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Latent class analysis of depression among maintenance hemodialysis patients in China: a multicenter cross-sectional

Xiaoyu Chen1, Peipei Han1, Zhenwen Liang1

  • 1Department of Rehabilitation Medicine, Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Shanghai, China.

Renal Failure
|September 9, 2025
PubMed

Insights

Depression is common in hemodialysis patients. This study identified three depression groups and found age, BMI, falls, malnutrition, and comorbidities influence depression severity in this population.

Area of Science:

  • Nephrology
  • Psychiatry
  • Public Health

Background:

  • Depression is a prevalent mental health issue among patients undergoing hemodialysis.
  • Identifying distinct depression profiles is crucial for understanding patient needs in this population.

Purpose of the Study:

  • To identify subgroups of hemodialysis patients based on depression severity.
  • To explore factors associated with different depression levels in a Chinese hemodialysis cohort.

Main Methods:

  • Latent class analysis (LCA) was used to categorize 1,090 hemodialysis patients into distinct depression groups.
  • Patient Health Questionnaire 9 (PHQ-9) assessed depression symptoms.
  • Multinomial logistic regression identified factors associated with depression severity.

Main Results:

  • Three classes emerged: High (11.9%), Moderate (38.9%), and Low (49.2%) depressive symptoms.
  • Age, BMI, fall history, malnutrition, and Charlson Comorbidity Index (CCI) were significant factors influencing depression in higher symptom groups.

Conclusions:

  • Depression severity is heterogeneous among hemodialysis patients.
  • Understanding risk factor profiles can guide targeted interventions for depression in hemodialysis patients.
Abstract

Keywords:
Depressionhemodialysis patientslatent class analysisrisk factors

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