Department of Physical Therapy and Rehabilitation Science, University of Kansas Medical Center, 3901 Rainbow Blvd, MS 2002, Kansas City, KS 66160; Department of Physical Therapy and Rehabilitation Science, University of Kansas Medical Center, Department of Rehabilitation Sciences and Physical Therapy, Sattam Bin Abdulaziz University, Alkharj, Saudi Arabia.
Department of Physical Therapy and Rehabilitation Science, University of Kansas Medical Center, Kansas City, KS; Department of Physical Therapy, Jazan University, Jazan, Saudi Arabia.
PM R. 2018 Aug;10(8):806-816. doi: 10.1016/j.pmrj.2017.12.005. Epub 2017 Dec 26.
Falls are a common adverse event among people with stroke. Previous studies investigating risk of falls after stroke have relied primarily on retrospective fall history ranging from 6-12 months recall, with inconsistent findings.
To identify factors and balance assessment tools that are associated with number of falls in individuals with chronic stroke.
Secondary analysis of a randomized clinical trial.
Multisite academic and clinical institutions.
Data from 181 participants with stroke (age 60.67 ± 11.77 years, post stroke 4.51 ± 4.78 years) were included.
Study participants completed baseline testing and were prospectively asked about falls. A multivariate negative binomial regression was used to identify baseline predictive factors predicting falls: age, endurance (6 minute walk test), number of medications, motor control (Fugl-Meyer lower extremity score), depression (Patient Health Questionnaire-9), physical activity (number of steps per week), and cognition (Mini Mental Status Exam score). A second negative binomial regression analysis was used to identify baseline balance assessment scores predicting falls: gait velocity (comfortable 10 Meter Walk), Berg Balance Scale (BBS), Timed Up and Go (TUG), and Functional Reach Test (FRT). Receiver operating characteristic (ROC) and area under the curve (AUC) were used to determine the cutoff scores for significant predictors of recurrent falls.
The number of falls during the 42-week follow-up period.
Baseline measures that significantly predicted the number of falls included increased number of medications, higher depression scores, and decreased FRT. Cutoff scores for the number of medications were 8.5 with an AUC of 0.68. Depression scores differentiated recurrent fallers at a threshold of 2.5 scores with an AUC of 0.62. FRT differentiated recurrent fallers at a threshold of 18.15 cm with an AUC of 0.66.
Number of medications, depression scores, and decreased FRT distance at baseline were associated with increased number of falls. Increased medications might indicate multiple comorbidities or polypharmacy effect; increased depression scores may indicate psychological status; and decreased functional reach distance could indicate dynamic balance impairments.
II.
跌倒在脑卒中患者中是一种常见的不良事件。既往研究主要依靠 6-12 个月的回顾性跌倒史来调查脑卒中后跌倒的风险，结果不一致。
确定与慢性脑卒中患者跌倒次数相关的因素和平衡评估工具。
随机临床试验的二次分析。
多地点学术和临床机构。
纳入了 181 名脑卒中患者的数据（年龄 60.67±11.77 岁，脑卒中后 4.51±4.78 年）。
研究参与者完成基线测试，并前瞻性地询问跌倒情况。采用多元负二项回归分析确定预测跌倒的基线预测因素：年龄、耐力（6 分钟步行试验）、用药数量、运动控制（Fugl-Meyer 下肢评分）、抑郁（患者健康问卷-9）、身体活动（每周步数）和认知（简易精神状态检查评分）。采用二次负二项回归分析确定预测跌倒的基线平衡评估得分：步态速度（舒适 10 米步行）、伯格平衡量表（BBS）、计时起立行走测试（TUG）和功能性伸手距离测试（FRT）。接收者操作特征（ROC）和曲线下面积（AUC）用于确定复发性跌倒的显著预测因素的截断值。
42 周随访期间的跌倒次数。
显著预测跌倒次数的基线指标包括用药数量增加、抑郁评分升高和 FRT 降低。用药数量的截断值为 8.5，AUC 为 0.68。抑郁评分在阈值为 2.5 时区分复发性跌倒者，AUC 为 0.62。FRT 在阈值为 18.15cm 时区分复发性跌倒者，AUC 为 0.66。
基线时用药数量、抑郁评分和 FRT 距离减少与跌倒次数增加相关。用药数量增加可能表明存在多种合并症或多药效应；抑郁评分增加可能表明心理状态；而功能性伸手距离减少可能表明动态平衡受损。
II。
