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The Role of Epicardial Fat Tissue at Cardiovascular Risk Assessment in Hemodialysis Patients with Nutritional Disorder

Abstract

Mustafa Demir, Omer Canpolat, Ayse Das Cerci and Ayhan Dogukan

Objective: Protein-energy malnutrition (PEM) is one of the most important risk factors in terms of morbidity and mortality in patients with end-stage renal disease (ESRD) receiving hemodialysis (HD). Therefore, in this population it is important to evaluate the nutritional status and body composition correctly. Our aim was to compare epicardial adipose tissue thickness (EAT) in HD patients with and without malnutrition.

Methods: Fifty-six patients were included in the study who were receiving HD therapy for ESRD. Mini Nutritional Assessment (MNA) was administered to determine the nutritional status of the patients. According to MNA scores; patients were divided into two groups as PEM+PEM risk group (group 1, n=25, score <24) and group with well-nourished (group 2, n=31, score ≥ 24). In addition, Tanita SC 330, a body composition analyzer, was used to evaluate the body composition of patients. Transthoracic echocardiography was performed to determine EAT.

Results: Of the 56 patients included in the study, 31 were male and 25 were female. EAT values were significantly different between the two groups (p=0.032). EAT value was higher in Group 2 than in Group 1 (p=0.032). Phosphor (P) (p=0.01) and CAXP (p=0.02) values were significantly higher in Group 2. In addition, fat mass (p=0.011), visceral fat percentage (p<0.001), muscle mass (p<0.001), metabolic age (p=0.01), lean body mass (p<0.001) and basal metabolic rate was significantly higher in Group 2. The highest positive correlation with EAT value was found with visceral fat ratio (r=0.600, p<0.001).

Conclusions: Malnutrition is a frequent problem in the HD population. We found low EAT in patients with malnutrition. As a result, we think that EAT can be used as a risk factor for KVC in patients without malnutrition.

Isenção de responsabilidade: Este resumo foi traduzido usando ferramentas de inteligência artificial e ainda não foi revisado ou verificado

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