Computer Mouse Use Captures Ataxia and Parkinsonism, Enabling Accurate Measurement and Detection
Computer Mouse Use Captures Ataxia and Parkinsonism, Enabling Accurate Measurement and Detection
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DOI：
10.1002/mds.27915
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发表时间：
2019-11-07
影响因子：
8.6
通讯作者：
Gupta, Anoopum S.
中科院分区：
文献类型：
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作者：
Gajos, Krzysztof Z.;Reinecke, Katharina;Gupta, Anoopum S.
背景运动障碍的客观评估需要支持临床试验和促进诊断。本研究的目的是确定基于网络的快速计算机鼠标测试（Hevelius）是否可以检测和准确测量共济失调和帕金森症。方法95名共济失调患者、46名帕金森患者、29名对照参与者和229，017名在线参与者完成了Hevelius。我们在年龄标准化的Hevelius特征上训练了机器学习模型，以（1）测量严重程度和疾病进展，（2）区分表型与对照组以及彼此之间。结果回归模型估计值与临床评分密切相关（从r = 0.66的ADRS优势臂总数的r = 0.83的简要共济失调评定量表）。疾病变化模型以高灵敏度识别共济失调进展。分类模型区分共济失调或帕金森病与健康对照具有高灵敏度（>= 0.91）和特异性（>= 0.90）。结论Hevelius在小鼠使用的几分钟内产生了颗粒状和准确的运动评估，可能是有用的结果测量和筛选工具。(c)2019作者出版社：Wiley Periodicals，Inc.国际帕金森和运动障碍协会（International Parkinson and Movement Disorder Society）
Background Objective assessments of movement impairment are needed to support clinical trials and facilitate diagnosis. The objective of the current study was to determine if a rapid web-based computer mouse test (Hevelius) could detect and accurately measure ataxia and parkinsonism. Methods Ninety-five ataxia, 46 parkinsonism, and 29 control participants and 229,017 online participants completed Hevelius. We trained machine-learning models on age-normalized Hevelius features to (1) measure severity and disease progression and (2) distinguish phenotypes from controls and from each other. Results Regression model estimates correlated strongly with clinical scores (from r = 0.66 for UPDRS dominant arm total to r = 0.83 for the Brief Ataxia Rating Scale). A disease change model identified ataxia progression with high sensitivity. Classification models distinguished ataxia or parkinsonism from healthy controls with high sensitivity (>= 0.91) and specificity (>= 0.90). Conclusions Hevelius produces a granular and accurate motor assessment in a few minutes of mouse use and may be useful as an outcome measure and screening tool. (c) 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.