Predictors of return to driving after stroke.
Predictors of return to driving after stroke.
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DOI：
10.1097/phm.0b013e318282bc0d
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发表时间：
2013-07
影响因子：
3
通讯作者：
Lang CE
中科院分区：
文献类型：
--
作者：
Aufman EL;Bland MD;Barco PP;Carr DB;Lang CE
虽然恢复驾驶是许多中风幸存者的主要担忧，但预测谁将在中风后恢复驾驶对于康复专业人员来说通常很困难。本研究的主要目的是确定住院康复医院入院时存在的患者因素，这些因素可用于确定哪些急性中风患者会或不会恢复驾驶。在比较回归者和非回归者的人口统计学和临床特征后，采用向后逐步法建立了以回归驾驶为结果变量的逻辑回归模型。百分之三十一 (48/156) 的中风前开车的患者在中风后六个月恢复开车。最终的回归模型使用 FIM 认知和下肢运动指数评分，预测驾驶结果的准确度为 75% (107/143)。入院康复时 FIM 认知和下肢运动指数评分较低的患者在六个月后恢复驾驶的可能性较小。康复专业人员可以使用该模型来帮助为患者及其家人提供咨询并集中治疗目标。
While returning to driving is a major concern for many stroke survivors, predicting who will return to driving after a stroke is often difficult for rehabilitation professionals. The primary aim of this study was to identify patient factors present at admission to an inpatient rehabilitation hospital that can be used to identify which patients with acute stroke will and will not return to driving. After comparing returners and non-returners on demographic and clinical characteristics, a logistic regression model with return to driving as the outcome variable was built using the backward stepwise method. Thirty-one percent (48/156) of patients who had been driving before their stroke had returned to driving six months post-stroke. The final regression model, using FIM cognition and lower extremity Motricity Index scores, predicted the driving outcome with an accuracy of 75% (107/143). Patients with lower FIM cognition and lower extremity Motricity Index scores at admission to inpatient rehabilitation are less likely to return to driving at six months. This model could be used by rehabilitation professionals to help counsel patients and their families and focus treatment goals.