Longitudinal Changes in Gait and Ankle Function in Youth with Charcot-Marie-Tooth Disease

项目摘要/摘要 Charcot-Marie-Tooth病(CMT)是最常见的遗传性周围神经病，但仍是一种罕见的疾病 这种疾病在美国影响着大约15万人。肌萎缩侧索硬化症导致远端肌肉无力和 肌挛缩症，影响行走能力。渐进性的行走能力丧失是导致 CMT患者的生活质量降低。因为疾病的发展是高度异质性的，所以很难 来预测一个人的步态将如何随着时间的推移而变化。这项研究的长期目标是了解 青少年CMT患者在步态过程中踝关节功能变化的自然病史能够预测疾病 个别患者的进展情况。当前项目的目标是：1)获得后续(纵向)步态分析 关于先前进行步态分析研究的患者的数据，以及2)确定患者和临床特征，包括 功能步态表型，预测步态功能随时间恶化的模式。我们假设 通过考虑基于踝关节的功能性步态表型可以预测行走能力的变化 运动学和动力学，以及临床特征，如CMT类型、性别、年龄、活动范围和 力量。我们以前研究过CMT患者的步态与年龄之间的关系，但这项研究是有限的 主要是通过使用横断面数据。来自纵向调查的小样本的初步结果 评估表明，可能存在横断面数据没有捕捉到的变化模式。 这项研究将收集有过步态分析的CMT患者的后续步态分析数据 研究以创建更大的纵向数据集。这些纵向数据将被用来确定 功能性步态表型可以改善青年和患有功能性步态障碍的年轻人未来行走能力的预测 CMT。更好地理解和预测个体患者预期的步态变化是 既要改善对个别患者的护理，也要能够评估新出现的 未来临床试验中的治疗方法。

PROJECT SUMMARY / ABSTRACT Charcot-Marie-Tooth disease (CMT) is the most commonly inherited peripheral neuropathy but is still a rare disease affecting approximately 150,000 people in the United States. CMT causes distal muscle weakness and contracture, impairing the ability to walk. Progressive loss of walking ability is the most significant contributor to reduced quality of life in persons with CMT. Because disease progression is highly heterogeneous, it is difficult to predict how an individual’s gait will change over time. The long-term goal of this research is to understand the natural history of changes in ankle function during gait in youth with CMT to be able to predict disease progression for individual patients. The current project aims to 1) obtain follow-up (longitudinal) gait analysis data on patients with prior gait analysis studies and 2) identify patient and clinical characteristics, including functional gait phenotypes, that predict patterns of deterioration of gait function over time. We hypothesize that changes in walking ability can be predicted by considering functional gait phenotypes based on ankle kinematics and kinetics in addition to clinical characteristics like CMT type, sex, age, range of motion, and strength. We have previously studied the association between gait and age in CMT, but this research is limited by the use of primarily cross-sectional data. Preliminary results from a small sample of longitudinal assessments suggest that there may be patterns of change that are not captured by the cross-sectional data. This study will collect follow-up gait analysis data on patients with CMT who have had prior gait analysis studies to create a larger longitudinal data set. These longitudinal data will be used to determine whether functional gait phenotypes can improve the prediction of future walking ability in youth and young adults with CMT. Better understanding and being able to predict the changes in gait expected for individual patients is important both to improve care for individual patients and also to be able to evaluate the effects of emerging treatments in future clinical trials.