Evaluation of body composition monitoring for assessment of nutritional status in hemodialysis patients. (1st January 2019)

• Record Type: Journal Article
• Authors: Zhang, Haifen; Tao, Xingjuan; Shi, Ling; Jiang, Na; Yang, Yan
• Is Part Of: Renal failure. Volume 41:Number 1(2019)
• Page Start: 377
• Page End: 383
• Publication Date: 2019-01-01
• Subjects: Bioimpedance -- body composition -- lean tissue mass -- nutrition assessment -- end-stage renal disease; Chronic renal failure -- Periodicals; Acute renal failure -- Periodicals; Uremia -- Periodicals; 616.614005
• DOI: 10.1080/0886022X.2019.1608241
• Languages: English
• ISSNs: 0886-022X

Abstract

Abstract: Background: Body composition monitoring is the only clinically available method for distinguishing among the three body components. This study aimed to determine the relationship between body composition and all-cause mortality in Chinese hemodialysis patients and examine whether the lean tissue index (LTI) derived from body composition monitoring can accurately diagnose malnourished patients. Methods: Hemodialysis patients ( n = 123) with nutritional and body composition assessment records in 2015 were examined. Body composition was assessed using a body composition monitor machine. Results: Fifty-seven patients (46.3%) had low LTI (LTI less than the 10th percentile of the respective normal distribution). Significant differences in the fat tissue index (FTI) were observed, with the low LTI group having a higher FTI (10.8 kg/m 2 vs. 9.0 kg/m 2, p = .007). The kappa coefficient of agreement between LTI and subjective global assessment (SGA) was 0.26 for the presence of malnutrition. During the mean observation period of 26.7 months, 20 of 123 (16.3%) patients died. Low LTI remained highly predictive of survival in the Cox regression analysis (hazard ratio: 3.24, 95% confidence interval 1.06–9.91, p = .04). Malnourishment defined by SGA predicted survival in the Kaplan–Meier analysis (log-rank χ 2 =4.05; p = .04) but not in the multivariate analysis. Conclusions: LTI is a predictor of mortality, and its predictive power was not affected when FTI, SGA, and hydration status were included in the multivariate analysis. However, SGA may not be adequate to identify patients at a risk of death among Chinese hemodialysis patients.