OBJECTIVE: Bioelectrical impedance analysis (BIA) is a fast, noninvasive method for assessing body composition, and its role in the evaluation of nutritional status in haemodialysis (HD) has been studied. This study aimed to compare BIA parameters to clinical, biochemical, and anthropometric markers of nutrition in HD patients, such as subjective global assessment modified for renal disease (SGA-1), serum albumin, body mass index (BMI), percent of standard body weight (%SBW), deviation of triceps skinfold thickness (TSF), mid-arm circumference (MAC), mid-arm muscle circumference (MAMC) from the standard value (50th percentile), anthropometry-derived fat (FM-A), and fat-free mass (FFM-A). METHODS: BIA was performed 30 minutes after a HD session and the reactance (Xc), resistance (R), phase angle (PA), body cell mass (BCM), fat mass (FM-BIA), and fat-free mass (FFM-BIA) values were recorded. The prevalence of malnutrition was estimated according to PA and percent of BCM. The correlation between methods was assessed through Pearson's correlation coefficient and Bland and Altman analysis. RESULTS: A total of 58 patients were studied (30 women and 28 men; mean age of 49.2 +/- 14.8 years). The mean PA was 6.19 +/- 1.33 degrees and the mean percent of BCM was 33.75 +/- 5.91%. The prevalence of malnutrition was 17.5% and 43.9% according to the PA and percent of BCM, respectively. PA had a negative correlation with age and SGA-1 score and a positive correlation with percent SBW, MAC, MAMC, FFM-A, and albumin. Percent of BCM had a negative correlation with age, MAC, MAMC and FM-A and a positive correlation with FFM-A and albumin. A significant correlation between FFM-A and FFM-BIA was observed, as well as between FM-A and FM-BIA. CONCLUSIONS: BIA indexes reflected nutritional state. PA and BCM seem to be less influenced by changes in volume and can be used for nutritional assessments of dialysis patients. (c) 2010 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.
OBJECTIVE: Bioelectrical impedance analysis (BIA) is a fast, noninvasive method for assessing body composition, and its role in the evaluation of nutritional status in haemodialysis (HD) has been studied. This study aimed to compare BIA parameters to clinical, biochemical, and anthropometric markers of nutrition in HDpatients, such as subjective global assessment modified for renal disease (SGA-1), serum albumin, body mass index (BMI), percent of standard body weight (%SBW), deviation of triceps skinfold thickness (TSF), mid-arm circumference (MAC), mid-arm muscle circumference (MAMC) from the standard value (50th percentile), anthropometry-derived fat (FM-A), and fat-free mass (FFM-A). METHODS: BIA was performed 30 minutes after a HD session and the reactance (Xc), resistance (R), phase angle (PA), body cell mass (BCM), fat mass (FM-BIA), and fat-free mass (FFM-BIA) values were recorded. The prevalence of malnutrition was estimated according to PA and percent of BCM. The correlation between methods was assessed through Pearson's correlation coefficient and Bland and Altman analysis. RESULTS: A total of 58 patients were studied (30 women and 28 men; mean age of 49.2 +/- 14.8 years). The mean PA was 6.19 +/- 1.33 degrees and the mean percent of BCM was 33.75 +/- 5.91%. The prevalence of malnutrition was 17.5% and 43.9% according to the PA and percent of BCM, respectively. PA had a negative correlation with age and SGA-1 score and a positive correlation with percent SBW, MAC, MAMC, FFM-A, and albumin. Percent of BCM had a negative correlation with age, MAC, MAMC and FM-A and a positive correlation with FFM-A and albumin. A significant correlation between FFM-A and FFM-BIA was observed, as well as between FM-A and FM-BIA. CONCLUSIONS: BIA indexes reflected nutritional state. PA and BCM seem to be less influenced by changes in volume and can be used for nutritional assessments of dialysis patients. (c) 2010 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.
Authors: C Demirci; G Aşcı; M S Demirci; M Özkahya; H Töz; S Duman; S Sipahi; S Erten; M Tanrısev; E Ok Journal: Int Urol Nephrol Date: 2016-04-19 Impact factor: 2.370
Authors: I Beberashvili; A Azar; I Sinuani; G Shapiro; L Feldman; K Stav; J Sandbank; Z Averbukh Journal: Eur J Clin Nutr Date: 2014-04-16 Impact factor: 4.016
Authors: Jung Eun Lee; In Young Jo; Song Mi Lee; Woo Jeong Kim; Hoon Young Choi; Sung Kyu Ha; Hyung Jong Kim; Hyeong Cheon Park Journal: Clin Interv Aging Date: 2015-08-13 Impact factor: 4.458