Longitudinal assessment of the nutritional status of patients with Chronic Kidney Disease: application of vector electrical bioimpedance

• Grant number: 19/26305-9
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Effective date (Start): December 01, 2020
• Effective date (End): November 30, 2021
• Field of knowledge: Health Sciences - Nutrition - Nutritional Analysis of Population
• Principal Investigator: Paula Garcia Chiarello
• Grantee: Gabriel Ruiz Sizoto
• Host Institution: Faculdade de Medicina de Ribeirão Preto (FMRP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil

Abstract

Chronic Kidney Disease (CKD) has altered nutritional status due to protein and energy catabolism commonly present in this population. Thus, serial and longitudinal assessment of nutritional status is important because it allows early detection of worsening of the condition, guiding a timely and resolute intervention. In this context, vector electrical bioimpedance (BIVA) has been highlighted as an appropriate method available in clinical routine. Thus, the aim of the present study is to evaluate the ability of classic and specific BIVA to estimate changes in body composition in patients with chronic kidney disease compared with DXA at a 1-year interval. We also evaluated the agreement between the nutritional status classifications obtained by BIVAc and BIVAe in patients with CKD. Ninety patients underwent conservative treatment, peritoneal dialysis, hemodialysis and kidney transplantation, in two evaluations with an interval of 1 year. Clinical and epidemiological data were collected. Body composition data were provided by DXA and entropometry evaluations. The resistance and reactance bioelectric parameters used in the BIVAc and BIVAe calculations were obtained by multifrequency bioelectrical impedance by tetra-polar whole-body protocol. Data will be presented as mean and standard deviation. The ANOVA test will be applied to compare the stratified groups in each of the BIVAc and BIVAe classifications separately. Unpaired t-test will be applied for comparisons between groups stratified into similar classifications by BIVAc and BIVAe. Paired t-test will be used for comparisons between cross-sectional and prospective data, as well as to evaluate the classification change by BIVAc and BIVAe (p <0.05).