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Background Patients with end-stage renal disease (ESRD) undergoing hemodialysis experience a rapid decline in skeletal muscle mass and strength. Hemodialysis removes amino acids (AAs) from the circulation, thereby lowering plasma AA concentrations and stimulating proteolysis. Objectives In the present study, we evaluate the impact of intradialytic protein ingestion at rest and following exercise on AA removal and plasma AA availability in patients with ESRD. Methods Ten patients (age: 65 +/- 16 y, male/female: 8/2, BMI: 24.2 +/- 4.8 kg/m(2), serum albumin: 3.4 +/- 0.3 g/dL) with ESRD undergoing hemodialysis participated in this randomized controlled crossover trial. During 4 hemodialysis sessions, patients were assigned to ingest 40 g protein or a placebo 60 min after initiation, both at rest (PRO and PLA, respectively) and following exercise (PRO + EX and PLA + EX, respectively). Spent dialysate and blood samples were collected every 30 min throughout hemodialysis to assess AA removal and plasma AA availability. Results Plasma AA concentrations declined by 26.1 +/- 4.5% within 30 min after hemodialysis initiation during all interventions (P < 0.001, eta(2)(p) > 0.79). Protein ingestion, but not intradialytic exercise, increased AA removal throughout hemodialysis (9.8 +/- 2.0, 10.2 +/- 1.6, 16.7 +/- 2.2, and 17.3 +/- 2.3 g during PLA, PLA + EX, PRO, and PRO + EX interventions, respectively; protein effect P < 0.001, eta(2)(p) = 0.97; exercise effect P = 0.32, eta(2)(p) = 0.11). Protein ingestion increased plasma AA concentrations until the end of hemodialysis, whereas placebo ingestion resulted in decreased plasma AA concentrations (time effect P < 0.001, eta(2)(p) > 0.84). Plasma AA availability (incremental AUC) was greater during PRO and PRO + EX interventions (49 +/- 87 and 70 +/- 34 mmol/L/240 min, respectively) compared with PLA and PLA + EX interventions (-227 +/- 54 and -208 +/- 68 mmol/L/240 min, respectively; protein effect P < 0.001, eta(2)(p) = 0.98; exercise effect P = 0.21, eta(2)(p) = 0.16). Conclusions Protein ingestion during hemodialysis compensates for AA removal and increases plasma AA availability both at rest and during recovery from intradialytic exercise. Intradialytic exercise does not compromise AA removal or reduce plasma AA availability during hemodialysis in a postabsorptive or postprandial state.

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 DeltaFFM (FFM 3-C - FFM 2-C) (r = 0.361; P < .05) and DeltaFM (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 DeltaFFM and DeltaFM 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.