Resumen de Concordância do diagnóstico de sarcopenia por diferentes propostas de avaliação, por BIA e DEXA

João Valentini Neto, Sandra Maria Lima Ribeiro

• português

  Introdução e Objetivo: A sarcopenia é considerada um dos maiores problemas clínicos entre os idosos, o que torna o seu diagnóstico muito importante. Embora existam várias proposições para o diagnóstico da sarcopenia, ainda não há um consenso sobre qual o melhor método. Buscando identificar a concordância entre distintas formas de avaliações de massa muscular para diagnóstico de sarcopenia baseadas em dados de bioimpedância elétrica (BIA) e raio-x de dupla energia (DEXA), Métodos: trata-se de um estudo piloto, realizado com uma amostra de conveniência formada por idosos, em risco de fragilidade. A composição corporal foi avaliada de duas formas: bioimpedância elétrica e DEXA. Os participantes tiveram a massa muscular classificada como baixa de acordo com a classificação proposta por 11 autores diferentes. Essas classificações foram analisadas quanto à concordância (índice de kappa) em três etapas: comparando as classificações segundo os dados de BIA; comparando as classificações a partir dos resultados de DEXA; comparando as classificações dos dados de BIA e de DEXA. Resultados: Foram encontradas forças de concordâncias significativas de fraca (k=0,192, p<0,001) a quase perfeita (k=0,892, p<0,001) entre as classificações por BIA; quase perfeitas para quase todos os resultados das classificações por DEXA (k>0,900, p<0,001); e razoáveis (k=0,331, p<0,001) a substanciais (k=0,668, p<0,001) em relação aos resultados das classificações por DEXA e BIA. Conclusão: Observou-se que diferentes métodos para a avaliação da massa muscular aqui adotadas apresentaram graus significativos de concordância em sua maioria, sendo os maiores encontrados dentre os que se baseiam em dados de DEXA. ABSTRACTAgreement of the sarcopenia disgnosis from different evaluation propositions by BIA and DEXA analysisBackground: Sarcopenia is considered one of the main clinic problems in elderly, which makes the diagnostic very important. Although there are different forms for sarcopenia diagnostic, there is no consensus about the best method. Aim: to identify the agreement between different forms of evaluating muscle mass for sarcopenia diagnostic, based on data from electric bioimpedance (BIA) and dual energy x-ray absorptiometry (DXA). Methods: a cross-sectional study, was performed with a convenience sample composed by elderly individuals under frailty risk. Body composition was evaluated from bioelectrical impedance and from DXA. Participants presented low muscle mass identified according to the classifications proposals postulated by 12different authors. These classifications were investigated for their concordance (kappa index) in three steps: comparing the values obtained by BIA; comparing the results based on DXA data; and comparing the data from BIA and DEXA. Results: Strength of agreement was found from poor (k=0,192, p<0,001) to almost perfect (k=0,892, p<0,001), between BIA classifications; almost perfect (k>0,900, p<0,001) between most results from DXA classification; fair (k=0,331, p<0,001) to substantial (k=0,668, p<0,001) degrees of agreement were found between DXA and BIA classifications. Conclusion: It was possible to note that the different methods taken here to evaluate sarcopenia agreed in general, but the better agreement degrees were found between the ones based on DXA data.

• English

  Background: Sarcopenia is considered one of the main clinic problems in elderly, which makes the diagnostic very important. Although there are different forms for sarcopenia diagnostic, there is no consensus about the best method. Aim: to identify the agreement between different forms of evaluating muscle mass for sarcopenia diagnostic, based on data from electric bioimpedance (BIA) and dual energy x-ray absorptiometry (DXA). Methods: a cross-sectional study, was performed with a convenience sample composed by elderly individuals under frailty risk. Body composition was evaluated from bioelectrical impedance and from DXA. Participants presented low muscle mass identified according to the classifications proposals postulated by 12different authors. These classifications were investigated for their concordance (kappa index) in three steps: comparing the values obtained by BIA; comparing the results based on DXA data; and comparing the data from BIA and DEXA. Results: Strength of agreement was found from poor (k=0,192, p<0,001) to almost perfect (k=0,892, p<0,001), between BIA classifications; almost perfect (k>0,900, p<0,001) between most results from DXA classification; fair (k=0,331, p<0,001) to substantial (k=0,668, p<0,001) degrees of agreement were found between DXA and BIA classifications. Conclusion: It was possible to note that the different methods taken here to evaluate sarcopenia agreed in general, but the better agreement degrees were found between the ones based on DXA data.