Serum albumin, subjective global assessment, body mass index and the bioimpedance analysis in the assessment of malnutrition in patients up to 15 years after liver transplantation.

Wagner D, Adunka C, Kniepeiss D, Jakoby E, Schaffellner S, Kandlbauer M, Fahrleitner-Pammer A, Roller RE, Kornprat P, Muller H, Iberer F, Tscheliessnigg KH. Serum albumin, subjective global assessment, body mass index and the bioimpedance analysis in the assessment of malnutrition in patients up to 15 years after liver transplantation. Clin Transplant 2011: 25: E396–E3400. © 2011 John Wiley & Sons A/S. Abstract:  Background:  The subjective global assessment (SGA) or the body mass index (BMI) is used to determine the nutritional state after LTX. Bioelectrical impedance analysis (BIA) is used as tool to determine body composition by nutritional care professionals. Methods:  BIA, SGA, BMI, and serum albumin (SA) levels were performed to assess malnutrition following liver transplantation. BIA measurement was used as reference standard to determine existing malnutrition. A phase angle (PA) <5 was used to define potentially existing chronic disease-related malnutrition as a standard. All other measured parameters were compared with respect to their prognostic accuracy regarding the prediction of malnutrition as compared to the mentioned standard. Results:  Seventy-one recipients (51 men, 20 women) were included. Median age was 58, weight 77 kg, BMI 26 kg/m2, PA 4.1°, and SA 4.3 g/dL. According to the Nutritional Risk Screening 2002, 9.4% (6/71), to BMI 15.4% (11/71), to SA 30.9% (22/71), and to BIA 36.5% (28/71) of the patients were malnourished. PA did not correlate with BMI or NA, there was a significant correlation with SA (p = 0.001). Univariate analysis revealed SA as independent predictor for malnutrition. ROC analysis for all parameters revealed a significantly (p < 0.05) better area under the receiver operating characteristic curve for SA (0.812) than for BMI (0.603) for the prediction of malnutrition. Conclusion:  SGA or BMI calculation alone does not suffice to evaluate the nutritional status. SA seems to play a crucial role in the prediction of severe disease-related malnutrition in this special patient cohort.