Sample Renee Beach, Kinney Allison L, Jackson Kurt, Diestelkamp Wiebke, Bigelow Kimberly Edginton
Department of Mechanical and Aerospace Engineering, University of Dayton, 300 College Park, Kettering Labs Room 363F, Dayton, OH, 45469-0238, USA.
Department of Physical Therapy, University of Dayton,300 College Park, Fitz Hall 207, Dayton, OH, 45469-2925, USA.
Gait Posture. 2017 Sep;57:168-171. doi: 10.1016/j.gaitpost.2017.06.007. Epub 2017 Jun 10.
The Timed Up and Go (TUG) has been commonly used for fall risk assessment. The instrumented Timed Up and Go (iTUG) adds wearable sensors to capture sub-movements and may be more sensitive. Posturography assessments have also been used for determining fall risk. This study used stepwise logistic regression models to identify key outcome measures for the iTUG and posturography protocols. The effectiveness of the models containing these measures in differentiating fallers from non-fallers were then compared for each: iTUG total time duration only, iTUG, posturography, and combined iTUG and posturography assessments. One hundred and fifty older adults participated in this study. The iTUG measures were calculated utilizing APDM Inc.'s Mobility Lab software. Traditional and non-linear posturography measures were calculated from center of pressure during quiet-standing. The key outcome measures incorporated in the iTUG assessment model (sit-to-stand lean angle and height) resulted in a model sensitivity of 48.1% and max re-scaled R value of 0.19. This was a higher sensitivity, indicating better differentiation, compared to the model only including total time duration (outcome of the traditional TUG), which had a sensitivity of 18.2%. When the key outcome measures of the iTUG and the posturography assessments were combined into a single model, the sensitivity was approximately the same as the iTUG model alone. Overall the findings of this study support that the iTUG demonstrates greater sensitivity than the total time duration, but that carrying out both iTUG and posturography does not greatly improve sensitivity when used as a fall risk screening tool.
定时起立行走测试（TUG）已被广泛用于跌倒风险评估。仪器辅助定时起立行走测试（iTUG）增加了可穿戴传感器以捕捉子动作，可能更具敏感性。姿势图评估也已用于确定跌倒风险。本研究使用逐步逻辑回归模型来识别iTUG和姿势图测试方案的关键结果指标。然后比较包含这些指标的模型在区分跌倒者和非跌倒者方面的有效性，分别为：仅iTUG总时长、iTUG、姿势图以及iTUG和姿势图联合评估。150名老年人参与了本研究。iTUG指标利用APDM公司的移动实验室软件进行计算。传统和非线性姿势图指标根据安静站立时的压力中心进行计算。iTUG评估模型中纳入的关键结果指标（从坐起到站立的倾斜角度和高度）导致模型敏感性为48.1%，最大重新缩放R值为0.19。与仅包括总时长（传统TUG的结果）的模型相比，这是更高的敏感性，表明区分能力更好，后者的敏感性为18.2%。当将iTUG和姿势图评估的关键结果指标合并到一个单一模型中时，敏感性与单独的iTUG模型大致相同。总体而言，本研究结果支持iTUG比总时长表现出更高的敏感性，但当用作跌倒风险筛查工具时，同时进行iTUG和姿势图评估并不能显著提高敏感性。
