Evaluation of body composition monitoring for assessment of nutritional status in hemodialysis patients

Ren Fail. 2019 Nov;41(1):377-383. doi: 10.1080/0886022X.2019.1608241.

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/m2 vs. 9.0 kg/m2, 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 χ2=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.

Keywords: Bioimpedance; body composition; end-stage renal disease; lean tissue mass; nutrition assessment.

Publication types

  • Observational Study

MeSH terms

  • Aged
  • Body Composition / physiology*
  • Female
  • Humans
  • Kaplan-Meier Estimate
  • Kidney Failure, Chronic / complications
  • Kidney Failure, Chronic / mortality
  • Kidney Failure, Chronic / therapy*
  • Male
  • Malnutrition / diagnosis*
  • Malnutrition / etiology
  • Malnutrition / mortality
  • Middle Aged
  • Multivariate Analysis
  • Nutrition Assessment*
  • Nutritional Status / physiology
  • Predictive Value of Tests
  • Prognosis
  • Renal Dialysis / adverse effects*
  • Retrospective Studies

Grants and funding

This work was supported by the Science Research Grant from the Shanghai Municipal Commission of Health and Family Planning under Grant number 2015MS-B15; and Shanghai Municipal Education Commission – Nursing Gaoyuan Project under Grant number hlgy16028kygg.