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透析患者的身体成分:使用不同预测模型对生物电阻抗进行功能评估。

Body composition in dialysis patients: a functional assessment of bioimpedance using different prediction models.

作者信息

Broers Natascha J H, Martens Remy J H, Cornelis Tom, Diederen Nanda M P, Wabel Peter, van der Sande Frank M, Leunissen Karel M L, Kooman Jeroen P

机构信息

Division of Nephrology, Department of Internal Medicine, University Hospital Maastricht, Maastricht, The Netherlands.

Fresenius Medical Care D GmbH, Research and Development, Bad Homburg, Germany.

出版信息

J Ren Nutr. 2015 Mar;25(2):121-8. doi: 10.1053/j.jrn.2014.08.007. Epub 2014 Oct 16.

Abstract

OBJECTIVES

The assessment of body composition (BC) in dialysis patients is of clinical importance given its role in the diagnosis of malnutrition and sarcopenia. Bioimpedance techniques routinely express BC as a 2-compartment (2-C) model distinguishing fat mass (FM) and fat-free mass (FFM), which may be influenced by the hydration of adipose tissue and fluid overload (OH). Recently, the BC monitor was introduced which applies a 3-compartment (3-C) model, distinguishing OH, adipose tissue mass, and lean tissue mass. The aim of this study was to compare BC between the 2-C and 3-C models and assess their relation with markers of functional performance (handgrip strength [HGS] and 4-m walking test), as well as with biochemical markers of nutrition.

METHODS

Forty-seven dialysis patients (30 males and 17 females) (35 hemodialysis, 12 peritoneal dialysis) with a mean age of 64.8 ± 16.5 years were studied. 3-C BC was assessed by BC monitor, whereas the obtained resistivity values were used to calculate FM and FFM according to the Xitron Hydra 4200 formulas, which are based on a 2-C model.

RESULTS

FFM (3-C) was 0.99 kg (95% confidence interval [CI], 0.27 to 1.71, P = .008) higher than FFM (2-C). FM (3-C) was 2.43 kg (95% CI, 1.70-3.15, P < .001) lower than FM (2-C). OH was 1.4 ± 1.8 L. OH correlated significantly with ΔFFM (FFM 3-C - FFM 2-C) (r = 0.361; P < .05) and ΔFM (FM 3-C - FM 2-C) (r = 0.387; P = .009). HGS correlated significantly with FFM (2-C) (r = 0.713; P < .001), FFM (3-C) (r = 0.711; P < .001), body cell mass (2-C) (r = 0.733; P < .001), and body cell mass (3-C) (r = 0.767; P < .001). Both physical activity (r = 0.456; P = .004) and HGS (r = 0.488; P = .002), but not BC, were significantly related to walking speed.

CONCLUSIONS

Significant differences between 2-C and 3-C models were observed, which are partly explained by the presence of OH. OH, which was related to ΔFFM and ΔFM of the 2-C and 3-C models, is therefore an important parameter for the differences in estimation of BC parameters of the 2-C and 3-C models. Both FFM (3-C) and FFM (2-C) were significantly related to HGS. Bioimpedance, HGS, and the 4-m walking test may all be valuable tools in the multidimensional nutritional assessment of both hemodialysis and peritoneal dialysis patients.

摘要

目的

鉴于身体成分(BC)在营养不良和肌肉减少症诊断中的作用,对透析患者的身体成分评估具有临床重要性。生物阻抗技术通常将身体成分表示为区分脂肪量(FM)和去脂体重(FFM)的两室(2-C)模型,这可能会受到脂肪组织水合作用和液体超负荷(OH)的影响。最近,引入了采用三室(3-C)模型的身体成分监测仪,该模型可区分OH、脂肪组织量和瘦组织量。本研究的目的是比较2-C和3-C模型之间的身体成分,并评估它们与功能表现指标(握力[HGS]和4米步行试验)以及营养生化指标的关系。

方法

对47例透析患者(30例男性和17例女性)(35例血液透析,12例腹膜透析)进行研究,平均年龄为64.8±16.5岁。通过身体成分监测仪评估3-C身体成分,而根据基于2-C模型的Xitron Hydra 4200公式,使用获得的电阻值来计算FM和FFM。

结果

FFM(3-C)比FFM(2-C)高0.99千克(95%置信区间[CI],0.27至1.71,P = 0.008)。FM(3-C)比FM(2-C)低2.43千克(95%CI,1.70 - 3.15,P < 0.001)。OH为1.4±1.8升。OH与ΔFFM(FFM 3-C - FFM 2-C)(r = 0.361;P < 0.05)和ΔFM(FM 3-C - FM 2-C)(r = 0.387;P = 0.009)显著相关。HGS与FFM(2-C)(r = 0.713;P < 0.001)、FFM(3-C)(r = 0.711;P < 0.001)、身体细胞量(2-C)(r = 0.733;P < 0.001)和身体细胞量(3-C)(r = 0.767;P < 0.001)显著相关。身体活动(r = 0.456;P = 0.004)和HGS(r = 0.488;P = 0.002),而非身体成分,与步行速度显著相关。

结论

观察到2-C和3-C模型之间存在显著差异,部分原因是存在OH。因此,OH与2-C和3-C模型的ΔFFM和ΔFM相关,是2-C和3-C模型身体成分参数估计差异的重要参数。FFM(3-C)和FFM(2-C)均与HGS显著相关。生物阻抗、HGS和4米步行试验可能都是血液透析和腹膜透析患者多维营养评估中有价值的工具。

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