PURPOSE: Malnutrition is a strong predictor of mortality in hemodialysis patients. Several scoring systems for evaluating nutritional status have been proposed. However, they rely on different sets of anthropometric and laboratory markers to make a diagnosis of malnutrition and assess its impact on prognosis. To validate them, nutritional scores should be compared with clinical outcomes. Thus, the purpose of this study was to assess malnutrition by three different nutrition scoring systems and determine which best predicts mortality in hemodialysis patients. METHODS: This prospective study included 106 adult chronic hemodialysis patients. Their mean age was 56.3 ± 14.9 years and mean body mass index 24.8 (21.8-28.9); 52 % were men and they had been on dialysis for 24 (5-55) months. Nutritional status was classified according to the diagnostic systems proposed by Wolfson et al. (Am J Clin Nutr 39(4):547-555, 1984), International Society of Renal Nutrition and Metabolism (ISRNM) (Fouque et al. in Kidney Int 73(4):391-398, 2008), and Beberashvili et al. (Nephrol Dial Transplant 25(8):2662-2671, 2010). During about 2 years of follow-up, mortality was assessed by Kaplan-Meier curves, log-rank, and Cox's models adjusted for diabetes, sex, C-reactive protein, time on dialysis, age, and fractional urea clearance. RESULTS: Twenty-three deaths (21.5 %) occurred during the study period. According to the systems of Wolfson, Beberashvili, and the ISRNM, 54, 32, and 20 % of patients, respectively, had malnutrition. Both univariate and multivariate analyses showed that the ISRNM system was the only one that predicted poorer survival (fourfold higher death risk) in malnourished patients. CONCLUSIONS: The scoring system proposed by the ISRNM most accurately identifies patients at higher risk of death.
PURPOSE:Malnutrition is a strong predictor of mortality in hemodialysis patients. Several scoring systems for evaluating nutritional status have been proposed. However, they rely on different sets of anthropometric and laboratory markers to make a diagnosis of malnutrition and assess its impact on prognosis. To validate them, nutritional scores should be compared with clinical outcomes. Thus, the purpose of this study was to assess malnutrition by three different nutrition scoring systems and determine which best predicts mortality in hemodialysis patients. METHODS: This prospective study included 106 adult chronic hemodialysis patients. Their mean age was 56.3 ± 14.9 years and mean body mass index 24.8 (21.8-28.9); 52 % were men and they had been on dialysis for 24 (5-55) months. Nutritional status was classified according to the diagnostic systems proposed by Wolfson et al. (Am J Clin Nutr 39(4):547-555, 1984), International Society of Renal Nutrition and Metabolism (ISRNM) (Fouque et al. in Kidney Int 73(4):391-398, 2008), and Beberashvili et al. (Nephrol Dial Transplant 25(8):2662-2671, 2010). During about 2 years of follow-up, mortality was assessed by Kaplan-Meier curves, log-rank, and Cox's models adjusted for diabetes, sex, C-reactive protein, time on dialysis, age, and fractional urea clearance. RESULTS: Twenty-three deaths (21.5 %) occurred during the study period. According to the systems of Wolfson, Beberashvili, and the ISRNM, 54, 32, and 20 % of patients, respectively, had malnutrition. Both univariate and multivariate analyses showed that the ISRNM system was the only one that predicted poorer survival (fourfold higher death risk) in malnourished patients. CONCLUSIONS: The scoring system proposed by the ISRNM most accurately identifies patients at higher risk of death.
Authors: Milan D Stosovic; Radomir T Naumovic; Mirjana Lj Stanojevic; Sanja P Simic-Ogrizovic; Dijana B Jovanovic; Ljubica D Djukanovic Journal: Nutr Clin Pract Date: 2011-10 Impact factor: 3.080
Authors: Melissa Schorr; Braden J Manns; Bruce Culleton; Michael Walsh; Scott Klarenbach; Marcello Tonelli; Lia Sauve; Rick Chin; Lianne Barnieh; Brenda R Hemmelgarn Journal: J Ren Nutr Date: 2010-07-21 Impact factor: 3.655
Authors: D Fouque; K Kalantar-Zadeh; J Kopple; N Cano; P Chauveau; L Cuppari; H Franch; G Guarnieri; T A Ikizler; G Kaysen; B Lindholm; Z Massy; W Mitch; E Pineda; P Stenvinkel; A Treviño-Becerra; A Trevinho-Becerra; C Wanner Journal: Kidney Int Date: 2007-12-19 Impact factor: 10.612
Authors: Yongmei Liu; Josef Coresh; Joseph A Eustace; J Craig Longenecker; Bernard Jaar; Nancy E Fink; Russell P Tracy; Neil R Powe; Michael J Klag Journal: JAMA Date: 2004-01-28 Impact factor: 56.272