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Bioelectrical Impedance Analysis-Derived Phase Angle Predicts Protein-Energy Wasting in Maintenance Hemodialysis Patients.

OBJECTIVE(S)
To explore the validity of using bioelectrical impedance analysis (BIA)-derived 50 kHz phase angle (PhA) in predicting protein-energy wasting (PEW) in Chinese maintenance hemodialysis (MHD) patients.


DESIGN AND METHODS
The design was a cross-sectional study. A total of 173 of MHD patients and 173 healthy adults were enrolled in the study. The prevalence of PEW in patients was performed by the International Society of Renal Nutrition and Metabolism criteria. The PhA, body cell mass, fat mass, body fat percentage, fat-free mass, and extracellular water/total body water were measured by InBody S10 body composition analyzer. The biochemical indices and anthropometric measurements were assessed using the way published elsewhere. The PhA, other values of BIA and its relationship with age, visceral protein, anthropometric measurements of the MHD patients were compared with the healthy group. The independent variables for predicting PEW and its cutoff values were explored using logistic regression model and receiver operating characteristic curve analysis, respectively.


RESULTS
The MHD patients' PhA value was significantly lower than the healthy group (4.89°± 1.19 vs. 6.32°± 2.23, P < .01). A total of 34.1% MHD patients with PEW had significantly lower PhA values compared with well-nourished patients (P < .05). The PhA decreased more significantly with age in MHD (r = -0.35, P < .001), compared with controls (r = -0.26, P < .001). The PhA values were positively associated with nutritional indices related to serum albumin, prealbumin, fat-free mass, and mid-arm muscle circumference. PhA values were not associated significantly with fat mass and body fat percentage (P > .05). Multivariate logistic regression analysis showed that PhA and body mass index were independent predictors of PEW, but the PhA was the stronger predictor (odds ratio = 4.48, P < .05). Receiver operating characteristic curve analysis suggested that the optimal PhA cutoff value to predict PEW was 4.6°.


CONCLUSIONS
BIA-derived PhA appears to be a useful bioelectrical marker for predicting PEW in Chinese hemodialysis patients with a cutoff value of 4.6°.