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脑瘫成人步态模式的分类:聚类方法。

Categorization of gait patterns in adults with cerebral palsy: a clustering approach.

机构信息

Université Versailles Saint Quentin en Yvelines, EA 4497, CIC-IT 805, APHP Service de physiologie et d'exploration fonctionnelle, Hôpital Raymond Poincaré, 92380 Garches, France.

出版信息

Gait Posture. 2014 Jan;39(1):235-40. doi: 10.1016/j.gaitpost.2013.07.110. Epub 2013 Aug 12.

Abstract

Gait patterns in adults with cerebral palsy have, to our knowledge, never been assessed. This contrasts with the large number of studies which have attempted to categorize gait patterns in children with cerebral palsy. Several methodological approaches have been developed to objectively classify gait patterns in patients with central nervous system lesions. These methods enable the identification of groups of patients with common underlying clinical problems. One method is cluster analysis, a multivariate statistical method which is used to classify an entire data set into homogeneous groups or "clusters". The aim of this study was to determine, using cluster analysis, the principal gait patterns which can be found in adults with cerebral palsy. Data from 3D motion analyses of 44 adults with cerebral palsy were included. A hierarchical cluster analysis was used to subgroup the different gait patterns based on spatiotemporal and kinematic parameters in the sagittal and frontal planes. Five clusters were identified (C1-C5) among which, 3 subgroups were determined, based on spontaneous gait speed (C1/C2: slow, C3/C4: moderate and C5: almost normal). The different clusters were related to specific kinematic parameters that can be assessed in routine clinical practice. These 5 classifications can be used to follow changes in gait patterns throughout growth and aging as well to assess the effects of different treatments (physiotherapy, surgery, botulinum toxin, etc.) on gait patterns in adults with cerebral palsy.

摘要

据我们所知,成年人脑瘫患者的步态模式从未被评估过。相比之下,有大量研究试图对脑瘫儿童的步态模式进行分类。已经开发了几种方法来客观地对中枢神经系统损伤患者的步态模式进行分类。这些方法可以识别出具有共同潜在临床问题的患者群体。一种方法是聚类分析,这是一种多元统计方法,用于将整个数据集分为同质组或“聚类”。本研究的目的是使用聚类分析确定可以在脑瘫成年人中发现的主要步态模式。该研究纳入了 44 名成人脑瘫患者的三维运动分析数据。使用层次聚类分析根据矢状面和额状面的时空和运动学参数对不同的步态模式进行亚组划分。在这 5 个聚类中(C1-C5),根据自发步行速度(C1/C2:慢,C3/C4:中,C5:几乎正常)确定了 3 个亚组。不同的聚类与可在常规临床实践中评估的特定运动学参数相关。这 5 种分类可用于跟踪生长和衰老过程中步态模式的变化,以及评估不同治疗方法(物理治疗、手术、肉毒毒素等)对脑瘫成年人步态模式的影响。

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