Identifying and Treating Depression in Hemodialysis Patients

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 the investigators' previous work, they 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. Investigators now propose a cross-sectional study (Phase 1) followed by a single-arm clinical trial (Phase 2) 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, anxiety, and quality of life (Quality of Life Questionnaire) in about 1083 patients. Investigators 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 96 patients with confirmed depression who will be assigned to directly observed weekly antidepressant treatment with fluoxetine. 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. Investigators anticipat