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

> **NIH NIH R01** · CASE WESTERN RESERVE UNIVERSITY · 2021 · $233,369

## Abstract

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.

## Key facts

- **NIH application ID:** 10112897
- **Project number:** 5R01DK112905-04
- **Recipient organization:** CASE WESTERN RESERVE UNIVERSITY
- **Principal Investigator:** DOUGLAS D GUNZLER
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $233,369
- **Award type:** 5
- **Project period:** 2017-12-05 → 2022-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10112897

## Citation

> US National Institutes of Health, RePORTER application 10112897, Using Latent Variables And Directly Observed Treatment To Improve The Diagnosis And Management of Depression Among Hemodialysis Patients (5R01DK112905-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10112897. Licensed CC0.

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