Roberto Alves Lourenço1, Mario Pérez-Zepeda2, Luis Gutiérrez-Robledo3, Francisco J García-García4, Leocadio Rodríguez Mañas5. 1. Internal Medicine Department, Faculty of Medical Sciences, Rio de Janeiro State University, Rio de Janeiro, Brazil. 2. Geriatric Epidemiologic Research, Instituto Nacional de Geriatría, Periferico Sur 2767, Colonia San Jeronimo Lidice, Delegacion Magdalena Contreras, Mexico, Distrito Federal 10200, Mexico. 3. General Direction, National Institute of Geriatrics, México, Distrito Federal, Mexico. 4. Servicio de Geriatría, Complejo Hospitalario de Toledo, Toledo, Spain. 5. Servicio de Geriatría, Hospital Universitario de Getafe, Getafe, Spain.
Abstract
BACKGROUND: There is a lack of consensus on the diagnosis of sarcopenia. A screening and diagnostic algorithm was proposed by the European Working Group on Sarcopenia in Older People (EWGSOP). OBJECTIVE: To assess the performance of the EWGSOP algorithm in determining the proportion of subjects suspected of having sarcopenia and selected to undergo subsequent muscle mass (MM) measurement. DESIGN: A cross-sectional study. SETTING: The cohorts, Frailty in Brazilian Older People Study-Rio de Janeiro (FIBRA-RJ), Brazil; Coyoacan Cohort (CC), Mexico City, Mexico; and Toledo Study for Healthy Aging (TSHA), Toledo, Spain. SUBJECTS: Three thousand two hundred and sixty community-dwelling individuals, 65 years and older. METHODS: Initially, the EWGSOP algorithm was applied using its originally proposed cut-off values for gait speed and handgrip strength; in the second step, values tailored for the specific cohorts were used. RESULTS: Using the originally suggested EWGSOP cut-off points, 83.4% of the total cohort (94.4% in TSHA, 75.5% in FIBRA-RJ, 67.8% in CC) would have been considered as suspected of sarcopenia. Adapted cut-off values lowered the proportion of abnormal results to 34.2% (quintile-based approach) and 23.71% (z-score approach). CONCLUSIONS: The algorithm proposed by the EWGSOP is of limited clinical utility in screening older adults for sarcopenia due to the high proportion of subjects selected to further undergo MM assessment. Tailoring cut-off values to specific characteristics of the population being studied reduces the number of people selected for MM assessment, probably improving the performance of the algorithm. Further research including the objective measure of MM is needed to determine the accuracy of these specific cut-off points.
BACKGROUND: There is a lack of consensus on the diagnosis of sarcopenia. A screening and diagnostic algorithm was proposed by the European Working Group on Sarcopenia in Older People (EWGSOP). OBJECTIVE: To assess the performance of the EWGSOP algorithm in determining the proportion of subjects suspected of having sarcopenia and selected to undergo subsequent muscle mass (MM) measurement. DESIGN: A cross-sectional study. SETTING: The cohorts, Frailty in Brazilian Older People Study-Rio de Janeiro (FIBRA-RJ), Brazil; Coyoacan Cohort (CC), Mexico City, Mexico; and Toledo Study for Healthy Aging (TSHA), Toledo, Spain. SUBJECTS: Three thousand two hundred and sixty community-dwelling individuals, 65 years and older. METHODS: Initially, the EWGSOP algorithm was applied using its originally proposed cut-off values for gait speed and handgrip strength; in the second step, values tailored for the specific cohorts were used. RESULTS: Using the originally suggested EWGSOP cut-off points, 83.4% of the total cohort (94.4% in TSHA, 75.5% in FIBRA-RJ, 67.8% in CC) would have been considered as suspected of sarcopenia. Adapted cut-off values lowered the proportion of abnormal results to 34.2% (quintile-based approach) and 23.71% (z-score approach). CONCLUSIONS: The algorithm proposed by the EWGSOP is of limited clinical utility in screening older adults for sarcopenia due to the high proportion of subjects selected to further undergo MM assessment. Tailoring cut-off values to specific characteristics of the population being studied reduces the number of people selected for MM assessment, probably improving the performance of the algorithm. Further research including the objective measure of MM is needed to determine the accuracy of these specific cut-off points.
Authors: E Dent; J E Morley; A J Cruz-Jentoft; H Arai; S B Kritchevsky; J Guralnik; J M Bauer; M Pahor; B C Clark; M Cesari; J Ruiz; C C Sieber; M Aubertin-Leheudre; D L Waters; R Visvanathan; F Landi; D T Villareal; R Fielding; C W Won; O Theou; F C Martin; B Dong; J Woo; L Flicker; L Ferrucci; R A Merchant; L Cao; T Cederholm; S M L Ribeiro; L Rodríguez-Mañas; S D Anker; J Lundy; L M Gutiérrez Robledo; I Bautmans; I Aprahamian; J M G A Schols; M Izquierdo; B Vellas Journal: J Nutr Health Aging Date: 2018 Impact factor: 4.075
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Authors: Tatiana Bering; Kiara G D Diniz; Marta Paula P Coelho; Diego A Vieira; Maria Marta S Soares; Adriana M Kakehasi; Maria Isabel T D Correia; Rosângela Teixeira; Dulciene M M Queiroz; Gifone A Rocha; Luciana D Silva Journal: J Cachexia Sarcopenia Muscle Date: 2018-01-19 Impact factor: 12.910