Sarcopenia em pessoas idosas: concordância entre métodos preditores

Sarcopenia is a relevant clinical condition worldwide. Its prevalence ranges from 5% to 13% in the elderly aged 65 years and over. Over 80 years, this value can reach 50%, demonstrating the influence of age on the development of the disease. Its diagnosis is based on reduced muscle mass, associated...

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Detalles Bibliográficos
Autores: Araújo, Sílvia Ribeiro Santos, Miranda, Rogério Mariano de, Silva, Bruno Rodrigues
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2024
País:Brasil
Institución:Universidade de São Paulo (USP)
Repositorio:Revista Brasileira de Educação Física e Esporte (Online)
Idioma:portugués
OAI Identifier:oai:revistas.usp.br:article/190873
Acceso en línea:https://www.revistas.usp.br/rbefe/article/view/190873
Access Level:acceso abierto
Palabra clave:Idoso
Sarcopenia
Força muscular
Testes funcionais
Elderly
Muscle strength
Functional tests
Descripción
Sumario:Sarcopenia is a relevant clinical condition worldwide. Its prevalence ranges from 5% to 13% in the elderly aged 65 years and over. Over 80 years, this value can reach 50%, demonstrating the influence of age on the development of the disease. Its diagnosis is based on reduced muscle mass, associated with decreased strength and/or low muscle function. The gold standard for diagnosing the disease is Dual-energy X-ray absorptiometry, but it is inaccessible due to its high cost and diagnostic complexity. Thus, alternative methods for screening for sarcopenia, such as: sit and stand test (TSL), calf circumference (CP) and manual strength test (FPM), SARC-F questionnaire are applied. Defining methods suitable for the outpatient setting is essential for both screening and diagnosis of the disease. The present study aimed to analyze whether there is agreement between predictive methods used to estimate the existence of sarcopenia in the elderly. This is a cross-sectional study carried out with 27 healthy elderly people (23 women and 4 men). The predictive methods were measuring CP, FPM, TSL and Ishii Probability Score (ISHII). The agreement between the classifications was used the Kappa statistic. All predictive methods identified sarcopenic and non-sarcopenic individuals. There was no agreement in the combinations: CTS x FPM; TSL x FPM and; TSL x ISHII. As for the association between the CTS and TSL methods, there was a moderate agreement between the predicted values  (k=0.43; p=0.006). Conclusion: Different predictive methods promote different sarcopenia diagnoses. A moderate agreement was observed for the combination between CTS and TSL predictors. It should be noted that the association between different tests is an option to be evaluated.