病态肥胖患者尿肌酐排泄量的估计及肾功能预测：来自身体成分分析的新工具

Estimation of Urinary Creatinine Excretion and Prediction of Renal Function in Morbidly Obese Patients: New Tools from Body Composition Analysis.

作者信息

Donadio Carlo, Moriconi Diego, Berta Rossana, Anselmino Marco

机构信息

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

Chirurgia Bariatrica, Azienda Ospedaliero Universitaria Pisana, Pisa, Italy.

出版信息

Kidney Blood Press Res. 2017;42(4):629-640. doi: 10.1159/000481630. Epub 2017 Oct 5.

DOI:10.1159/000481630

PMID:28977791

Abstract

BACKGROUND/AIMS: In obese subjects the accuracy of prediction of renal function is quite low. The aim of this study was to obtain a more accurate estimate of urinary creatinine excretion (UCr), creatinine clearance (CCr), and GFR from body cell mass (BCM).

METHODS

Seventy-three adult morbidly obese patients (BMI 35.2-64.5 kg/m2) were examined. BCM was calculated from body impedance analysis. CCr was measured (mCCr) and was predicted from BCM and antropometric data (MR-BCMCCr), with Cockcroft and Gault (C&GCCr) and Salazar and Corcoran (S&CCCr) formulas. GFR was predicted from BCM (BCM GFR) and with MDRD and CKD-EPI formulas.

RESULTS

Multiple regression (MR) indicated a strict linear correlation between UCr, BCM and anthropometric data. UCr predicted from MR equation (MR-BCMUCr) was very similar to measured UCr. MR-BCMCCr (168±46 mL/min) and mCCr (167±51 mL/min) were also similar, while significant differences were found between mCCr, C&GCCr and S&CCCr. The correlation and the agreement between MR-BCMCCr and mCCr were closer and prediction error was lower than the other formulas. BCM GFR (125±32 mL/min) had close correlations and agreements with MDRD GFR and CKD EPI formulas.

CONCLUSIONS

In morbidly obese patients the measurement of BCM meliorates the prediction of UCr and CCr, and allows the prediction of GFR.

摘要

背景/目的：在肥胖受试者中，肾功能预测的准确性相当低。本研究的目的是从身体细胞质量（BCM）更准确地估计尿肌酐排泄量（UCr）、肌酐清除率（CCr）和肾小球滤过率（GFR）。

方法

对73例成年病态肥胖患者（BMI 35.2 - 64.5 kg/m²）进行检查。通过人体阻抗分析计算BCM。测量CCr（mCCr），并根据BCM和人体测量数据采用Cockcroft和Gault（C&GCCr）以及Salazar和Corcoran（S&CCCr）公式预测CCr（MR-BCMCCr）。根据BCM（BCM GFR）以及MDRD和CKD-EPI公式预测GFR。

结果

多元回归（MR）表明UCr、BCM和人体测量数据之间存在严格的线性相关性。根据MR方程预测的UCr（MR-BCMUCr）与测量的UCr非常相似。MR-BCMCCr（168±46 mL/min）和mCCr（167±51 mL/min）也相似，而mCCr、C&GCCr和S&CCCr之间存在显著差异。MR-BCMCCr与mCCr之间的相关性和一致性更紧密，预测误差低于其他公式。BCM GFR（125±32 mL/min）与MDRD GFR和CKD EPI公式具有密切的相关性和一致性。