Abstract

Unraveling specific dimensions of depressive symptoms may help to improve screening and treatment in dialysis patients. We aimed to identify the best-fitting factorial structure for the Beck Depression Inventory-II (BDI) in dialysis patients and to assess the relation of these structure dimensions with quality of life (QoL), hospitalization, and mortality. This prospective study included chronic dialysis patients from 10 dialysis centers in five hospitals between 2012 and 2017. Dimensions of depressive symptoms within the BDI were analyzed using confirmatory factor analysis. To investigate the clinical impact of these dimensions, the associations between symptom dimensions and QoL, hospitalization rate, and mortality were investigated using logistic, Poisson, and Cox proportional hazard regression models. Multivariable regression models included demographic, social, and clinical variables. In total, 687 dialysis patients were included. The factor model that included a general and a somatic factor provided the best-fitting structure of the BDI-II. Only the somatic dimension scores were associated with all-cause mortality (hazard ratio of 1.7 [1.2-2.5], p < .007) in the multivariable model. All dimensions were associated with increased hospitalization rate and reduced QoL. The somatic dimension of the BDI-II in dialysis patients was associated with all-cause mortality, increased hospitalization rate, and reduced QoL. Other dimensions were associated with hospitalization rate and decreased QoL. These findings show that symptom dimensions of depression have differential association with adverse clinical outcomes. Future studies should take symptom dimensions into account when investigating depression-related pathways, screening, and treatment effects in dialysis patients.

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