Lourenço Roberto Alves, Pérez-Zepeda Mario, Gutiérrez-Robledo Luis, García-García Francisco J, Rodríguez Mañas Leocadio
Internal Medicine Department, Faculty of Medical Sciences, Rio de Janeiro State University, Rio de Janeiro, Brazil.
Geriatric Epidemiologic Research, Instituto Nacional de Geriatría, Periferico Sur 2767, Colonia San Jeronimo Lidice, Delegacion Magdalena Contreras, Mexico, Distrito Federal 10200, Mexico.
Age Ageing. 2015 Mar;44(2):334-8. doi: 10.1093/ageing/afu192. Epub 2014 Dec 23.
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).
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.
A cross-sectional study.
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.
Three thousand two hundred and sixty community-dwelling individuals, 65 years and older.
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.
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).
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.
关于肌肉减少症的诊断尚无共识。老年肌肉减少症欧洲工作组(EWGSOP)提出了一种筛查和诊断算法。
评估EWGSOP算法在确定疑似肌肉减少症并被选进行后续肌肉量(MM)测量的受试者比例方面的性能。
一项横断面研究。
队列研究包括巴西里约热内卢的巴西老年人衰弱研究(FIBRA-RJ);墨西哥城的科约阿坎队列(CC);以及西班牙托莱多的健康老龄化托莱多研究(TSHA)。
3260名65岁及以上的社区居住个体。
最初,使用EWGSOP算法最初提出的步态速度和握力临界值;第二步,使用针对特定队列量身定制的值。
使用最初建议的EWGSOP临界值,总队列中的83.4%(TSHA中为94.4%,FIBRA-RJ中为75.5%,CC中为67.8%)会被视为疑似肌肉减少症。调整后的临界值将异常结果的比例降至34.2%(基于五分位数法)和23.71%(z分数法)。
EWGSOP提出的算法在筛查老年人肌肉减少症方面临床效用有限,因为被选进一步进行MM评估的受试者比例很高。根据所研究人群的特定特征调整临界值可减少被选进行MM评估的人数,可能会提高该算法的性能。需要进一步开展包括MM客观测量的研究来确定这些特定临界值的准确性。