Dynamic Treatment Regimens of Physical Activity for Persons with Osteoarthritis

项目概要/摘要 对影响骨关节炎 (OA) 病程的因素了解有限，阻碍了其发展和 优化策略以减轻疼痛并减缓疾病进展。虽然 OA 是一种机械- 尽管身体活动是最常见的疾病，但关于身体活动的影响仍然存在重要的知识差距 关节结构机械刺激的原因。 OA 疼痛主要是由活动引起的（例如爬楼梯、 步行），但矛盾的是，步行疗法可以减轻疼痛。此外，一定程度的振荡 压缩应力会导致软骨的营养变化，而静态或高速应力会导致分解代谢 回应。考虑到不同类型的活动对关节的影响不同，研究结果不足为奇 体力活动量对 OA 影响的研究得出了相互矛盾的结果。此外，还不确定什么 各种类型的活动可能有利于缓解疼痛或改善功能，而不会造成伤害和加速 疾病进展。该项目的长期目标是促进临床医生和患者的决策 制定更优化的身体活动方案，以缓解疼痛、维持功能表现和减速 骨关节炎的结构损伤。该提案的中心假设是体力活动对 骨关节炎的结果因个体特征而异，例如疾病阶段和 不同类型的活动对 OA 结果有不同的影响。此外，我们假设最佳活动 治疗方案可能会随着患者特征的变化而变化。因此，针对个人的身体活动 需要可调整且符合患者当前特征的治疗方案。我们建议 利用骨关节炎倡议 (OAI) 和多中心骨关节炎研究 (MOST) 队列， 两项针对 OA 的大规模纵向研究，其中包含体力活动数据，客观测量 加速度计，以及广泛的临床、成像和用药历史数据。我们的目标是：1） 描述体力活动类型与膝关节 OA 结构进展的随时间变化的关联，2) 检查针对个人的动态身体活动方案，以减轻膝关节骨关节炎患者的疼痛， 3) 检查针对个人的动态身体活动方案，以实现基于表现的身体活动 膝骨关节炎患者的功能。这项工作的贡献是重大的，因为更好地理解 迫切需要了解身体活动类型和强度如何改善或恶化 OA 的结果。我们的 新颖的分析方法不同于传统的基于身体活动推荐的方法 对人群的平均影响。与以人群为导向的方法不同，这些方法对个人的情况漠不关心 独特的特征，我们针对个人的方法将使我们能够根据情况调整身体活动方案 疾病发生。我们的工作将为不同类型的体育活动提供新的证据，并可以为人们提供信息 更好的OA管理。

PROJECT SUMMARY/ABSTRACT Limited understanding of factors affecting the course of Osteoarthritis (OA) has hampered development and optimization of strategies that would lessen pain and slow disease progression. While OA is a mechanically- driven disease, important knowledge gaps remain regarding the effects of physical activity, the most common reason for mechanical stimulation of joint structures. OA pain is mainly activity-induced (e.g., stair climbing, walking), but paradoxically, walking regimens can reduce pain. Further, certain degrees of oscillating compressive stress cause trophic changes in cartilage, whereas static or high velocity stress causes catabolic responses. Given the contrasting effects of different types of activities on the joint, it is not surprising that studies of the effects of the amount of physical activity on OA have had conflicting results. Further, it is uncertain what types of activity could be beneficial for pain relief or function improvement without causing harm and accelerating disease progression. The long-term goal of this project is to facilitate decision making for clinicians and patients of a more optimal physical activity regimen for pain relief, maintaining functional performance, and decelerating structural damage in osteoarthritis. The central hypothesis of this proposal is that physical activity's influence on osteoarthritis outcomes differs depending on individual characteristics such as the stage of disease and that different types of activity have different effects on OA outcomes. Further, we hypothesize that the optimal activity regimen may evolve as the patient characteristics change. Therefore, a person-specific physical activity regimen that is adjustable and consistent with the patient's current characteristics is needed. We propose to take advantage of the Osteoarthritis Initiative (OAI) and Multicenter Osteoarthritis Study (MOST) cohorts, two large-scale longitudinal studies on OA with data on physical activity, measured objectively by accelerometer, in addition to extensive clinical, imaging, and medication history data. Our aims are: 1) to characterize the time-varying association of physical activity types with knee OA structural progression, 2) to examine a person-specific and dynamic physical activity regimen for pain reduction in persons with knee OA, and 3) to examine a person-specific and dynamic physical activity regimen for performance-based physical function in persons with knee OA. The contribution of this work is significant because a better understanding of how physical activity types and intensity may improve or worsen the outcomes of OA is urgently needed. Our novel analytic approach is a departure from the traditional approaches of physical activity recommendation based on average effect in the population. Unlike population-oriented approaches that were indifferent to an individual's unique characteristics, our person-specific approach will allow us to adjust the physical activity regimen as the disease evolves. Our work will provide new evidence about diverse types of physical activity and could inform better OA management.