躯体感觉系统的完整性解释了中风后治疗反应的差异。
Somatosensory system integrity explains differences in treatment response after stroke.
机构信息
From the Departments of Anatomy and Neurobiology (M.L.I., D.J.R., S.C.C.), Biomedical Engineering (J.R.R., D.J.R.), Neurology (V.C. , S.C.C.), Mechanical and Aerospace Engineering (D.J.R.), and Physical Medicine and Rehabilitation (D.J.R. , S.C.C.), University of California at Irvine; and Department of Mechanical Engineering (E.T.W.), University of Idaho, Moscow.
出版信息
Neurology. 2019 Mar 5;92(10):e1098-e1108. doi: 10.1212/WNL.0000000000007041. Epub 2019 Feb 6.
OBJECTIVE
To test the hypothesis that, in the context of robotic therapy designed to enhance proprioceptive feedback via a Hebbian model, integrity of both somatosensory and motor systems would be important in understanding interparticipant differences in treatment-related motor gains.
METHODS
In 30 patients with chronic stroke, behavioral performance, neural injury, and neural function were quantified for somatosensory and motor systems. Patients then received a 3-week robot-based therapy targeting finger movements with enhanced proprioceptive feedback.
RESULTS
Hand function improved after treatment (Box and Blocks score increase of 2.8 blocks, = 0.001) but with substantial variability: 9 patients showed improvement exceeding the minimal clinically important difference (6 blocks), while 8 patients (all of whom had >2-SD greater proprioception deficit compared to 25 healthy controls) showed no improvement. In terms of baseline behavioral assessments, a somatosensory measure (finger proprioception assessed robotically) best predicted treatment gains, outperforming all measures of motor behavior. When the neural basis underlying variability in treatment response was examined, somatosensory-related variables were again the strongest predictors. A multivariate model combining total sensory system injury and sensorimotor cortical connectivity (between ipsilesional primary motor and secondary somatosensory cortices) explained 56% of variance in treatment-induced hand functional gains ( = 0.002).
CONCLUSIONS
Measures related to the somatosensory network best explained interparticipant differences in treatment-related hand function gains. These results underscore the importance of baseline somatosensory integrity for improving hand function after stroke and provide insights useful for individualizing rehabilitation therapy.
CLINICALTRIALSGOV IDENTIFIER
NCT02048826.
目的
验证假设，在基于机器人的治疗中，通过赫布模型增强本体感觉反馈，在理解治疗相关运动增益的个体间差异方面，感觉和运动系统的完整性很重要。
方法
在 30 名慢性中风患者中，对感觉和运动系统的行为表现、神经损伤和神经功能进行了量化。然后，患者接受了为期 3 周的机器人手指运动治疗，增强本体感觉反馈。
结果
治疗后手功能改善（Box and Blocks 评分增加 2.8 分， = 0.001），但存在较大的变异性：9 名患者的改善超过了最小临床重要差异（6 分），而 8 名患者（所有患者的本体感觉缺陷均超过 2 个标准差，与 25 名健康对照组相比）没有改善。就基线行为评估而言，感觉测量（机器人评估手指本体感觉）是预测治疗效果的最佳指标，优于所有运动行为测量。当检查治疗反应变异性的神经基础时，感觉相关变量再次成为最强的预测因素。一个结合了总感觉系统损伤和感觉运动皮质连接性（对侧初级运动皮质和次级感觉皮质之间）的多变量模型，解释了治疗引起的手部功能增益变化的 56%（ = 0.002）。
结论
与感觉网络相关的测量指标最好地解释了治疗相关手部功能增益的个体间差异。这些结果强调了基线感觉完整性在手后改善手部功能的重要性，并为个性化康复治疗提供了有用的见解。
临床试验.gov 标识符：NCT02048826。
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