Depression and Heart Failure Disease Progression

描述（由申请人提供）：有超过500万美国人患有心力衰竭（HF），每年还有67万新病例被诊断出来。心衰是一种典型的不稳定状态，是医疗保险人群中最昂贵的诊断，也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b型利钠肽（BNP）的短期波动上。患者自我管理行为对于最小化心衰疾病不稳定性非常重要。心衰常伴有抑郁，抑郁症状的升高与不良临床结果的显著增加有关。无论是抑郁型还是非抑郁型心衰患者，抑郁症状的恶化都标志着心血管住院或死亡的风险显著增加。尽管风险与抑郁症状相关，但其与心衰病程恶化和不良临床结果的关联性质尚不清楚。越来越多的证据表明，抑郁症状与心衰疾病加速进展之间的关联可能涉及多种行为和病理生理途径。本研究对220例伴有收缩功能障碍的心衰患者进行了一项创新性的前瞻性生物行为监测研究，旨在探讨抑郁症状及其生物行为表现与心衰疾病恶化之间的关系。使用新开发的家庭监测生物技术，我们建议在16周的时间内通过每周BNP评估来跟踪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步监测进行评估。每周一次的生物行为监测将以全面的基线和4个月的抑郁、心衰疾病严重程度以及与抑郁症状存在相关并与心衰疾病进展相关的病理生理机制评估为框架。临床结果也将在随后的2年随访期间进行评估。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，将服务于

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.