Depression and Heart Failure Disease Progression

有超过500万美国人患有心力衰竭（HF），另有670，000名新患者 每年都有确诊病例。HF是一种典型的不稳定状态， 医疗保险人群中昂贵的诊断，是住院治疗的最常见原因。 HF疾病的不稳定性反映在HF疾病生物标志物的短期波动中， B型利钠肽（BNP）。患者自我管理行为对于 最小化HF疾病不稳定性。抑郁症通常与HF共病， 抑郁症状与不良临床结果的显著增加相关。为 抑郁和非抑郁HF患者，抑郁症状恶化标志着 心血管住院或死亡的风险显著增加。尽管有风险 与抑郁症状相关，其与HF恶化相关的性质 疾病轨迹和不良临床结果知之甚少。 越来越多的证据表明，抑郁症状与 加速的HF疾病进展可能涉及多种行为和病理生理学 途径。本申请提出了一个创新的，前瞻性的生物行为监测研究 220名患有收缩功能障碍的HF患者，旨在解决如何 抑郁症状及其生物行为表现与HF恶化有关 疾病利用新开发的家庭监测生物技术，我们建议跟踪 在16周期间，使用BNP每周评估HF疾病严重程度的波动。 抑郁症状和HF相关的健康行为也将每周通过 同时监测。这种每周生物行为监测将由全面的 基线和4个月的抑郁、HF疾病严重程度和病理生理学评估 与抑郁症状的存在有关的机制， HF疾病的进展。临床结果也将在随后的2- 年随访期。这项拟议中的研究将创建一个独特的数据结构， 使用当代统计方法，将有助于阐明因果关系之间的联系， 抑郁症状，自我管理健康行为，病理生理过程， HF疾病进展和临床结局。研究结果预计将产生 在我们理解为什么抑郁症状可能特别 在HF的存在下是有害的，并将有助于为未来临床试验的设计提供信息。

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.