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帕金森病患者安静站立时压力中心的综合多变量分析。

A comprehensive multivariate analysis of the center of pressure during quiet standing in patients with Parkinson's disease.

作者信息

Fujii Shintaro, Takamura Yusaku, Ikuno Koki, Morioka Shu, Kawashima Noritaka

机构信息

Graduate School of Health Sciences, Kio University, Nara, Japan.

Department of Rehabilitation, Nishiyamato Rehabilitation Hospital, Nara, Japan.

出版信息

J Neuroeng Rehabil. 2024 Apr 23;21(1):59. doi: 10.1186/s12984-024-01358-1.

Abstract

BACKGROUND

We hypothesized that postural instability observed in individuals with Parkinson's disease (PD) can be classified as distinct subtypes based on comprehensive analyses of various evaluated parameters obtained from time-series of center of pressure (CoP) data during quiet standing. The aim of this study was to characterize the postural control patterns in PD patients by performing an exploratory factor analysis and subsequent cluster analysis using CoP time-series data during quiet standing.

METHODS

127 PD patients, 47 aged 65 years or older healthy older adults, and 71 healthy young adults participated in this study. Subjects maintain quiet standing for 30 s on a force platform and 23 variables were calculated from the measured CoP time-series data. Exploratory factor analysis and cluster analysis with a Gaussian mixture model using factors were performed on each variable to classify subgroups based on differences in characteristics of postural instability in PD.

RESULTS

The factor analysis identified five factors (magnitude of sway, medio-lateral frequency, anterio-posterior frequency, component of high frequency, and closed-loop control). Based on the five extracted factors, six distinct subtypes were identified, which can be considered as subtypes of distinct manifestations of postural disorders in PD patients. Factor loading scores for the clinical classifications (younger, older, and PD severity) overlapped, but the cluster classification scores were clearly separated.

CONCLUSIONS

The cluster categorization clearly identifies symptom-dependent differences in the characteristics of the CoP, suggesting that the detected clusters can be regarded as subtypes of distinct manifestations of postural disorders in patients with PD.

摘要

背景

我们假设,通过对安静站立期间压力中心(CoP)数据时间序列获得的各种评估参数进行综合分析,帕金森病(PD)患者中观察到的姿势不稳可分为不同亚型。本研究的目的是通过在安静站立期间使用CoP时间序列数据进行探索性因素分析和随后的聚类分析,来表征PD患者的姿势控制模式。

方法

127名PD患者、47名65岁及以上的健康老年人和71名健康年轻人参与了本研究。受试者在测力平台上安静站立30秒,并根据测量的CoP时间序列数据计算23个变量。对每个变量进行探索性因素分析和使用因素的高斯混合模型聚类分析,以根据PD患者姿势不稳特征的差异对亚组进行分类。

结果

因素分析确定了五个因素(摆动幅度、中外侧频率、前后频率、高频成分和闭环控制)。基于提取的五个因素,确定了六种不同的亚型,可视为PD患者姿势障碍不同表现的亚型。临床分类(年轻、年长和PD严重程度)的因素负荷得分重叠,但聚类分类得分明显分开。

结论

聚类分类清楚地识别了CoP特征中与症状相关的差异,表明检测到的聚类可被视为PD患者姿势障碍不同表现的亚型。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/66ff/11036778/9b7d667d3cfa/12984_2024_1358_Fig1_HTML.jpg

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