肌萎缩
医学
接收机工作特性
超声波
力学指标
股直肌
体质指数
骨骼肌
贝叶斯多元线性回归
曲线下面积
线性回归
肌肉团
心脏病学
核医学
内科学
物理医学与康复
放射科
统计
肌电图
微气泡
数学
作者
Yen‐Lung Chen,Peng‐Ta Liu,Huihua Kenny Chiang,Si‐Huei Lee,Yen‐Li Lo,Yueh‐Cheng Yang,Hong‐Jen Chiou
摘要
Sarcopenia patients require more medical attention and caretaking. As such, early detection of sarcopenia and appropriate interventions are crucial for decreasing medical costs and meeting the challenges of aging populations. The aim of the present study was to develop a reliable and accurate model to estimate muscle mass using ultrasound-derived parameters from the rectus femoris (RF), referenced by dual-energy X-ray absorptiometry.Cross-sectional study was performed. The study patients were recruited by Taipei Veterans General Hospital (No. 2016-07-013C) between 2016 and 2019. A total of 91 community-dwelling adults (35 men and 56 women) were enrolled in this study. Ultrasound measurements of RF muscle thickness (MT), cross-sectional area (CSA), and muscle volume (MV) were performed in B-mode. Muscle strength and physical performance were also examined. Multivariate linear regression was used to build models for the prediction of appendicular skeletal muscle index (ASMI) based on MT, CSA, and MV values. The accuracy of ultrasound RF measurements for predicting sarcopenia was evaluated by using receiver operating characteristic (ROC) curve analysis.The regression equations used for ASMI prediction (adjusted body mass index, sex, and leg length) had high precision and low error. Moreover, the MV model results were close to those of the CSA model and higher than those of the MT model. The ROC analysis showed that both MV and CSA had excellent discrimination when assessing sarcopenia (AUC = 0.83 and 0.81, respectively), whereas MT showed acceptable discrimination (AUC = 0.73).Ultrasound-derived RF MV was accurate when predicting ASMI and diagnosing sarcopenia in community-dwelling adults.
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