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左旋多巴对晚期帕金森病患者肌电图模式的影响

Levodopa-Induced Changes in Electromyographic Patterns in Patients with Advanced Parkinson's Disease.

作者信息

Ruonala Verneri, Pekkonen Eero, Airaksinen Olavi, Kankaanpää Markku, Karjalainen Pasi A, Rissanen Saara M

机构信息

Department of Applied Physics, University of Eastern Finland, Kuopio, Finland.

Department of Clinical Neurosciences, Neurology, University of Helsinki, Helsinki University Hospital, Helsinki, Finland.

出版信息

Front Neurol. 2018 Feb 5;9:35. doi: 10.3389/fneur.2018.00035. eCollection 2018.

Abstract

Levodopa medication is the most efficient treatment for motor symptoms of Parkinson's disease (PD). Levodopa significantly alleviates rigidity, rest tremor, and bradykinesia in PD. The severity of motor symptoms can be graded with UPDRS-III scale. Levodopa challenge test is routinely used to assess patients' eligibility to deep-brain stimulation (DBS) in PD. Feasible and objective measurements to assess motor symptoms of PD during levodopa challenge test would be helpful in unifying the treatment. Twelve patients with advanced PD who were candidates for DBS treatment were recruited to the study. Measurements were done in four phases before and after levodopa challenge test. Rest tremor and rigidity were evaluated using UPDRS-III score. Electromyographic (EMG) signals from biceps brachii and kinematic signals from forearm were recorded with wireless measurement setup. The patients performed two different tasks: arm isometric tension and arm passive flexion-extension. The electromyographic and the kinematic signals were analyzed with parametric, principal component, and spectrum-based approaches. The principal component approach for isometric tension EMG signals showed significant decline in characteristics related to PD during levodopa challenge test. The spectral approach on passive flexion-extension EMG signals showed a significant decrease on involuntary muscle activity during the levodopa challenge test. Both effects were stronger during the levodopa challenge test compared to that of patients' personal medication. There were no significant changes in the parametric approach for EMG and kinematic signals during the measurement. The results show that a wireless and wearable measurement and analysis can be used to study the effect of levodopa medication in advanced Parkinson's disease.

摘要

左旋多巴药物是治疗帕金森病(PD)运动症状最有效的方法。左旋多巴能显著缓解PD患者的僵硬、静止性震颤和运动迟缓。运动症状的严重程度可用统一帕金森病评定量表第三部分(UPDRS - III)进行分级。左旋多巴激发试验常用于评估PD患者是否适合接受脑深部电刺激(DBS)治疗。在左旋多巴激发试验期间,采用可行且客观的测量方法来评估PD的运动症状,将有助于统一治疗方案。本研究招募了12例晚期PD患者,这些患者均为DBS治疗的候选对象。在左旋多巴激发试验前后分四个阶段进行测量。使用UPDRS - III评分评估静止性震颤和僵硬程度。通过无线测量装置记录肱二头肌的肌电图(EMG)信号和前臂的运动学信号。患者执行两项不同任务:手臂等长收缩和手臂被动屈伸。采用参数法、主成分法和基于频谱的方法对EMG和运动学信号进行分析。对于等长收缩EMG信号,主成分法显示在左旋多巴激发试验期间与PD相关的特征显著下降。对于被动屈伸EMG信号,频谱法显示在左旋多巴激发试验期间非自愿肌肉活动显著减少。与患者个人用药相比,左旋多巴激发试验期间这两种效应更强。测量期间,EMG和运动学信号的参数法未出现显著变化。结果表明,无线可穿戴测量与分析可用于研究左旋多巴药物对晚期帕金森病的疗效。

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