Identifying Cardiotoxic Manifestations of Posttraumatic Psychopathology: A Population-based Longitudinal Investigation

识别创伤后精神病理学的心脏毒性表现：基于人群的纵向调查

• 批准号: 10534712
• 负责人: Jaimie L. Gradus
• 金额: $ 62.91万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-12-15 至 2025-11-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10534712
• 关键词: 18 year old; Accidents; Accounting; Address; Affect; Anxiety; Automobile Driving; Big Data; Cardiotoxicity; Cardiovascular Diseases; Cardiovascular system; Characteristics; Complex; Computerized Medical Record; Data; Data Science; Data Sources; Databases; Development; Diagnosis; Disease Outcome; Electronic Health Record; Event; Exposure to; Future; Heart Diseases; Heart failure; Hypertension; Incidence; Individual; Intervention; Investigation; Knowledge; Link; Literature; Machine Learning; Measures; Mental Depression; Mental disorders; Myocardial Infarction; National Heart, Lung, and Blood Institute; Outcome; Pattern; Persons; Population; Population-Based Registry; Post-Traumatic Stress Disorders; Prevalence; Prevention; Psychopathology; Public Health; Registries; Reporting; Research; Resources; Risk; Risk Factors; Role; Sampling; Sex Differences; Smoking; Stroke; Substance abuse problem; Techniques; Time; Trauma; United States; Woman; Work; assault; cardiovascular disorder prevention; cardiovascular disorder risk; cardiovascular health; cardiovascular risk factor; cohort; comorbidity; data registry; follow-up; improved; men; mortality; novel; novel strategies; population based; primary outcome; prospective; psychiatric comorbidity; psychologic; resilience; risk prediction model; secondary outcome; sex; substance misuse; trauma exposure; traumatic event; venous thromboembolism; virtual; working group

PROJECT SUMMARY Trauma affects the vast majority of people (50-89%) during their lifetime, and it can have lasting impacts on not only psychiatric but also cardiovascular health. Both trauma exposure and posttraumatic stress disorder (PTSD)—the quintessential trauma-related psychiatric disorder—have been linked prospectively to increased risk of developing a range of cardiovascular outcomes. However, as described in a recent NHLBI Working Group report, critical knowledge gaps must be addressed before trauma or its psychiatric sequelae might be novel targets for reducing cardiovascular disease (CVD) risk. Indeed, our current understanding is limited by a disproportionate focus on PTSD when examining subsequent CVD risk in trauma-exposed individuals. Posttraumatic psychopathology manifests in heterogeneous ways (e.g., depression, anxiety, substance abuse) that have been linked to elevated CVD risk in non-trauma-exposed samples. Further, despite differences in the prevalence and manifestations of posttraumatic psychopathology and CVD in men and women, few studies have directly examined sex differences in these associations. The field's ability to investigate these questions has been hampered by a lack of rigorous measures of trauma exposure and posttraumatic psychopathology in most existing electronic medical record databases, which have extensive data on CVD outcomes. This study will address these knowledge gaps by harnessing a unique prospective, population-based trauma cohort in order to characterize “cardiotoxic” manifestations of posttraumatic psychopathology in men and women. This trauma cohort was created using Danish electronic health registry (EHR) data as part of R01MH110453 (PI: Gradus), and it identified over 1.4 million individuals exposed to a trauma between 1994 and 2016. This established data source includes rich, highly valid, and complete registry-based data with up to 25 years of follow-up on psychiatric and cardiovascular diagnoses following trauma. We will use this existing resource, restricted to persons age 18 years and older with no prior CVD events (n = 1,068,100), to comprehensively examine posttraumatic psychopathology as a predictor of incident CVD. In Aim 1, we will harness cutting edge, novel data science techniques (machine learning) to identify particularly “cardiotoxic” manifestations of psychopathology after trauma. Given sex differences in psychiatric disorders and CVD, sex-specific psychopathology profiles associated with incident CVD risk will be examined in stratified analyses. In Aim 2, we will use traditional analyses to quantify discovered psychiatric predictors and unanticipated/novel psychiatric comorbidity profiles associated with CVD risk in the machine learning analyses, as well as a priori literature-based combinations of psychiatric disorders that increase CVD risk. This EHR-based trauma cohort provides a unique opportunity to consider comprehensively the constellation of posttraumatic psychopathology that may predict CVD, and the results of this study will be used to ultimately inform the development of targeted CVD prevention efforts in trauma-exposed populations.

项目概要 绝大多数人（50-89%）一生中都会受到创伤的影响，并且它会对非创伤性患者产生持久影响。 不仅是精神疾病，还有心血管健康。创伤暴露和创伤后应激障碍 （PTSD）——典型的创伤相关精神疾病——已被前瞻性地与增加的 发生一系列心血管结局的风险。然而，正如最近的 NHLBI 工作中所述 小组报告，在创伤或其精神后遗症可能发生之前必须解决关键的知识差距 降低心血管疾病（CVD）风险的新目标。事实上，我们目前的理解受到以下因素的限制： 在检查遭受创伤的个体随后的 CVD 风险时，过分关注 PTSD。 创伤后精神病理学以不同的方式表现（例如抑郁、焦虑、药物滥用） 与非外伤暴露样本中 CVD 风险升高有关。此外，尽管存在差异 男性和女性创伤后精神病理学和心血管疾病的患病率和表现，很少有研究 直接研究了这些关联中的性别差异。该领域调查这些问题的能力 由于缺乏严格的创伤暴露和创伤后精神病理学测量措施而受到阻碍 大多数现有的电子病历数据库都包含有关 CVD 结果的大量数据。这项研究 将通过利用独特的前瞻性、基于人群的创伤队列来解决这些知识差距 为了描述男性和女性创伤后精神病理学的“心脏毒性”表现。这 创伤队列是使用丹麦电子健康登记 (EHR) 数据创建的，作为 R01MH110453 的一部分（PI： Gradus），它确定了 1994 年至 2016 年间超过 140 万人遭受过创伤。 已建立的数据源包括丰富、高度有效且完整的基于注册表的数据，历史长达 25 年 创伤后精神和心血管诊断的随访。我们将利用现有的资源， 仅限于 18 岁及以上且既往无 CVD 事件的人 (n = 1,068,100)，以全面 检查创伤后精神病理学作为 CVD 事件的预测因子。在目标 1 中，我们将利用尖端技术， 新颖的数据科学技术（机器学习）来识别特别“心脏毒性”的表现 创伤后的精神病理学。鉴于精神疾病和心血管疾病的性别差异，性别特异性 与CVD风险相关的精神病理学概况将通过分层分析进行检查。在目标 2 中， 我们将使用传统分析来量化发现的精神预测因素和意外/新颖的因素 机器学习分析中与 CVD 风险相关的精神共病概况以及先验 基于文献的精神疾病组合会增加 CVD 风险。这个基于 EHR 的创伤队列 提供了一个独特的机会来全面考虑创伤后精神病理学的星座 可能会预测 CVD，这项研究的结果将最终用于指导 CVD 的开发 针对遭受创伤的人群开展有针对性的 CVD 预防工作。