Department of Physical Therapy, University of Utah, 520 Wakara Way, Salt Lake City, UT 84108, USA.
Parkinsonism Relat Disord. 2011 Mar;17(3):166-71. doi: 10.1016/j.parkreldis.2010.12.007. Epub 2011 Jan 6.
Despite clear deficits in postural control, most clinical examination tools lack accuracy in identifying persons with Parkinson disease (PD) who have fallen or are at risk for falls. We assert that this is in part due to the lack of ecological validity of the testing.
To test this assertion, we examined the responsiveness and predictive validity of the Functional Gait Assessment (FGA), the Pull test, and the Timed up and Go (TUG) during clinically defined ON and OFF medication states. To address responsiveness, ON/OFF medication performance was compared. To address predictive validity, areas under the curve (AUC) of receiver operating characteristic (ROC) curves were compared. Comparisons were made using separate non-parametric tests.
Thirty-six persons (24 male, 12 female) with PD (22 fallers, 14 non-fallers) participated. Only the FGA was able to detect differences between fallers and non-fallers for both ON/OFF medication testing. The predictive validity of the FGA and the TUG for fall identification was higher during OFF medication compared to ON medication testing. The predictive validity of the FGA was higher than the TUG and the Pull test during ON and OFF medication testing.
In order to most accurately identify fallers, clinicians should test persons with PD in ecologically relevant conditions and tasks. In this study, interpretation of the OFF medication performance and use of the FGA provided more accurate prediction of those who would fall.
尽管姿势控制存在明显缺陷,但大多数临床检查工具在识别已跌倒或有跌倒风险的帕金森病(PD)患者方面缺乏准确性。我们断言,这部分是由于测试缺乏生态有效性。
为了检验这一说法,我们在临床定义的药物开启和关闭状态下,检查了功能性步态评估(FGA)、牵拉试验和计时起立行走(TUG)的反应性和预测有效性。为了研究反应性,比较了药物开启和关闭时的表现。为了研究预测有效性,比较了接收者操作特征(ROC)曲线下的面积(AUC)。使用单独的非参数检验进行了比较。
36 名(24 名男性,12 名女性)PD 患者(22 名跌倒者,14 名非跌倒者)参与了研究。只有 FGA 能够在药物开启和关闭测试中检测到跌倒者和非跌倒者之间的差异。与药物开启测试相比,FGA 和 TUG 在药物关闭测试中对跌倒识别的预测有效性更高。在药物开启和关闭测试中,FGA 的预测有效性均高于 TUG 和牵拉试验。
为了最准确地识别跌倒者,临床医生应在生态相关的条件和任务中测试 PD 患者。在这项研究中,对药物关闭时的表现的解释和 FGA 的使用提供了对那些可能跌倒的人的更准确预测。