Neurophysiological and Kinematic Predictors of Response in Chronic Stroke

慢性中风反应的神经生理学和运动学预测因子

• 批准号: 9397976
• 负责人: GEORGE F. WITTENBERG
• 金额: --
• 依托单位: BALTIMORE VA MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-07-01 至 2019-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9397976
• 关键词: Accelerometer; Action Research; Activities of Daily Living; Affect; Algorithms; Anatomy; Biological Markers; Biological Preservation; Brain; Chronic; Chronic Phase; Clinical; Clinical Trials; Consent; Contracture; Corticospinal Tracts; Costs and Benefits; Data; Decision Making; Early Intervention; Effectiveness; Enrollment; Ensure; Environment; Evaluation; Functional Imaging; Functional disorder; Genotype; Goals; Gold; Home environment; Hybrids; Impairment; Individual; Internal Capsule; Intervention; Intuition; Investigation; Knowledge; Lesion; Magnetic Resonance Imaging; Measurement; Measures; Medical; Methodology; Methods; Modeling; Monitor; Motor; Motor Activity; Motor Cortex; Movement; Neurologic; Non-linear Models; Outcome; Outcome Assessment; Outcome Measure; Participant; Patients; Performance; Physiological; Physiology; Population; Prediction of Response to Therapy; Predictive Value; Predictive Value of Tests; Publishing; Quality of life; Recovery; Recovery of Function; Recruitment Activity; Rehabilitation therapy; Research; Rest; Robot; Robotics; Stroke; Structure; Survivors; System; Testing; Therapeutic; Time; Training; Transcranial magnetic stimulation; Translations; Upper Extremity; Veterans; Visit; Wolves; Work; Wrist; arm; base; chronic stroke; clinical decision-making; clinical practice; clinical predictors; clinically significant; cost; cost effective; design; disability; effective intervention; functional gain; functional loss; hemiparesis; improved; kinematics; motor learning; motor recovery; neurophysiology; potential biomarker; predicting response; predictive modeling; primary outcome; programs; public health relevance; repetitive task practice; research clinical testing; response; robot assistance; robot rehabilitation; robot therapy; robotic device; robotic training; standard care; tool; white matter

 DESCRIPTION (provided by applicant): Upper extremity hemiparesis has a profound and lasting negative impact on quality of life and independence in activities of daily living for stoke survivors, yet, despite many investigations, there are no gold standard treatments in current clinical practice. We have carried out a progressive research program that has demonstrated the effectiveness of robotic therapy in chronic stroke patients, and then optimizing the type of robotic therapy and associated therapy that these patients receive. But gains in the chronic group are modest on average, and despite an intuition that earlier intervention will be beneficial, there is little data to confirm that. Therefore, we propose to build upon our expertise with robot-assisted training for chronic stroke impairment in order to evaluate the potential of predictive models that would select patients with better chances of making functional gains. Our clinical hypothesis is that kinematic and physiological biomarkers of recovery potential exist, and include baseline motor ability in both functional tasks and in the robotic environment, and measures of corticospinal tract effectiveness determined by transcranial magnetic stimulation. Functional and anatomical measures of connectivity, and plasticity relevant genotype are secondary biomarkers to test. Time after stroke is another promising marker to test, with strong implications for clinical practice. We also propose a secondary mechanistic hypothesis that maladaptive transhemispheric cortical inhibition will be altered by the intervention. Specific Objectives: Create a predictive model of function and disability following the intervention. Measure the effects of 12 weeks of robot-assisted therapy and transition to task training at > 6 months after stroke. Create a model that predicts clinically meaningful change in Fugl-Meyer in response to the intervention and test the validity of the model. Determine the effect our hybrid method of training has on interhemispheric inhibition by using transcranial magnetic stimulation to study silent period and recruitment curve. Patients with moderate to severe arm dysfunction (based on Fugl-Meyer scores of 7 to 45) of >6 months duration who are medically stable and do not have contractures or other impairments that would interfere with training will be enrolled. 96 subjects will be assigned to a single study arm with a multiple baseline approach to ensure stability of measures. Evaluations will be conducted by an examiner who has no knowledge of the predictive model. The first four weeks of training will consist of wrist robot training sessions, te second four weeks will consist of planar robot training sessions and the third four weeks will consist of alternation wrist and planar training sessions. Robot training sessions will be 45 minutes in duration followed by 15 minutes of training on functionally relevant tasks (translation to task training (TTT)). Clinical evaluations will include Stroke Impact Scale (Primary Outcome), Fugl-Meyer Upper Extremity Motor Performance Section Test, Wolf Motor Function Test, Action Research Arm Test, and activity monitor of home arm use. Kinematic analysis will be conducted pre and post training. A majority of patients will be consented for TMS and MRI. In those subjects intrahemispheric inhibition will be determined at each outcomes measurement visit. MRI will be performed only at the baseline period, and will be used to define the lesion type, white matter integrity and functional connectivity of the corticospinal tract. At the conclusion of these aims we will have a method for clinical decision-making regarding intensive arm therapy late after stroke, and a better mechanistic understanding of how it works. The method will be disseminated throughout the VA medical system and beyond.

 描述（由申请人提供）： 上肢偏瘫对中风幸存者的生活质量和日常生活活动的独立性具有深远而持久的负面影响，然而，尽管进行了许多研究，但目前的临床实践中还没有金标准治疗方法，我们已经开展了一项渐进的研究计划。这已经证明了机器人治疗对慢性中风患者的有效性，然后优化了这些患者接受的机器人治疗和相关治疗的类型，但平均而言，慢性组的进展有限，尽管直觉认为早期干预将是有益的。 ，几乎没有数据可以证实这一点。因此，我们建议利用我们在慢性中风损伤的机器人辅助训练方面的专业知识，以评估预测模型的潜力，这些模型将选择更有机会获得功能的患者，我们的临床假设是恢复的运动学和生理生物标志物。潜在的存在，包括功能任务和机器人环境中的基线运动能力，以及通过颅磁刺激确定的皮质脊髓束有效性的测量，以及可塑性相关的基因型是中风后要测试的次要生物标志物。是另一个我们还提出了一个次要机制假设，即干预将导致适应不良的跨半球皮质抑制。具体目标：创建一个预测模型，测量干预后的功能和残疾。创建一个模型，预测 Fugl-Meyer 对干预的反应有临床意义的变化，并测试模型的有效性。混合训练方法通过使用经颅磁刺激来研究静默期和募集曲线来研究半球间抑制，持续时间>6个月且病情稳定且患有中度至重度手臂功能障碍（基于Fugl-Meyer评分为7至45）的患者。不存在会干扰训练的挛缩或其他损伤的受试者将被分配到采用多基线方法的单一研究组，以确保措施的稳定性，由不具备相关知识的检查员进行。训练的前四周将包括腕式机器人训练课程，第二周将包括平面机器人训练课程，第三周将包括交替腕式和平面机器人训练课程。持续 45 分钟，然后进行 15 分钟功能相关任务的训练（翻译为任务训练 (TTT)），临床评估将包括中风影响量表（主要结果）、Fugl-Meyer 上肢运动性能部分测试、Wolf。大多数患者将在训练前和训练后进行运动功能测试、动作研究手臂测试和运动学分析，以测定这些受试者的半球内抑制情况。 MRI 将仅在基线期进行，并用于在结束时确定病变类型、白质完整性和皮质脊髓束的功能连接。 为了实现这些目标，我们将制定一种关于中风后期强化手臂治疗的临床决策方法，并更好地了解其工作原理，该方法将在整个 VA 医疗系统及其他地区传播。