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小脑共济失调、痉挛性截瘫和帕金森病患者特定步态模式的识别:非层次聚类分析

Identification of specific gait patterns in patients with cerebellar ataxia, spastic paraplegia, and Parkinson's disease: A non-hierarchical cluster analysis.

作者信息

Serrao Mariano, Chini Giorgia, Bergantino Matteo, Sarnari Diego, Casali Carlo, Conte Carmela, Ranavolo Alberto, Marcotulli Christian, Rinaldi Martina, Coppola Gianluca, Bini Fabiano, Pierelli Francesco, Marinozzi Franco

机构信息

Department of Medical and Surgical Sciences and Biotechnologies, Sapienza University of Rome, Corso della Repubblica 79, Latina 40100, Italy; Movement Analysis LAB, Rehabilitation Centre Policlinico Italia, Piazza del Campidano 6, 00162 Rome, Italy.

Movement Analysis LAB, Rehabilitation Centre Policlinico Italia, Piazza del Campidano 6, 00162 Rome, Italy; Biolab3, Department of Engineering, Roma TRE University, Via Vito Volterra 62, 00149 Roma, Italy.

出版信息

Hum Mov Sci. 2018 Feb;57:267-279. doi: 10.1016/j.humov.2017.09.005. Epub 2017 Sep 28.

Abstract

Patients with degenerative neurological diseases such as cerebellar ataxia, spastic paraplegia, and Parkinson's disease often display progressive gait function decline that inexorably impacts their autonomy and quality of life. Therefore, considering the related social and economic costs, one of the most important areas of intervention in neurorehabilitation should be the treatment of gait abnormalities. This study aims to determine whether an entire dataset of gait parameters recorded in patients with degenerative neurological diseases can be clustered into homogeneous groups distinct from each other and from healthy subjects. Patients affected by three different types of primary degenerative neurological diseases were studied. These diseases were: i) cerebellar ataxia (28 patients), ii) hereditary spastic paraplegia (31 patients), and iii) Parkinson's disease (70 patients). Sixty-five gender-age-matched healthy subjects were enrolled as a control group. An optoelectronic motion analysis system was used to measure time-distance parameters and lower limb joint kinematics during gait in both patients and healthy controls. When clustering single parameters, step width and ankle joint range of motion (RoM) in the sagittal plane differentiated cerebellar ataxia group from the other groups. When clustering sets of two, three, or four parameters, several pairs, triples, and quadruples of clusters differentiated the cerebellar ataxia group from the other groups. Interestingly, the ankle joint RoM parameter was present in 100% of the clusters and the step width in approximately 50% of clusters. In addition, in almost all clusters, patients with cerebellar ataxia showed the lowest ankle joint RoM and the largest step width values compared to healthy controls, patients with hereditary spastic paraplegia, and Parkinson's disease subjects. This study identified several clusters reflecting specific gait patterns in patients with degenerative neurological diseases. In particular, the specific gait pattern formed by the increased step width, reduced ankle joint RoM, and increased gait variability, can differentiate patients with cerebellar ataxia from healthy subjects and patients with spastic paraplegia or Parkinson's disease. These abnormal parameters may be adopted as sensitive tools for evaluating the effect of pharmacological and rehabilitative treatments.

摘要

患有退行性神经疾病(如小脑共济失调、痉挛性截瘫和帕金森病)的患者通常会出现进行性步态功能衰退,这必然会影响他们的自主性和生活质量。因此,考虑到相关的社会和经济成本,神经康复中最重要的干预领域之一应该是治疗步态异常。本研究旨在确定退行性神经疾病患者记录的整个步态参数数据集是否可以聚类为彼此不同且与健康受试者不同的同质组。对受三种不同类型原发性退行性神经疾病影响的患者进行了研究。这些疾病分别为:i)小脑共济失调(28例患者),ii)遗传性痉挛性截瘫(31例患者),以及iii)帕金森病(70例患者)。招募了65名年龄和性别匹配的健康受试者作为对照组。使用光电运动分析系统测量患者和健康对照在步态期间的时间 - 距离参数和下肢关节运动学。在对单个参数进行聚类时,矢状面的步宽和踝关节活动范围(RoM)将小脑共济失调组与其他组区分开来。在对两个、三个或四个参数集进行聚类时,几组聚类对将小脑共济失调组与其他组区分开来。有趣的是,踝关节RoM参数出现在100%的聚类中,步宽出现在约50%的聚类中。此外,在几乎所有聚类中,与健康对照、遗传性痉挛性截瘫患者和帕金森病患者相比,小脑共济失调患者的踝关节RoM最低,步宽值最大。本研究确定了几个反映退行性神经疾病患者特定步态模式的聚类。特别是,由步宽增加、踝关节RoM减小和步态变异性增加形成的特定步态模式,可以将小脑共济失调患者与健康受试者以及痉挛性截瘫或帕金森病患者区分开来。这些异常参数可作为评估药物和康复治疗效果的敏感工具。

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