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

基本信息

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
项目类别：
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

项目摘要

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）此外，尽管存在差异，但非创伤暴露样本中的 CVD 风险升高有关。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，很少有研究直接检查了这些协会中的性别差异。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。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。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 年我们将利用现有的资源，对创伤后的精神科和心血管诊断进行跟踪。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 事件的预测因素在目标 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”的表现鉴于精神疾病和心血管疾病的性别差异，创伤后的精神病理学具有性别特异性。在目标 2 中，将检查与 CVD 事件风险相关的精神病理学概况。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增加 CVD 风险的精神疾病组合。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。