Aged and Extended Care Services, The Queen Elizabeth Hospital, Central Adelaide Local Health Network, South Australia, Australia; Adelaide Geriatrics Training and Research with Aged Care (G-TRAC) Centre, School of Medicine, Faculty of Health Science, University of Adelaide, Adelaide, South Australia, Australia; School of Medicine, Faculty of Health Science, University of Adelaide, Adelaide, South Australia, Australia.
School of Medicine, Faculty of Health Science, University of Adelaide, Adelaide, South Australia, Australia.
J Am Med Dir Assoc. 2015 Jan;16(1):25-30. doi: 10.1016/j.jamda.2014.06.018. Epub 2014 Sep 18.
Sarcopenia is the presence of low muscle mass and poor physical function. We have developed an anthropometric prediction equation (PE). We compared the accuracy of our previously developed anthropometric prediction equation (PE) to dual absorptiometry x-ray (DXA) in predicting low muscle mass and sarcopenia.
Cross-sectional study design.
Community dwelling.
Men and women aged 65 years and older.
Gender-specific low muscle mass cutoffs were identified using the lowest 20% of the skeletal muscle index (SMI) where muscle mass was determined using PE in 611 men and 375 women aged 65 years and older. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of PE derived low muscle mass were compared with DXA-derived low muscle mass. The cohort was randomized into a development and validation group to identify various cutoffs for low muscle mass via the PE method and test its performance against the DXA method.
The PE cutoff for low muscle mass was less than 8.05 kg/m(2) in men and less than 5.35 kg/m(2) in women. On validation of various cutoffs with improving sensitivity values from 70% to 97%, specificity increased from 45.5% to 85.7%, PPV increased from 31.3% to 56.9%, and NPV increased from 93.0% to 98.6% in men. In women, specificity improved from 42% to 72%, PPV reduced from 56.9% to 31.3%, and NPV improved from 93.0% to 98.6%. When the PE method was combined with a measure of muscle performance, a similar pattern of performance was observed.
The PE when combined with a measure of muscle function to create a screening tool performs as a "rule-out" test with high sensitivity values and NPVs.
肌少症是指肌肉量低和身体机能差。我们开发了一种人体测量预测方程（PE）。我们比较了我们之前开发的人体测量预测方程（PE）和双能 X 射线吸收法（DXA）在预测低肌肉量和肌少症方面的准确性。
横断面研究设计。
社区居住。
年龄在 65 岁及以上的男性和女性。
使用最低 20%的骨骼肌指数（SMI）确定性别特异性低肌肉量截断值，其中肌肉量使用 611 名男性和 375 名年龄在 65 岁及以上的女性的 PE 确定。PE 衍生的低肌肉量的灵敏度、特异性、阳性预测值（PPV）和阴性预测值（NPV）与 DXA 衍生的低肌肉量进行比较。该队列被随机分为开发和验证组，以通过 PE 方法确定低肌肉量的各种截断值，并测试其与 DXA 方法的性能。
男性的 PE 低肌肉量截断值小于 8.05kg/m²，女性的截断值小于 5.35kg/m²。在验证各种截断值时，灵敏度从 70%提高到 97%，特异性从 45.5%提高到 85.7%，PPV 从 31.3%提高到 56.9%，NPV 从 93.0%提高到 98.6%。在女性中，特异性从 42%提高到 72%，PPV 从 56.9%降低到 31.3%，NPV 从 93.0%提高到 98.6%。当 PE 方法与肌肉功能测量结合使用时，观察到类似的性能模式。
PE 与肌肉功能测量相结合作为一种筛查工具，具有高灵敏度值和 NPV，表现为一种“排除”测试。
