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: 10344540
• 负责人: Jaimie L. Gradus
• 金额: $ 70.01万
• 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/10344540
• 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; Event; Exposure to; Future; Health; 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; base; 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.

项目总结