Slip-Fall Predictors in Community-Dwelling, Ambulatory Stroke Survivors: A Cross-sectional Study.
Slip-Fall Predictors in Community-Dwelling, Ambulatory Stroke Survivors: A Cross-sectional Study.
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DOI：
10.1097/npt.0000000000000331
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发表时间：
2020-10
期刊：
影响因子：
--
通讯作者：
Bhatt T
中科院分区：
文献类型：
--
作者：
Gangwani R;Dusane S;Wang S;Kannan L;Wang E;Fung J;Bhatt T
考虑到慢性卒中（PwCS）患者福尔斯的多因素性质和通常严重的后果，确定最佳预测跌倒风险的测量方法对于识别高危人群至关重要。我们的目的是确定国际功能、残疾和健康分类（ICF）领域的措施，这些措施可以预测PWCS中实验室诱发的滑倒相关跌倒风险。五十六PwCS参加了实验中，他们受到了一个突然滑倒的麻痹腿，而走在地上人行道。在滑倒之前，他们接受了一系列测试，以评估跌倒的风险因素。使用基于性能的测试和仪器测量来评估平衡。评估的其他跌倒风险因素包括感觉运动障碍的严重程度、肌肉力量、体力活动水平和心理社会因素。对所有变量进行Logistic回归分析。根据跌倒风险预测的敏感性和特异性，检查每种测量方法的准确性。在56名参与者中，24名（43%）在滑倒时摔倒，32名（57%）恢复平衡。多变量逻辑回归分析模型确定动态步态稳定性、髋关节伸肌力量和计时起身和行走（TUG）评分是实验室诱导的滑倒的重要预测因素，其综合敏感性为75%，特异性为79.2%，总体准确性为77.3%。结果表明，ICF领域内的跌倒风险指标--身体、结构和功能（动态步态稳定性和髋伸肌力量）和活动限制（TUG）--可以在PwCS中提供灵敏的实验室诱导滑倒预测模型。
Considering the multifactorial nature and the often-grave consequences of falls in people with chronic stroke (PwCS), determining measurements that best predict fall risk is essential for identifying those who are at high risk. We aimed to determine measures from the domains of the International Classification of Functioning, Disability and Health (ICF) that can predict laboratory-induced slip-related fall risk among PwCS. Fifty-six PwCS participated in the experiment in which they were subjected to an unannounced slip of the paretic leg while walking on an overground walkway. Prior to the slip, they were given a battery of tests to assess fall risk factors. Balance was assessed using performance-based tests and instrumented measures. Other fall risk factors assessed were severity of sensorimotor impairment, muscle strength, physical activity level, and psychosocial factors. Logistic regression analysis was performed for all variables. The accuracy of each measure was examined based on its sensitivity and specificity for fall risk prediction. Of the 56 participants, 24 (43%) fell upon slipping while 32 (57%) recovered their balance. The multivariate logistic regression analysis model identified dynamic gait stability, hip extensor strength, and the Timed Up and Go (TUG) score as significant laboratory-induced slip-fall predictors with a combined sensitivity of 75%, a specificity of 79.2%, and an overall accuracy of 77.3%. The results indicate that fall risk measures within the ICF domains—body, structure, and function (dynamic gait stability and hip extensor strength) and activity limitation (TUG)—could provide a sensitive laboratory-induced slip-fall prediction model in PwCS.