Literature DB >> 27491548

Bioelectrical impedance vector analysis as a useful predictor of nutritional status in patients with short bowel syndrome.

Priscila Giacomo Fassini1, Carolina Ferreira Nicoletti2, Karina Pfrimer2, Carla Barbosa Nonino2, Júlio Sérgio Marchini2, Eduardo Ferriolli2.   

Abstract

BACKGROUND & AIMS: Short bowel syndrome (SBS) represents a serious intestinal absorption disorder. Therefore, patients with SBS may have severe malnutrition and excessive mineral and fluid losses. Once the assessment of nutritional status is important in their follow-up, body composition measurements and especially total body water (TBW) must be repeatedly evaluated for the assessment of changes in hydration and nutritional care. The aim of this study was to investigate if bioelectrical impedance vector analysis (BIVA) is a useful predictor of nutritional and hydration status in SBS patients.
METHODS: In this observational study, 22 participants (12 women), 11 with SBS and 11 gender, age and BMI-matched controls, were evaluated using the bioelectrical impedance measurements (BIA) and BIVA to assess nutritional and hydration status.
RESULTS: Participants age was 53 ± 8 y (mean ± SD). Body water, fat mass and lean mass as assessed by BIA did not differ between the two groups. However, BIVA showed important differences between the groups regarding hydration and amount of soft tissue (p < 0.0001 for women and p = 0.0015 for men). The results also evidenced that women's vectors were related to cachexia, while men's vectors were divided into lean and cachexia quadrants. The use of BIVA analysis also evidenced hydration disturbance and losses of soft tissue.
CONCLUSIONS: BIVA may represent a better predictor of nutritional status for analysis and interpretation of body composition in patients with short bowel syndrome. This trial was registered at ClinicalTrials.gov as NCT02113228.
Copyright © 2016 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

Entities:  

Keywords:  Bioelectrical impedance analysis; Bioelectrical impedance vector analysis; Body composition; Nutritional status; Short bowel syndrome

Mesh:

Year:  2016        PMID: 27491548     DOI: 10.1016/j.clnu.2016.07.011

Source DB:  PubMed          Journal:  Clin Nutr        ISSN: 0261-5614            Impact factor:   7.324


  1 in total

1.  A human body physiological feature selection algorithm based on filtering and improved clustering.

Authors:  Bo Chen; Jie Yu; Xiu-E Gao; Qing-Guo Zheng
Journal:  PLoS One       Date:  2018-10-31       Impact factor: 3.240

  1 in total

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