利用步态运动学能否预测老年人跌倒？
Is it possible to predict falls in older adults using gait kinematics?
作者信息
Marques Nise Ribeiro, Spinoso Deborah Hebling, Cardoso Bruna Carvalho, Moreno Vinicius Christianini, Kuroda Marina Hiromi, Navega Marcelo Tavella
机构信息
Center of Health Sciences, Universidade do Sagrado Coração, USC, Bauru, Brazil.
Department of Physical Therapy and Occupation Therapy, Universidade Estadual Paulista, UNESP, Marilia, Brazil.
出版信息
Clin Biomech (Bristol). 2018 Nov;59:15-18. doi: 10.1016/j.clinbiomech.2018.08.006. Epub 2018 Aug 11.
BACKGROUND
Gait kinematic parameters have been reported as an important clinical tool to assess the risk of falls in older adults. However, the ability of these parameters to predict falls in the older population is still unclear.
OBJECTIVE
To identify the ability that gait kinematic parameters present to predict fall in older adults.
METHODS
Data from 102 older adults, who live in a community setting, were considered for this study. For data collection, older subjects had to walk on a 14 meter-walkway in their preferred gait speed. The incidence of falls was recorded at baseline together with gait kinematics and then every three months during the period of the study. The ability of gait kinematic parameters to predict falls was tested using the ROC curve.
RESULTS
Stance time variability, swing time, and stride length presented a sensitivity to predict falls in older adults higher than 70%.
CONCLUSION
Gait kinematic parameters, such as stance variability, swing time, and stride length may predict future falls in older adults.
背景
步态运动学参数已被报道为评估老年人跌倒风险的重要临床工具。然而，这些参数预测老年人群跌倒的能力仍不明确。
目的
确定步态运动学参数预测老年人跌倒的能力。
方法
本研究纳入了102名居住在社区的老年人的数据。在数据收集过程中，老年受试者必须以其偏好的步态速度在14米长的通道上行走。在基线时记录跌倒发生率以及步态运动学数据，然后在研究期间每三个月记录一次。使用ROC曲线测试步态运动学参数预测跌倒的能力。
结果
站立时间变异性、摆动时间和步长对预测老年人跌倒的敏感性高于70%。
结论
步态运动学参数，如站立变异性、摆动时间和步长，可能预测老年人未来的跌倒情况。
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