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      Comparison of Bioelectrical Impedance Vector Analysis (BIVA) to 7-point Subjective Global Assessment for the diagnosis of malnutrition Translated title: Comparação da Análise Vetorial de Impedância Bioelétrica (BIVA) com a Avaliação Subjetiva Global de 7 pontos para o diagnóstico de desnutrição

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          Abstract

          Introduction:

          Bioelectrical impedance vector analysis (BIVA) is a non-invasive and low-cost strategy. The methods used to assess malnutrition in patients undergoing HD are still a challenge. The aim of the present study was to compare BIVA to 7-Point Subjective Global Assessment (7-point SGA) to identify malnutrition. We also investigated the sensitivity and specificity of the previously proposed cutoffs point for BIVA parameters.

          Methods:

          Patients of both sexes, over 20 years of age, on HD treatment were included. Anthropometric parameters, laboratory data, and bioelectrical impedance analysis (BIA) were evaluated. Values of resistance (R) and reactance (Xc) obtained by mono-frequency BIA were normalized to body height (H) to generate a graph of the bioimpedance vector with the BIVA software. The analysis of the area under the receiver operating curve ROC (AUC) was performed.

          Results:

          Among the included 104 patients, the mean age was 51.70 (±15.10) years, and 52% were male. The BIVA had a sensitivity of 35% for diagnosing malnutrition. The specificity of BIVA for identifying the well-nourished patients was 85.7%. The diagnostic accuracy between the BIVA and 7-point SGA was AUC=0.604; 95%CI 0.490-0.726, higher than the previously established cutoff values (AUC=0.514; 95%CI: 0.369-0.631). The 95% confidence ellipses did not overlap (p<0.05).

          Conclusion:

          Our study showed low accuracy of BIVA for diagnosing malnutrition using a 7-point SGA as a reference standard. However, it is a complementary method for assessing nutritional status as it provides data on cellularity and hydration, which are important aspects for the HD population.

          Resumo

          Introdução:

          Análise vetorial de impedância bioelétrica (BIVA) é uma estratégia não invasiva e de baixo custo. Os métodos usados para avaliar desnutrição em pacientes em HD ainda são um desafio. O objetivo do presente estudo foi comparar BIVA com Avaliação Subjetiva Global de 7 pontos (ASG de 7 pontos) para identificar desnutrição. Também investigamos sensibilidade e especificidade do ponto de corte proposto anteriormente para parâmetros de BIVA.

          Métodos:

          Foram incluídos pacientes de ambos os sexos, acima de 20 anos, em HD. Foram avaliados parâmetros antropométricos, dados laboratoriais e análise de impedância bioelétrica (BIA). Valores de resistência (R) e reatância (Xc) obtidos por BIA de mono-frequência foram normalizados para altura corporal (H) gerando um gráfico do vetor de bioimpedância com a ajuda do software BIVA. Foi realizada uma análise da área sob a curva ROC (AUC).

          Resultados:

          Entre 104 pacientes incluídos, a idade média foi 51,70 (±15,10) anos, e 52% eram homens. BIVA demonstrou sensibilidade de 35% para diagnosticar desnutrição. A especificidade da BIVA para identificar pacientes bem nutridos foi 85,7%. A precisão diagnóstica entre BIVA e ASG de 7 pontos foi AUC=0,604; IC95%: 0,490-0,726, superior aos valores de corte estabelecidos anteriormente (AUC=0,514; IC95%: 0,369-0,631). Elipses de confiança de 95% não se sobrepuseram (p<0,05).

          Conclusão:

          Nosso estudo mostrou baixa precisão da BIVA para diagnóstico de desnutrição usando ASG-7 pontos como padrão de referência. Entretanto, é um método complementar para avaliar estado nutricional, pois fornece dados sobre celularidade e hidratação, aspectos importantes para a população em HD.

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          Most cited references42

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          • Abstract: found
          • Article: not found

          Measuring the accuracy of diagnostic systems.

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          Diagnostic systems of several kinds are used to distinguish between two classes of events, essentially "signals" and "noise". For them, analysis in terms of the "relative operating characteristic" of signal detection theory provides a precise and valid measure of diagnostic accuracy. It is the only measure available that is uninfluenced by decision biases and prior probabilities, and it places the performances of diverse systems on a common, easily interpreted scale. Representative values of this measure are reported here for systems in medical imaging, materials testing, weather forecasting, information retrieval, polygraph lie detection, and aptitude testing. Though the measure itself is sound, the values obtained from tests of diagnostic systems often require qualification because the test data on which they are based are of unsure quality. A common set of problems in testing is faced in all fields. How well these problems are handled, or can be handled in a given field, determines the degree of confidence that can be placed in a measured value of accuracy. Some fields fare much better than others.
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            Measuring the accuracy of diagnostic systems

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              A lack of agreement on definitions and terminology used for nutrition-related concepts and procedures limits the development of clinical nutrition practice and research.
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                Author and article information

                Journal
                J Bras Nefrol
                J Bras Nefrol
                jbn
                Jornal Brasileiro de Nefrologia
                Sociedade Brasileira de Nefrologia
                0101-2800
                2175-8239
                24 September 2021
                Apr-Jun 2022
                : 44
                : 2
                : 171-178
                Affiliations
                [1 ]Universidade Federal de Goiás, Faculdade de Nutrição, Programa de Pós-graduação Nutrição e Saúde, Goiânia, GO, Brasil.
                [2 ]Universidade Federal de Goiás, Faculdade de Nutrição, Goiânia, GO, Brasil.
                Author notes
                Correspondence to: Maria do Rosário Gondim Peixoto. E-mail: maria_rosario_gondim@ 123456ufg.br

                Authors’ Contribution

                MRGP conceptualization, methodology, formal analysis, writing, reviewing and editing of the manuscript; CSAS formal analysis and writing of the manuscript. NPQ and DMS investigation, formal analysis, writing of the manuscript and original draft preparation. ATVSF and NAC writing, reviewing and editing of the manuscript.

                Conflict of Interest

                The authors declare that they have no conflict of interest.

                Author information
                http://orcid.org/0000-0001-5786-027X
                http://orcid.org/0000-0002-8226-3175
                http://orcid.org/0000-0001-8412-1704
                http://orcid.org/0000-0002-6785-3433
                http://orcid.org/0000-0001-8159-1209
                http://orcid.org/0000-0003-1950-0817
                Article
                10.1590/2175-8239-JBN-2021-0099
                9269190
                34590669
                df768855-0a22-4d32-bd43-79194e6471f1

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 14 April 2021
                : 31 July 2021
                Categories
                Original Article

                renal insufficiency, chronic,malnutrition,nutritional assessment,renal dialysis,insuficiência renal crônica,desnutrição,avaliação nutricional,diálise renal

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