Department of Rehabilitation Sciences, Katholieke Universiteit Leuven, Leuven, Belgium.
Mov Disord. 2012 Nov;27(13):1644-51. doi: 10.1002/mds.25183. Epub 2012 Oct 31.
Freezing of gait (FOG) is part of a complex clinical picture in Parkinson's disease (PD) and is largely refractory to standard care. Diverging hypotheses exist about its origins, but a consolidated view on what determines FOG is lacking. The aim of this study was to develop an integrative model of FOG in people with PD. This cross-sectional study included 51 Parkinson subjects: 24 patients without FOG and 27 with FOG matched for age, gender, and disease severity. Subjects underwent an extensive clinical test battery evaluating general disease characteristics, gait and balance, nongait freezing, and cognitive functions. The relative contribution of these outcomes to FOG was determined using logistic regression analysis. The combination of the following four independent contributors provided the best explanatory model of FOG (R(2) = 0.49): nongait freezing; levodopa equivalent dose (LED); cognitive impairment; and falls and balance problems. The model yields a high-risk profile for FOG (P > 95%) when Parkinson patients are affected by at least one type of nongait freezing (e.g., freezing of other repetitive movements), falls or balance problems during the last 3 months, and a Scales for Outcomes in Parkinson's Disease-Cognition score below 28. A high LED further increases the risk of FOG to 99%. Nongait freezing, increased dopaminergic drug dose, cognitive deficits, and falls and balance problems are independent determinants of FOG in people with PD and may play a synergistic role in its manifestation.
冻结步态(FOG)是帕金森病(PD)复杂临床表现的一部分,对标准治疗方法基本无效。对于其起源,存在不同的假设,但缺乏对决定 FOG 的因素的综合观点。本研究旨在建立 PD 患者 FOG 的综合模型。这项横断面研究纳入了 51 名帕金森病患者:24 名无 FOG 患者和 27 名 FOG 患者,这些患者在年龄、性别和疾病严重程度方面相匹配。患者接受了广泛的临床测试,评估一般疾病特征、步态和平衡、非步态冻结和认知功能。使用逻辑回归分析确定这些结果对 FOG 的相对贡献。以下四个独立因素的组合为 FOG 提供了最佳的解释模型(R²=0.49):非步态冻结、左旋多巴等效剂量(LED)、认知障碍和跌倒和平衡问题。当帕金森病患者在过去 3 个月中至少有一种非步态冻结(如其他重复性运动冻结)、跌倒或平衡问题,以及帕金森病认知评分低于 28 时,该模型会生成 FOG 的高风险特征(P>95%)。高 LED 进一步将 FOG 的风险增加到 99%。非步态冻结、增加的多巴胺能药物剂量、认知缺陷以及跌倒和平衡问题是 PD 患者 FOG 的独立决定因素,可能在其表现中发挥协同作用。