4.5 Article

Estimation of sarcopenia prevalence using various assessment tools

期刊

EXPERIMENTAL GERONTOLOGY
卷 61, 期 -, 页码 31-37

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.exger.2014.11.014

关键词

Sarcopenia; Muscle mass; Prevalence; Diagnostic

资金

  1. FNRS (Fonds National de la Recherche Scientifique de Belgique - FRS-FNRS)

向作者/读者索取更多资源

Background: Sarcopenia is defined as a progressive and generalized loss of muscle mass with either a loss of muscle strength or a loss of physical performance but there is no recommendation regarding the diagnostic tools that have to be used. In this study, we compared the prevalence of sarcopenia assessed using different diagnostic tools. Methods: To measure muscle mass, muscle strength and physical performance, we used for each outcome two different diagnostic tools. For muscle mass, we used Dual Energy X-Ray Absorptiometry (DXA) and bioelectrical impedance analysis (BIA); for muscle strength, we used a hydraulic dynamometer and a pneumatic dynamometer; for physical performance we used the Short Physical Performance Battery test (SPPB test) and the walk speed. Eight diagnostic groups were hereby established. Results: A total of 250 consecutive subjects were recruited in an outpatient clinic in Liege, Belgium. Estimated prevalence of sarcopenia varied from 8.4% to 27.6% depending on the method of diagnosis used. Regarding muscle mass, BIA systematically overestimated muscle mass compared to DXA (mean estimated prevalence with BIA = 12.8%; mean prevalence with DXA = 21%). For muscle strength, the pneumatic dynamometer diagnosed twice more sarcopenic subjects than the hydraulic dynamometer (mean estimated prevalence with PD = 22.4%; mean estimated prevalence with HD = 11.4%). Finally, no difference in prevalence was observed when the walking speed or the SPPB test was used. A weak overall kappa coefficient was observed (0.53), suggesting that the 8 methods of diagnosis are moderately concordant. Conclusion: Within the same definition of sarcopenia, prevalence of sarcopenia is highly dependent on the diagnostic tools used. (C) 2014 Elsevier Inc. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.5
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据