BACKGROUND: Hemodialysis (HD) patients are vulnerable to multiple metabolic and nutrition derangements, leading to changes in body composition. Handgrip strength (HGS) has been used as a nutrition marker. We aimed to evaluate the relationship between HGS and lean tissue mass (LTM) with several parameters in HD patients and develop HGS predictive equations. METHODS: Cross-sectional study with 155 patients in HD treatment for ≥3 months. Body composition was assessed through bioimpedance spectroscopy. HGS was measured with a hydraulic hand dynamometer. Biochemical parameters were evaluated. Data were analyzed by sex. RESULTS: Ninety-four were men, and mean age was 64.4 ± 14.7 years. We found positive correlation of HGS with LTM, lean tissue index, and body cell mass and negative correlation between HGS, age, and overhydration in both sexes. Serum albumin level presented a positive correlation and magnesium a negative correlation with HGS only in men. The LTM presented a positive correlation with protein intake, serum albumin level, and body cell mass and a negative correlation with age in both groups. A significant positive correlation with magnesium and a negative correlation with overhydration were observed in men. The predictability of the models was R2 = 0.618 for men and R2 = 0.500 for women. CONCLUSION: HGS is highly correlated with LTM, and both differ between sexes and are, therefore, differently correlated with the parameters studied. Body composition, overhydration, and some biochemical parameters explain changes in HGS. Predictive models including body composition and biochemical parameters may explain at least 50% of the variance of HGS.
BACKGROUND: Hemodialysis (HD) patients are vulnerable to multiple metabolic and nutrition derangements, leading to changes in body composition. Handgrip strength (HGS) has been used as a nutrition marker. We aimed to evaluate the relationship between HGS and lean tissue mass (LTM) with several parameters in HDpatients and develop HGS predictive equations. METHODS: Cross-sectional study with 155 patients in HD treatment for ≥3 months. Body composition was assessed through bioimpedance spectroscopy. HGS was measured with a hydraulic hand dynamometer. Biochemical parameters were evaluated. Data were analyzed by sex. RESULTS: Ninety-four were men, and mean age was 64.4 ± 14.7 years. We found positive correlation of HGS with LTM, lean tissue index, and body cell mass and negative correlation between HGS, age, and overhydration in both sexes. Serum albumin level presented a positive correlation and magnesium a negative correlation with HGS only in men. The LTM presented a positive correlation with protein intake, serum albumin level, and body cell mass and a negative correlation with age in both groups. A significant positive correlation with magnesium and a negative correlation with overhydration were observed in men. The predictability of the models was R2 = 0.618 for men and R2 = 0.500 for women. CONCLUSION: HGS is highly correlated with LTM, and both differ between sexes and are, therefore, differently correlated with the parameters studied. Body composition, overhydration, and some biochemical parameters explain changes in HGS. Predictive models including body composition and biochemical parameters may explain at least 50% of the variance of HGS.
Authors: Victor da Silva; Hugo Corrêa; Rodrigo Neves; Lysleine Deus; Andrea Reis; Michel Souza; Cláudio Dos Santos; Danilo de Castro; Fernando Honorato; Herbert Simões; Milton Moraes; Brad Schoenfeld; Jonato Prestes; Thiago Rosa Journal: Front Physiol Date: 2021-03-10 Impact factor: 4.566
Authors: Rens J R Gadaen; Jeroen P Kooman; Tom Cornelis; Frank M van der Sande; Bjorn J Winkens; Natascha J H Broers Journal: Nephron Date: 2020-10-27 Impact factor: 2.847