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. 2016 Jun;9(3):374-80.
doi: 10.1093/ckj/sfw007. Epub 2016 Mar 24.

Fat tissue and inflammation in patients undergoing peritoneal dialysis

Abraham Rincón Bello  1 , Laura Bucalo  2 , Soraya Abad Estébanez  2 , Almudena Vega Martínez  2 , Daniel Barraca Núñez  2 , Claudia Yuste Lozano  2 , Ana Pérez de José  2 , Juan M López-Gómez  2
Affiliations

Fat tissue and inflammation in patients undergoing peritoneal dialysis

Abraham Rincón Bello et al. Clin Kidney J. 2016 Jun.

Abstract

Background: Body weight has been increasing in the general population and is an established risk factor for hypertension, diabetes, and all-cause and cardiovascular mortality. Patients undergoing peritoneal dialysis (PD) gain weight, mainly during the first months of treatment. The aim of this study was to assess the relationship between body composition and metabolic and inflammatory status in patients undergoing PD.

Methods: This was a prospective, non-interventional study of prevalent patients receiving PD. Body composition was studied every 3 months using bioelectrical impedance (BCM(®)). We performed linear regression for each patient, including all BCM(®) measurements, to calculate annual changes in body composition. Thirty-one patients in our PD unit met the inclusion criteria.

Results: Median follow-up was 26 (range 17-27) months. Mean increase in weight was 1.8 ± 2.8 kg/year. However, BCM(®) analysis revealed a mean increase in fat mass of 3.0 ± 3.2 kg/year with a loss of lean mass of 2.3 ± 4.1 kg/year during follow-up. The increase in fat mass was associated with the conicity index, suggesting that increases in fat mass are based mainly on abdominal adipose tissue. Changes in fat mass were directly associated with inflammation parameters such as C-reactive protein (r = 0.382, P = 0.045) and inversely associated with high-density lipoprotein cholesterol (r=-0.50, P = 0.008).

Conclusions: Follow-up of weight and body mass index can underestimate the fat mass increase and miss lean mass loss. The increase in fat mass is associated with proinflammatory state and alteration in lipid profile.

Keywords: fat mass; inflammation; metabolic syndrome; peritoneal dialysis.

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Figures

Fig. 1.
Fig. 1.
Baseline FTI correlations. FTI and age (A) and conicity index (B).
Fig. 2.
Fig. 2.
Inverse correlation between residual Kt/V and intraperitoneal glucose absorption.
Fig. 3.
Fig. 3.
Correlations between rates of increase in fat mass. (A) Inverse correlation between baseline fat percentage and fat percentage rate increase. (B) FTI rate increase and change in CRP per year. (C) FTI increase rate per year and change in HDL cholesterol per year.
See this image and copyright information in PMC

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