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- W3043594911 abstract "Introduction: the estimation of appendicular lean soft tissue by DXA (ALSTDXA) is one of the criteria for the diagnosis of sarcopenia. However, this method is expensive and not readily avaiable in clinical practice. Anthropometric equations are low-cost and able to accurate predict ALST, but such equations have not been validated for male Brazilian older adults between the ages of 60 to 79 years. To this end, this study sought to validate the existing predictive anthropometric equations for ALST, and to verify its accuracy for the diagnosis of sarcopenia in male Brazilian older adults. Methods: this cross-sectional study recruited and enrolled 25 male older adults (69.3 ± 5.60 years). ALSTDXA and anthropometric measures were determined. ALST estimations with 13 equations were compared to ALSTDXA. The validity of the equations was established when: p > 0.05 (paired t-test); standard error of the estimate (SEE) < 3.5 kg; and coefficient of determination r² > 0.70. Results: two Indian equations met the criteria (Kulkarini 1: 22.19 ± 3.41 kg; p = 0.134; r² = 0.78; EPE = 1.3 kg. Kulkarini 3: 22.14 ± 3.52 kg; p = 0.135; r² = 0.82; SEE = 1.2 kg). However, these equations presented an average bias (Bland-Altman: 0.54 and 0.48 kg) and 'false negative' classification for the ALST index. Thus, three explanatory equations were developed. The most accurate equation demonstrated a high level of agreement (r2adj = 0.87) and validity (r²PRESS = 0.83), a low predictive error (SEEPRESS = 1.53 kg), and an adequate ALST classification. Conclusion: anthropometric models for predicting ALST are valid alternatives for the diagnosis and monitoring of sarcopenia in older adults; however, population specificity affects predictive validity, with risks of false positive/negative misclassification.Introducción: uno de los criterios utilizados para el diagnóstico de la sarcopenia es la determinación de tejido blando magro apendicular por DXA (TBMADXA), método costoso que no siempre está disponible en la práctica clínica. Las ecuaciones antropométricas suponen un bajo coste y predicen bien el TBMA, pero con una validez desconocida para los varones brasileños de 60 a 79 años. Por lo tanto, nuestro objetivo fue validar las ecuaciones antropométricas existentes predictivas del TBMA y verificar su precisión para el diagnóstico de sarcopenia en varones brasileños de edad avanzada. Métodos: participaron en este estudio transversal 25 hombres de edad avanzada (69,3 ± 5,60 años). Se determinaron el TBMADXA y las medidas antropométricas. Las ecuaciones predictivas del TBMA se compararon con el TBMADXA. La validez de las ecuaciones en las comparaciones se confirmó cuando: p > 0,05 (prueba de la “t” pareada); error estándar estimado (EEE) < 3,5 kg; coeficiente de determinación r² > 0,70. Resultados: dos ecuaciones indias cumplieron los criterios (Kulkarini 1: 22,19 ± 3,41 kg; p = 0,134; r² = 0,78; EEE = 1,3 kg. Kulkarini 3: 22,14 ± 3,52 kg; p = 0,135; r² = 0,82; EEE = 1,2 kg). Sin embargo, presentaron sesgo promedio (Bland-Altman: 0,54 y 0,48 kg) y clasificación de 'falso negativo' para el índice de TBMA. Por lo tanto, se crearon tres ecuaciones explicativas. La ecuación más precisa mostró un alto acuerdo (r2adj = 0,87), uma alta validez (r²PRESS = 0,83), um bajo error predictivo (EEEPRESS = 1,53 kg) y uma clasificación del TBMA adecuada. Conclusión: los modelos antropométricos para predecir el TBMA son alternativas válidas para el diagnóstico y el seguimiento de la sarcopenia en los ancianos. Pero la especificidad de la población afecta a su validez predictiva, con riesgos de incorrección por clasificación falsa positiva/negativa." @default.
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- W3043594911 date "2020-01-01" @default.
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- W3043594911 title "Population specificity affects prediction of appendicular lean tissues for diagnosed sarcopenia: a cross-sectional study" @default.
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