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Identifying Sarcopenia in Acute Care Setting Patients

机译:识别急性护理环境患者的肌肉减少症

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摘要

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 ± 6.9 years and body mass index 26.3 ± 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= 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.
机译:目的:通过在急诊老年病科中应用欧洲老年人肌肉减少症工作组(EWGSOP)流程图来评估肌肉减少症的患病率,并结合手握和步态速度测试来测试EWGS​​OP诊断算法的修改版本,以识别肌肉质量低的受试者。设计:观察性队列研究。地点:学术医学科的老年病科。参加者:119名急性病患者(女性34.4%),平均年龄80.4±6.9岁,体重指数26.3±4.9 kg / m2。测量:通过生物阻抗分析评估肌肉质量,通过手持测功机评估肌肉力量,并通过4米步行测试步态速度。结果:使用EWGSOP分类进行肌肉减少症,有5.0%的肌肉减少症和21.0%的严重肌肉减少症。结合步态速度测试和握力测量,在检测低肌肉质量的受试者中观察到了最高的预测能力(敏感性和特异性分别为80.6%和62.5%)。表现出正常步态速度和握力的受试者表现出通过生物阻抗分析评估的肌肉质量的正常值。通过使用ROC方法,当将两个测试合并时,AUC在统计学上高于分别使用每个测试时的AUC(0.740; P = 018)。结论:我们的研究表明,入院急诊科的4名患者中有1名被确认为肌肉减少症。当使用结合步态速度和握力获得的EWGSOP流程图的改进版本时,提高了识别低肌肉质量受试者的算法的灵敏度和特异性。

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