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。我们开展了一项渐进式研究计划，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类型和相关治疗。但慢性病组的平均获益不大，尽管直觉认为早期干预将是有益的，但几乎没有数据证实这一点。因此，我们建议利用我们在慢性中风损伤机器人辅助训练方面的专业知识，以评估预测模型的潜力，以选择更有机会获得功能增益的患者。我们的临床假设是，存在恢复潜力的运动学和生理学生物标志物，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。连接性的功能和解剖学测量以及可塑性相关基因型是要测试的次要生物标志物。中风后的时间是另一个有希望测试的标志，对临床实践具有重要意义。我们还提出了一个次要机制假设，即干预将改变适应不良的跨半球皮质抑制。具体目标：创建干预后功能和残疾的预测模型。测量 12 周机器人辅助治疗以及中风后 6 个月以上过渡到任务训练的效果。创建一个模型，预测 Fugl-Meyer 响应干预而发生的有临床意义的变化，并测试模型的有效性。通过使用经颅磁刺激研究静默期和募集曲线，确定我们的混合训练方法对半球间抑制的影响。将招募持续时间>6个月、病情稳定且没有挛缩或其他会干扰训练的损伤的中度至重度手臂功能障碍（基于Fugl-Meyer评分为7至45）的患者。 96 名受试者将被分配到一个采用多基线方法的研究组，以确保测量的稳定性。评估将由不了解预测模型的审查员进行。训练的前四个星期将包括腕部机器人训练课程，第二个四周将包括平面机器人训练课程，第三周将包括交替腕部和平面训练课程。机器人培训课程持续 45 分钟，随后进行 15 分钟功能相关任务的培训（翻译为任务培训 (TTT)）。临床评估将包括中风影响量表（主要结果）、Fugl-Meyer 上肢运动功能部分测试、Wolf 运动功能测试、行动研究手臂测试和家庭手臂使用活动监测器。将在训练前后进行运动学分析。大多数患者将同意进行 TMS 和 MRI。在这些受试者中，将在每次结果测量访视时确定半球内抑制。 MRI 仅在基线期进行，用于确定病变类型、白质完整性和皮质脊髓束的功能连接。结束时 为了实现这些目标，我们将拥有一种关于中风后期强化手臂治疗的临床决策方法，并对其工作原理有更好的机械理解。该方法将在整个退伍军人管理局医疗系统内外传播。