Using Latent Variables And Directly Observed Treatment To Improve The Diagnosis And Management of Depression Among Hemodialysis Patients

抑郁症存在于约20-30%的血液透析患者中，并且与 发病率和死亡率。然而，抑郁症的诊断和治疗不足， 在透析患者中。这部分是由于抑郁症之间的重叠 症状（如食欲改变、睡眠困难、感到疲倦）和与 血液透析患者的持续代谢紊乱（例如恶心、夜间 痉挛，治疗后感觉被冲洗掉）。抑郁症和 症状和透析相关的并发症使其难以诊断， 来治疗抑郁症此外，抗抑郁药物的处方可能会增加 已经很高的药丸负担，并导致依从性差。此外，证据基础 对血液透析患者抑郁症的治疗指导作用有限。在我们以前 工作中，我们开发了使用潜变量和结构方程模型的方法， 孤立抑郁症状。其他研究人员已经直接证明， 观察治疗可提高结核病和艾滋病毒治疗的有效性。 我们现在提出一项横断面研究，随后是一项17岁的随机对照试验。 透析设施。这项横断面研究将涉及对抑郁症患者的评估。 症状（使用PHQ-9筛查仪器）以及透析相关 并发症然后，我们将使用结构方程模型来开发和验证一个 血液透析特异性PHQ-9（hdPHQ-9）将隔离抑郁症状。审判 将涉及216名确诊为抑郁症的患者，他们将被随机分配到（a） 直接观察的每周一次氟西汀抗抑郁治疗或（B）转诊至他们的 肾科医生、他们的初级保健医生或附近的心理健康提供者。的 试验的主要结果是12周时抑郁症的缓解。审判 结果也将用于比较PHQ-9和hdPHQ-9的响应性。 我们预计，hdPHQ-9将是一个有效的和响应的工具，将隔离 血液透析患者的抑郁症状，并最终改善筛查， 抑郁症的诊断我们还希望每周直接观察氟西汀 治疗将是治疗血液透析患者抑郁症的有效方法。 拟议项目的创新特点包括使用潜变量来解决 重叠，长效抗抑郁药每周给药，直接观察 治疗和严格的随机对照试验设计。该项目有 不仅可以改善抑郁症的诊断和管理， 而且还能改善血液透析患者的发病率和死亡率。而且 可以作为未来研究的模型，在重叠的医学疾病中分离症状。 条件

Depression is present in about 20-30% of hemodialysis patients and is associated with morbidity and mortality. However, depression is inadequately diagnosed and treated among dialysis patients. This is due in part to the overlap between depressive symptoms (e.g. appetite change, trouble sleeping, feeling tired) and symptoms related to persistent metabolic derangements in hemodialysis patients (e.g. nausea, nocturnal cramps, feeling washed out after treatment). The overlap between depressive symptoms and dialysis-related complications makes it difficult to diagnose and therefore to treat depression. In addition, prescription of antidepressant medication may increase an already high pill burden and result in poor adherence. Moreover, the evidence base to guide depression treatment among hemodialysis patients is limited. In our previous work, we developed methods to use latent variables and structural equation modeling to isolate depressive symptoms. Other investigators have demonstrated that directly observed treatment enhances the effectiveness of tuberculosis and HIV treatment. We now propose a cross-sectional study followed by a randomized controlled trial at 17 dialysis facilities. The cross-sectional study will involve assessments of depressive symptoms (using the PHQ-9 screening instrument) as well as dialysis-related complications. We will then use structural equation modeling to develop and validate a hemodialysis-specific PHQ-9 (hdPHQ-9) that will isolate depressive symptoms. The trial will involve 216 patients with confirmed depression who will be randomly assigned to (a) directly observed weekly antidepressant treatment with fluoxetine or (b) referral to their nephrologists, their primary care physicians, or nearby mental health providers. The primary outcome of the trial will be remission of depression at 12 weeks. The trial results will also be used to compare the responsiveness of the PHQ-9 and the hdPHQ-9. We anticipate that the hdPHQ-9 will be a valid and responsive instrument that will isolate depressive symptoms in hemodialysis patients and ultimately improve the screening and diagnosis of depression. We also expect that directly observed weekly fluoxetine treatment will be an effective way to manage depression among hemodialysis patients. Innovative features of the proposed project include the use of latent variables to address overlap, administration of a long acting weekly antidepressant, directly observed treatment, and a rigorous randomized controlled trial design. The project has the potential not only to improve the diagnosis and management of depression among hemodialysis patients but also to improve their morbidity and mortality. Furthermore, it may serve as a model for future studies to isolate symptoms among overlapping medical conditions.