Identifying Sarcopenia in Acute Care Setting Patients

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• 作者：Andrea P. Rossi ; MD ; PhD^a ; ^{mauro.zamboni@univr.it" class="auth_mail} ; ^{andrea.rossi@hotmail.it" class="auth_mail} ; Francesco Fantin ; MD ; PhD^a ; Rocco Micciolo ; MD^b ; Monica Bertocchi ; MD^a ; Paolo Bertassello ; MD^a ; Valeria Zanandrea ; MD^a ; Alessandra Zivelonghi ; MD^a ; Luisa Bissoli ; MD^a ; Mauro Zamboni ; MD^a ; ^{mauro.zamboni@univr.it" class="auth_mail} ; ^{andrea.rossi@hotmail.it" class="auth_mail}
• 关键词：Sarcopenia ; walking speed ; muscle strength
• 刊名：Journal of the American Medical Directors Association
• 出版年：April, 2014
• 年：2014
• 卷：15
• 期：4
• 页码：303.e7-303.e12
• 全文大小：625 K

文摘

Objectives

To evaluate the prevalence of sarcopenia by applying European Working Group on Sarcopenia in Older People (EWGSOP) flow chart in an acute care geriatric unit as well as to test a modified version of the EWGSOP diagnostic algorithm combining handgrip and gait speed test to identify subjects with low muscle mass.

Design

Observational cohort study.

Setting

Geriatric unit in an academic medical department.

Participants

One hundred nineteen acutely ill persons (34.4% female), with mean age 80.4 卤 6.9 years and body mass index 26.3 卤 4.9 kg/m².

Measurements

Assessment of muscle mass by bioimpedence analysis, muscle strength by handheld dynamometer, and gait speed with the 4-meter walking test.

Results

Using the EWGSOP classification for sarcopenia, 5.0% presented with sarcopenia and 21.0% with severe sarcopenia. Combining gait speed test and handgrip strength measurement, the highest predictive power in detecting subjects with low muscle mass was observed (sensitivity and specificity, 80.6% and 62.5%, respectively). Subjects presenting with both normal gait speed and handgrip showed normal values of muscle mass as assessed with bioimpedence analysis. By using the ROC method, when the 2 tests were combined, the AUC was statistically higher than when using each test separately (0.740; P聽= .018).

Conclusions

Our study shows that 1 of 4 patients admitted to the acute care department were recognized to be sarcopenic. When a modifived version of the EWGSOP flow chart, obtained combining both gait speed and handgrip was used, sensitivity and specificity of algorithm to identify subjects with low muscle mass was improved.