Secondary Analysis of Existing Databases in Traumatic Brain Injury to Explore Outcomes Relevant to Medical Rehabilitation

疼痛是轻度创伤性脑损伤(MTBI)患者最常见的并发症之一。 对这一人群中疼痛或治疗的纵向病程了解甚少。尽管 在临床护理中，普遍使用疼痛评分作为第五个生命体征，但很少有人尝试利用 基于通常收集的疼痛数据，并实际定义这些分数随时间或结合的意义 以及治疗轨迹。因此，越来越多的mTBI和疼痛患者患有功能性脑损伤。 残疾、医疗保健利用率增加、家庭功能受到挑战，以及延迟重返工作岗位。vt.给出 伊拉克和阿富汗战争退伍军人(IAV)中mTBI的高患病率和临床可获得性 退伍军人事务部(VA)、IAV和mTBI的重点管理数据是独一无二的 来研究这些重要的问题。 我们的跨学科团队将汇编来自以前资助的项目的数据，以：确定模式(轨迹) 在IAV与mTBI的队列中，对VA护理的前五年的疼痛评分和疼痛治疗进行评估，并确定 疼痛和治疗轨迹以及包括自杀在内的不良后果之间的关系 构思/企图、服药过量、事故和药物使用障碍的发展。 我们将使用潜在生长混合建模技术来识别与疼痛相关的不同轨迹 评分和潜在类别模型，以确定疼痛治疗后5年内的独特轨迹 进入退伍军人管理局。然后我们将确定在接下来的两年窗口期间不良事件的发生率 5年的轨迹发展周期因疼痛评分和治疗轨迹类别而异。我们将使用 用COX回归模型确定疼痛与治疗轨迹和不良反应的独立效应 结果，控制年龄、性别、种族/民族和其他共病情况。 结果将提供可用于通过确定更有效和次优的数据来为最佳实践提供参考的数据 对于同时经历mTBI和疼痛的个人的治疗方法。更重要的是，这将是 这是首批实现疼痛生命体征临床益处的研究之一。鉴于不断增加的 在临床护理过程中开发的管理数据的可用性，该项目中使用的方法可以 翻译成在其他临床环境中使用。此外，拟议的项目为更多 有针对性的研究，可以检查患者疼痛的纵向体验和治疗 透视。由此产生的数据还将导致预测模型的开发，这些模型可以用于 为具有特定疼痛表型的mTBI患者确定有效和次优的治疗方法 超越退伍军人事务部的不同护理设置，建立证据以推进现有的临床实践指南 用于治疗mTBI患者的疼痛。

Pain is one of the most common comorbidities among individuals with mild traumatic brain injuries (mTBI), yet little has been done to understand the longitudinal course of pain or treatment in this population. Despite the ubiquitous use of pain scores as the fifth vital sign in clinical care, there have been few attempts to capitalize on commonly gathered pain data and to actually define the meaning of these scores over time or in conjunction with treatment trajectories. As a result, a growing number of individuals with mTBI and pain suffer functional disability, increased healthcare utilization, challenges to family functioning, and delayed return to work. Given the high prevalence of mTBI in Iraq and Afghanistan war Veterans (IAV), and the availability of clinically focused administrative data from the Department of Veterans Affairs (VA), IAV with mTBI are a unique population to examine these important issues. Our transdisciplinary team will compile data from a previously funded project to: Identify patterns (trajectories) of pain scores and pain treatment during the first five years of VA care in an IAV cohort with mTBI, and identify the relationships among pain and treatment trajectories, and adverse outcomes including suicidal ideation/attempt, overdose, accidents, and development of substance use disorder. We will use the latent growth mixture modeling technique to identify distinct trajectories associated with pain scores and latent class models to identify unique trajectories of pain treatment over the 5-year period after entering VA care. We will then determine if the incidence of adverse events during the 2-year window following the 5-year trajectory development period differs by pain score and treatment trajectory classes. We will use Cox regression models to determine the independent effects of pain and treatment trajectories and adverse outcomes, controlling for age, gender, race/ethnicity, and other comorbid conditions. Results will provide data that can be used to inform best practices by identifying more effective and suboptimal treatment approaches for individuals who experience comorbid mTBI and pain. More importantly, this will be one of the first studies to fulfill the promise of clinical benefit for the pain vital sign. Given the increasing availability of administrative data developed in the course of clinical care, methods used in this project can be translated for use in other clinical settings. Moreover, the proposed project provides the foundation for more focused studies that can examine the longitudinal experience and treatment of pain from the patient's perspective. The resulting data will also lead to the development of predictive models that can be used to identify effective and suboptimal treatment approaches for mTBI patients with specific pain phenotypes across different settings of care beyond the VA, establishing evidence to advance existing clinical practice guidelines for treating pain in individuals with mTBI.