背景:评估运动质量的传统方法依赖于主观的标准化量表和临床专业知识。这种局限性为评估脊髓小脑共济失调(SCA)患者带来了挑战,其中流动性的变化可能是微妙和多变的。我们假设机器学习分析系统可以补充传统的临床医生评估的步态测量。我们的目的是使用基于视频的步态离散度评估来比较troriluzole与安慰剂对SCA成人步态质量的影响。
方法:SCA参与者在第3阶段进行步态评估,双盲,曲鲁唑的安慰剂对照试验(NCT03701399)。通过深度学习姿态提取算法处理视频,然后估计一种新的步态稳定性度量,姿态分散指数,量化逐帧对称性,balance,在自然和串联行走任务中的稳定性。在混合线性模型中评估曲鲁唑治疗的效果,参与者级别的分组,和按年龄调整的治疗组-就诊周互动,性别,用于共济失调评估和评级的基线修正功能量表(f-SARA),和诊断后的时间。
结果:来自218名随机参与者,67名和56名参与者有一个串联和自然步行尝试的可解释视频,分别。在第48周,与安慰剂相比,分配给三列鲁唑的个体表现出串联行走姿势分散指数的显着改善(p=0.010){调整的相互作用系数:0.584[95%置信区间(CI)0.137至1.031]}。类似的,在自然步行评估[系数:1.198(95%CI-1.067~3.462)]中观察到无显著趋势.Further,自然步行期间较低的基线姿势离散度指数(p=0.041)与较高的后续跌倒风险显著相关[校正泊松系数:-0.356[95%CI-0.697~-0.014)].
结论:使用这种新颖的方法,与安慰剂相比,串联步行时,曲鲁唑治疗的受试者的步态有所改善。应用于视频捕获的步态参数的机器学习可以补充SCA成人中临床医生报告的运动评估。姿态分散指数可能会在未来的研究中增强评估。审判注册-临床试验。
■NCT03701399。
BACKGROUND: Traditional methods for assessing movement quality rely on subjective standardized scales and clinical expertise. This limitation creates challenges for assessing patients with spinocerebellar ataxia (SCA), in whom changes in mobility can be subtle and varied. We hypothesized that a machine learning analytic system might complement traditional clinician-rated measures of gait. Our objective was to use a video-based assessment of gait dispersion to compare the effects of troriluzole with placebo on gait quality in adults with SCA.
METHODS: Participants with SCA underwent gait assessment in a phase 3, double-blind, placebo-controlled trial of troriluzole (NCT03701399). Videos were processed through a deep learning pose extraction algorithm, followed by the estimation of a novel gait stability measure, the Pose Dispersion Index, quantifying the frame-by-frame symmetry, balance, and stability during natural and tandem walk tasks. The effects of troriluzole treatment were assessed in mixed linear models, participant-level grouping, and treatment group-by-visit week interaction adjusted for age, sex, baseline modified Functional Scale for the Assessment and Rating of Ataxia (f-SARA), and time since diagnosis.
RESULTS: From 218 randomized participants, 67 and 56 participants had interpretable videos of a tandem and natural walk attempt, respectively. At Week 48, individuals assigned to troriluzole exhibited significant (p = 0.010) improvement in tandem walk Pose Dispersion Index versus placebo {adjusted interaction coefficient: 0.584 [95% confidence interval (CI) 0.137 to 1.031]}. A similar, nonsignificant trend was observed in the natural walk assessment [coefficient: 1.198 (95% CI - 1.067 to 3.462)]. Further, lower baseline Pose Dispersion Index during the natural walk was significantly (p = 0.041) associated with a higher risk of subsequent falls [adjusted Poisson coefficient: - 0.356 [95% CI - 0.697 to - 0.014)].
CONCLUSIONS: Using this novel approach, troriluzole-treated subjects demonstrated improvement in gait as compared to placebo for the tandem walk. Machine learning applied to video-captured gait parameters can complement clinician-reported motor assessment in adults with SCA. The Pose Dispersion Index may enhance assessment in future research. TRIAL REGISTRATION-CLINICALTRIALS.
UNASSIGNED: NCT03701399.