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: 10086003
• 负责人: GEORGE F. WITTENBERG
• 金额: --
• 依托单位: VETERANS HEALTH ADMINISTRATION
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-07-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10086003
• 关键词: Accelerometer; Action Research; Activities of Daily Living; Affect; Algorithms; Anatomy; Biological Markers; 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; 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; post stroke; potential biomarker; predicting response; predictive modeling; preservation; primary outcome; programs; public health relevance; recruit; repetitive task practice; research clinical testing; response; robot assistance; robot rehabilitation; robot therapy; robotic device; robotic training; standard care; stroke patient; tool; treatment optimization; 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)： 上肢偏瘫对卒中幸存者的生活质量和日常生活自理能力具有深远而持久的负面影响，然而，尽管有许多研究，但目前的临床实践中还没有金标准的治疗方法。我们开展了一项渐进的研究计划，证明了机器人治疗在慢性中风患者中的有效性，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。但慢性病患者的平均收益不大，尽管有一种直觉认为，早期干预将是有益的，但几乎没有数据证实这一点。因此，我们建议在机器人辅助的慢性卒中损伤训练方面的专业知识的基础上，评估预测模型的潜力，这些模型将选择有更好机会获得功能改善的患者。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，以及由经颅磁刺激确定的皮质脊髓束有效性的衡量标准。连通性的功能和解剖指标，以及可塑性相关的基因都是需要测试的二级生物标志物。中风后的时间是另一个有希望进行测试的指标，对临床实践具有很强的意义。我们还提出了第二个机制假说，即非适应性跨大脑皮质抑制将通过干预而改变。具体目标：建立干预后功能和残疾的预测模型。在中风后6个月，测量12周的机器人辅助治疗和过渡到任务训练的效果。建立一个模型，预测干预后Fugl-Meyer的临床有意义的变化，并测试模型的有效性。通过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大脑半球间抑制的影响。有中度到重度手臂功能障碍(根据Fugl-Meyer评分，7到45分)持续6个月的患者，医学上稳定，没有肌挛缩或其他会影响训练的损伤，将被纳入其中。96名受试者将被分配到一个单一的研究小组，采用多基线方法，以确保措施的稳定性。评估将由一名对预测模型一无所知的考官进行。第一个四周的训练将包括手腕机器人训练课程，第二个四周将包括平面机器人训练课程，第三个四周将包括交替的腕部和平面训练课程。机器人培训课程将持续45分钟，然后是15分钟的功能相关任务培训(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、行动研究手臂测试以及家庭手臂使用的活动监测。训练前和训练后将进行运动学分析。大多数患者将同意接受TMS和MRI。在这些受试者中，大脑半球内抑制将在每次结果测量访问时被确定。磁共振成像将仅在基线期间进行，并将用于确定皮质脊髓束的病变类型、白质完整性和功能连接性。在……结束时 这些目标将为中风后晚期强化手臂治疗的临床决策提供一种方法，并更好地从机制上理解其工作原理。该方法将在整个退伍军人管理局医疗系统和更远的地方传播。