Cameron Michelle H, Thielman Emily, Mazumder Rajarshi, Bourdette Dennis
Department of Neurology, Oregon Health & Science University and Portland VA Medical Center, Portland, OR 97219, USA.
Mult Scler Int. 2013;2013:496325. doi: 10.1155/2013/496325. Epub 2013 Sep 26.
Background. Many people with MS fall, but the best method for identifying those at increased fall risk is not known. Objective. To compare how accurately fall history, questionnaires, and physical tests predict future falls and injurious falls in people with MS. Methods. 52 people with MS were asked if they had fallen in the past 2 months and the past year. Subjects were also assessed with the Activities-specific Balance Confidence, Falls Efficacy Scale-International, and Multiple Sclerosis Walking Scale-12 questionnaires, the Expanded Disability Status Scale, Timed 25-Foot Walk, and computerized dynamic posturography and recorded their falls daily for the following 6 months with calendars. The ability of baseline assessments to predict future falls was compared using receiver operator curves and logistic regression. Results. All tests individually provided similar fall prediction (area under the curve (AUC) 0.60-0.75). A fall in the past year was the best predictor of falls (AUC 0.75, sensitivity 0.89, specificity 0.56) or injurious falls (AUC 0.69, sensitivity 0.96, specificity 0.41) in the following 6 months. Conclusion. Simply asking people with MS if they have fallen in the past year predicts future falls and injurious falls as well as more complex, expensive, or time-consuming approaches.
背景。许多多发性硬化症患者会跌倒,但目前尚不清楚识别跌倒风险增加者的最佳方法。目的。比较跌倒史、问卷调查和身体测试在预测多发性硬化症患者未来跌倒和致伤性跌倒方面的准确性。方法。询问52名多发性硬化症患者在过去2个月和过去一年是否跌倒过。还使用特定活动平衡信心量表、国际跌倒效能量表和多发性硬化症步行量表-12问卷、扩展残疾状态量表、25英尺定时步行测试以及计算机化动态姿势描记法对受试者进行评估,并让他们用日历记录接下来6个月的每日跌倒情况。使用受试者工作特征曲线和逻辑回归比较基线评估预测未来跌倒的能力。结果。所有测试单独进行时提供的跌倒预测结果相似(曲线下面积(AUC)为0.60 - 0.75)。过去一年中有跌倒经历是接下来6个月内跌倒(AUC 0.75,敏感性0.89,特异性0.56)或致伤性跌倒(AUC 0.69,敏感性0.96,特异性0.41)的最佳预测指标。结论。简单询问多发性硬化症患者过去一年是否跌倒,在预测未来跌倒和致伤性跌倒方面与更复杂、昂贵或耗时的方法效果相当。