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

对现有的创伤性脑损伤数据库进行二次分析，探索与医疗康复相关的结果

• 批准号: 9173126
• 负责人: Mary Jo Pugh
• 金额: $ 17.17万
• 依托单位: FOUNDATION FOR ADVANCING VETERANS' HLTH
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9173126
• 关键词: Accidents; Address; Adverse event; Affect; Afghanistan; Age; Analgesics; Anti-Inflammatory Agents; Anti-inflammatory; Anticonvulsants; Antidepressive Agents; Back; Brain Injuries; Caring; Clinic; Clinic Visits; Clinical; Clinical Data; Clinical Practice Guideline; Collection; Communities; Comorbidity; Complementary and alternative medicine; Data; Data Set; Databases; Development; Dizziness; Electronic Health Record; Epidemiology; Ethnic Origin; Family; Feeling suicidal; Foundations; Funding; Future; Gender; Goals; Growth; Headache; Health Care Costs; High Prevalence; Home environment; Impaired cognition; Incidence; Individual; Intercept; Iraq; Lead; Light; Measures; Methods; Migraine; Military Personnel; Minor; Modeling; Muscle relaxants; Neck Pain; Opioid; Outcome; Outcomes Research; Overdose; Pain; Pain Clinics; Pain management; Patients; Pattern; Pharmaceutical Preparations; Pharmacy facility; Phenotype; Physical therapy; Population; Positioning Attribute; Post-Traumatic Stress Disorders; Race; Rehabilitation therapy; Research; Services; Skeletal Muscle; Statistical Models; Substance Use Disorder; Symptoms; Techniques; Testing; Time; Translating; Trauma; Traumatic Brain Injury; Variant; Veterans; War; Work; addiction; adverse outcome; arthritic pain; chronic pain; clinical care; cohort; experience; functional disability; health care service utilization; innovation; longitudinal course; mild traumatic brain injury; mind control; pain symptom; predictive modeling; rate of change

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.

疼痛是轻度创伤性脑损伤 (mTBI) 患者最常见的合并症之一，但 我们几乎没有采取任何措施来了解这一人群的疼痛或治疗的纵向过程。尽管 在临床护理中普遍使用疼痛评分作为第五生命体征，但很少有人尝试利用它 根据通常收集的疼痛数据，并随着时间的推移或结合起来实际定义这些分数的含义 与治疗轨迹。因此，越来越多患有 mTBI 和疼痛的人出现功能障碍 残疾、医疗保健利用率增加、家庭功能面临挑战以及延迟重返工作岗位。给定 伊拉克和阿富汗战争退伍军人 (IAV) 中 mTBI 的高患病率以及临床治疗的可用性 来自退伍军人事务部 (VA) 的集中管理数据，带有 mTBI 的 IAV 是独一无二的 人口来研究这些重要问题。 我们的跨学科团队将从之前资助的项目中收集数据，以： 识别模式（轨迹） 在患有 mTBI 的 IAV 队列中，评估 VA 护理前五年的疼痛评分和疼痛治疗，并确定 疼痛和治疗轨迹之间的关系，以及包括自杀在内的不良后果 意念/尝试、服药过量、事故以及物质使用障碍的发展。 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 年期间的独特轨迹 进入 VA 护理。然后，我们将确定以下 2 年窗口内不良事件的发生率： 5 年轨迹开发期因疼痛评分和治疗轨迹类别而异。我们将使用 Cox 回归模型确定疼痛和治疗轨迹以及不良反应的独立影响 结果，控制年龄、性别、种族/民族和其他合并症。 结果将提供可用于通过识别更有效和次优的最佳实践提供信息的数据 针对患有 mTBI 和疼痛共病的个体的治疗方法。更重要的是，这将是 这是首批实现疼痛生命体征临床获益承诺的研究之一。鉴于日益增加的 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 翻译用于其他临床环境。此外，拟议的项目为更多 重点研究可以检查患者的纵向疼痛经历和治疗 看法。由此产生的数据还将导致预测模型的开发，该模型可用于 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 VA 之外的不同护理环境，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。