Body Composition in Dialysis Patients: A Functional Assessment of Bioimpedance Using Different Prediction Models

作者：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^*

来源：Journal of Renal Nutrition, 2015, 25(2): 121-128.

DOI：10.1053/j.jrn.2014.08.007

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 5.008) 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 DFFM (FFM 3-C 2 FFM 2-C) (r =0.361; P < .05) and DFM (FM 3-C 2 FM 2-C) (r = 0.387; P 5.009). 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 5.004) and HGS (r = 0.488; P 5.002), 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 Delta FFM and Delta FMof the 2-C and 3-Cmodels, is therefore an important parameter for the differences in estimation of BCparameters 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-mwalking testmay all be valuable tools in themultidimensional nutritional assessment of both hemodialysis and peritoneal dialysis patients.

• 出版日期2015-3