Zackrisson Theresa, Bergquist Filip, Eklund Mats, Holmberg Björn, Thorlin Thorleif
Institute of Neuroscience and Physiology, Department of Clinical Neuroscience and Rehabilitation, University of Gothenburg, Sweden.
J Mot Behav. 2013;45(5):415-22. doi: 10.1080/00222895.2013.815152. Epub 2013 Aug 25.
Several partly overlapping diseases have Parkinsonism as a symptom and tools that may differentiate between these disorders would be helpful. The authors evaluated the discriminating properties of the objective automated posturo-locomotor-manual (PLM) L-DOPA test in regard to health, and the movement disorders Parkinson's disease (PD), multiple system atrophy (MSA), and progressive supranuclear palsy (PSP). A PLM test-retest procedure was performed in healthy controls (n = 37) and results were compared with PLM L-DOPA tests performed by 132 patients with Parkinsonism in intermediate to advanced stages (56 PD, 53 MSA, 23 PSP). The movement time (MT) for the standardized movement and its different components was measured. The discriminating abilities of individual, or combinations of, test variables were determined by forward stepwise multiple logistic regression and evaluated with receiver-operating characteristic (ROC) analysis. Each PLM variable separated healthy persons from patients with Parkinsonism before administration of L-DOPA (area under the curve (AUC) = 0.94-0.99, p < .001 for any separate variable). A combination of (MToff - MTon)/MToff and MTon had the highest ability to separate patients with PD from patients with atypical Parkinsonism (area under the curve = 0.91, p < .001). The PLM test discriminates between healthy controls and patients with Parkinsonism, and between patients with Parkinson's disease and patients with atypical Parkinsonism.
有几种部分重叠的疾病都以帕金森症为症状,能够区分这些病症的工具会很有帮助。作者评估了客观自动化姿势 - 运动 - 手动(PLM)左旋多巴测试在健康人群以及运动障碍疾病帕金森病(PD)、多系统萎缩(MSA)和进行性核上性麻痹(PSP)方面的鉴别特性。在健康对照者(n = 37)中进行了PLM重测程序,并将结果与132例中晚期帕金森症患者(56例PD、53例MSA、23例PSP)进行的PLM左旋多巴测试结果进行比较。测量了标准化运动及其不同组成部分的运动时间(MT)。通过向前逐步多元逻辑回归确定测试变量单独或组合的鉴别能力,并通过受试者操作特征(ROC)分析进行评估。在给予左旋多巴之前,每个PLM变量都能将健康人与帕金森症患者区分开(曲线下面积(AUC)= 0.94 - 0.99,任何单独变量的p <.001)。(MToff - MTon)/MToff和MTon的组合具有将PD患者与非典型帕金森症患者区分开的最高能力(曲线下面积 = 0.91,p <.001)。PLM测试能够区分健康对照者与帕金森症患者,以及帕金森病患者与非典型帕金森症患者。