Depression and Heart Failure Disease Progression

描述(由申请人提供)：美国有500多万人患有心力衰竭(HF)，每年新增67万例确诊病例。心力衰竭是一种典型的不稳定情况，是医疗保险人群中最昂贵的诊断，也是最常见的住院原因。心力衰竭的不稳定性反映在心力衰竭生物标志物B型利钠肽(BNP)的短期波动上。患者的自我管理行为对于最大限度地减少心力衰竭的不稳定性非常重要。抑郁通常与心力衰竭并存，抑郁症状的增加与不良临床结果的显著增加有关。对于抑郁和非抑郁的心衰患者，抑郁症状的恶化标志着心血管住院或死亡的风险显著增加。尽管与抑郁症状相关的风险，但它们与恶化的心衰疾病轨迹和不良临床结果的关系的本质尚不清楚。越来越多的证据表明，抑郁症状和心力衰竭加速进展之间的联系可能涉及多种行为和病理生理途径。这项应用提出了一项针对220名患有收缩功能障碍的心力衰竭患者的创新的、前瞻性的生物行为监测研究，旨在解决抑郁症状及其生物行为表现如何与恶化的心力衰竭疾病有关的问题。利用最新开发的家庭监测生物技术，我们建议在16周的时间里，通过每周评估BNP来追踪心力衰竭严重程度的波动。抑郁症状和与心力衰竭相关的健康行为也将通过同步监测每周进行评估。这项每周的生物行为监测将通过对抑郁、心力衰竭严重程度和与抑郁症状的存在相关并与心力衰竭的进展有关的病理生理机制的全面基线和4个月的评估来确定。临床结果也将在随后的两年随访期内进行评估。拟议的研究将创建一个独特的数据结构，使我们能够使用当代统计方法，这将有助于 阐明抑郁症状、自我管理健康行为、病理生理过程与心力衰竭疾病进展和临床结果之间的因果关系。这项研究结果有望在我们理解为什么抑郁症状在存在HF时可能特别有害方面取得重要进展，并将有助于为未来临床试验的设计提供信息。

DESCRIPTION (provided by applicant): There are over five million Americans living with heart failure (HF), and another 670,000 new cases being diagnosed each year. HF is a characteristically unstable condition that is the most costly diagnosis in the Medicare population and is the most common cause for hospitalization. The instability of HF disease is reflected in short-term fluctuations of the HF disease biomarker, B-Type Natriuretic Peptide (BNP). Patient self-management behaviors are important for minimizing HF disease instability. Depression is often comorbid with HF, and elevated depressive symptoms are associated with a marked increase in adverse clinical outcomes. For both depressed and non-depressed HF patients, worsening depressive symptoms mark a substantially increased risk of cardiovascular hospitalization or death. Despite the risk associated with depressive symptoms, the nature of their association with a worsening HF disease trajectory and adverse clinical outcomes is poorly understood. Converging evidence suggests that the association between depressive symptoms and accelerated HF disease progression may involve multiple behavioral and pathophysiological pathways. This application proposes an innovative, prospective bio-behavioral monitoring study of 220 HF patients with systolic dysfunction that is designed to address the issue of how depressive symptoms and their bio-behavioral manifestations are implicated in worsening HF disease. Using newly developed home-monitoring biotechnology, we propose to track fluctuations in HF disease severity using weekly assessments of BNP over a 16-week period. Symptoms of depression and HF-related health behaviors also will be assessed weekly via concurrent monitoring. This weekly bio-behavioral monitoring will be framed by comprehensive baseline and 4-month assessments of depression, HF disease severity, and pathophysiological mechanisms that have been related to the presence of depressive symptoms and implicated in the progression of HF disease. Clinical outcomes also will be assessed over a subsequent 2- year follow-up period. The proposed study will create a unique data structure that will allow us to use contemporary statistical methods that will serve to elucidate causal associations between depressive symptoms, self-management health behaviors, pathophysiological processes, and HF disease progression and clinical outcomes. The study findings are expected to yield important advances in our understanding of why depressive symptoms may be particularly detrimental in the presence of HF and will help to inform the design of future clinical trials.