Depression Symptoms in Haemodialysis Patients Predict All-Cause Mortality but Not Kidney Transplantation: A Cause-Specific Outcome Analysis

Abstract

Background

Depression is common in haemodialysis (HD) patients and associated with poor outcomes.

Purpose

To evaluate whether depression symptoms predict survival and transplantation in a large sample of haemodialysis patients using cause-specific survival models.

Methods

Survival data was collected between April 2013 and November 2015, as part of the screening phase of a multicentre randomised placebo-controlled trial of sertraline in HD patients. Depression was measured using the Beck Depression Inventory-II (BDI-II) and the Patient Health Questionnaire-9 (PHQ-9). Demographic and clinical data were collected via a self-report questionnaire and medical records. Competing risk survival analysis involved cause-specific and subdistribution hazard survival models. All models were adjusted for appropriate covariates including comorbidity and C-reactive protein (CRP) in a subanalysis.

Results

Of 707 cases available for analysis, there were 148 deaths. The mean survival time was 787.5 days. Cumulative survival at 12 months was 88.5%. During the study follow-up period, there were 92 transplants. The cumulative transplant event rate at 12 months was 7.8%. In separate adjusted models, depression symptoms predicted mortality (BDI-II HR = 1.03 95% CI 1.01, 1.04; PHQ-9 HR = 1.04 95% CI 1.01, 1.06). With respect to screening cut-off scores, a PHQ-9 ≥ 10 was associated with mortality (HR = 1.51 95% CI 1.01, 2.19) but not a BDI-II ≥ 16. Depression symptoms were not associated with time to transplantation in either cause-specific or subdistribution model.

Conclusions

Consistent with past findings in HD patients, depression symptoms predicted survival but were not associated with kidney transplantation. Suitable treatments for depression need further evaluation, and their impact upon quality of life and clinical outcomes determined.

Trial Registration Number (ISRCTN06146268).

from # All Medicine by Alexandros G. Sfakianakis via Alexandros G.Sfakianakis on Inoreader http://ift.tt/2tXC2NR
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