1.73 m²). From the relationship between the GFR and the BCM/SCr ratio, we predicted the GFR (BCM GFR). The BCM GFR was very similar to the GFR with a high correlation ( = 0.906), concordance and a low prediction error (12.4 mL/min/1.73 m²). In CKD patients, UCr, CCr and the GFR can be predicted from body composition analysis.

摘要

本研究的目的是通过身体成分分析预测尿肌酐排泄量(UCr)、肌酐清除率(CCr)和肾小球滤过率(GFR)。身体细胞质量(BCM)是包含肌肉质量的部分,而肌酐正是在肌肉中产生的。对165例慢性肾脏病(CKD)成年患者(72名女性)进行了身体阻抗分析以测量BCM,这些患者的血清肌酐(SCr)为0.6 - 14.4mg/dL。测量了GFR(Tc - DTPA)并使用肾病饮食改良(MDRD)公式进行预测。其他检测参数包括SCr、24小时UCr以及测量的24小时CCr(mCCr)。发现24小时UCr与BCM之间存在严格的线性相关性(= 0.772)。多元线性回归(MR)表明,UCr与BCM、体重和男性性别呈正相关,与年龄和SCr呈负相关。使用MR方程预测的UCr(MR - UCr)与24小时UCr非常相似。由MR - UCr和SCr预测的CCr(MR - BCM - CCr)与mCCr非常相似,具有高度相关性(= 0.950)、一致性且预测误差较低(8.9 mL/min/1.73 m²)。根据GFR与BCM/SCr比值之间的关系,我们预测了GFR(BCM GFR)。BCM GFR与GFR非常相似,具有高度相关性(= 0.906)、一致性且预测误差较低(12.4 mL/min/1.73 m²)。在CKD患者中,可以通过身体成分分析预测UCr、CCr和GFR。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5bc0/5490532/151cd746438b/nutrients-09-00553-g001.jpg

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