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Validity of malnutrition scores for predicting mortality in chronic hemodialysis patients

dc.contributor.authorToledo, Flavia R. [UNESP]
dc.contributor.authorAntunes, Aline A. [UNESP]
dc.contributor.authorVannini, Francieli C.D. [UNESP]
dc.contributor.authorSilveira, Liciana V.A. [UNESP]
dc.contributor.authorMartin, Luis Cuadrado [UNESP]
dc.contributor.authorBarretti, Pasqual [UNESP]
dc.contributor.authorCaramori, Jacqueline C.T. [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2014-05-27T11:29:47Z
dc.date.available2014-05-27T11:29:47Z
dc.date.issued2013-06-24
dc.description.abstractPurpose: 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. © 2013 Springer Science+Business Media Dordrecht.en
dc.description.affiliationDepartment of Internal Medicine, Faculdade de Medicina de Botucatu Universidade Estadual Paulista (UNESP), Rubião Junior, Botucatu, 18618-000
dc.description.affiliationDepartment of Biostatistics, Instituto de Biociências de Botucatu Universidade Estadual Paulista (UNESP), Botucatu
dc.description.affiliationUnespDepartment of Internal Medicine, Faculdade de Medicina de Botucatu Universidade Estadual Paulista (UNESP), Rubião Junior, Botucatu, 18618-000
dc.description.affiliationUnespDepartment of Biostatistics, Instituto de Biociências de Botucatu Universidade Estadual Paulista (UNESP), Botucatu
dc.format.extent1-6
dc.identifierhttp://dx.doi.org/10.1007/s11255-013-0482-3
dc.identifier.citationInternational Urology and Nephrology, p. 1-6.
dc.identifier.doi10.1007/s11255-013-0482-3
dc.identifier.issn0301-1623
dc.identifier.issn1573-2584
dc.identifier.lattes5496411983893479
dc.identifier.lattes4923203168446615
dc.identifier.orcid0000-0003-4979-4836
dc.identifier.scopus2-s2.0-84879038453
dc.identifier.urihttp://hdl.handle.net/11449/75701
dc.identifier.wosWOS:000327950000027
dc.language.isoeng
dc.relation.ispartofInternational Urology and Nephrology
dc.relation.ispartofjcr1.692
dc.relation.ispartofsjr0,653
dc.rights.accessRightsAcesso restrito
dc.sourceScopus
dc.subjectHemodialysis
dc.subjectMalnutrition
dc.subjectMortality
dc.subjectNutritional status
dc.subjectSurvival
dc.titleValidity of malnutrition scores for predicting mortality in chronic hemodialysis patientsen
dc.typeArtigo
dcterms.licensehttp://www.springer.com/open+access/authors+rights
dspace.entity.typePublication
unesp.author.lattes5496411983893479[6]
unesp.author.lattes4923203168446615
unesp.author.orcid0000-0003-4979-4836[6]
unesp.author.orcid0000-0001-8931-5495[4]
unesp.campusUniversidade Estadual Paulista (UNESP), Instituto de Biociências, Botucatupt
unesp.campusUniversidade Estadual Paulista (UNESP), Faculdade de Medicina, Botucatupt
unesp.departmentClínica Médica - FMBpt
unesp.departmentBioestatística - IBBpt

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