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  • Title: Phase angle assessment by bioelectrical impedance analysis and its predictive value for malnutrition risk in hospitalized geriatric patients.
    Author: Varan HD, Bolayir B, Kara O, Arik G, Kizilarslanoglu MC, Kilic MK, Sumer F, Kuyumcu ME, Yesil Y, Yavuz BB, Halil M, Cankurtaran M.
    Journal: Aging Clin Exp Res; 2016 Dec; 28(6):1121-1126. PubMed ID: 26786583.
    Abstract:
    BACKGROUND: Phase angle (PhA) value determined by bioelectrical impedance analysis (BIA) is an indicator of cell membrane damage and body cell mass. Recent studies have shown that low PhA value is associated with increased nutritional risk in various group of patients. However, there have been only a few studies performed globally assessing the relationship between nutritional risk and PhA in hospitalized geriatric patients. The aim of the study is to evaluate the predictive value of the PhA for malnutrition risk in hospitalized geriatric patients. METHODS: One hundred and twenty-two hospitalized geriatric patients were included in this cross-sectional study. Comprehensive geriatric assessment tests and BIA measurements were performed within the first 48 h after admission. Nutritional risk state of the patients was determined with NRS-2002. Phase angle values of the patients with malnutrition risk were compared with the patients that did not have the same risk. The independent variables for predicting malnutrition risk were determined. SPSS version 15 was utilized for the statistical analyzes. RESULTS: The patients with malnutrition risk had significantly lower phase angle values than the patients without malnutrition risk (p = 0.003). ROC curve analysis suggested that the optimum PhA cut-off point for malnutrition risk was 4.7° with 79.6 % sensitivity, 64.6 % specificity, 73.9 % positive predictive value, and 73.9 % negative predictive value. BMI, prealbumin, PhA, and Mini Mental State Examination Test scores were the independent variables for predicting malnutrition risk. CONCLUSIONS: PhA can be a useful, independent indicator for predicting malnutrition risk in hospitalized geriatric patients.
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