Evidence mapPaperPMID 40926186Full record

ArticleRenal failure2025

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

Xiaoyu Chen, Peipei Han, Zhenwen Liang, Chen Yu, Kun Zhang, Siyi Zhu, Weijia Li, Yifan Xue, Qi Guo

Abstract readMulticenter Study
In one paragraph

Article in Renal failure, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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3 · Its place in the literature

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2 citing papers in PubMed.

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5 · Who and what money

Authors and funding

9 authors.

Xiaoyu ChenDepartment of Rehabilitation Medicine, Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Shanghai, China.
Peipei HanDepartment of Rehabilitation Medicine, Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Shanghai, China.
Zhenwen LiangDepartment of Rehabilitation Medicine, Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Shanghai, China.
Chen YuDepartment of Nephrology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China.
Kun ZhangDepartment of Nephrology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China.
Siyi ZhuDepartment of Rehabilitation Medicine, Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Shanghai, China.
Weijia LiDepartment of Rehabilitation Medicine, Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Shanghai, China.
Yifan XueDepartment of Rehabilitation Medicine, Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Shanghai, China.
Qi GuoDepartment of Rehabilitation Medicine, Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDepression is a common mental disorder in hemodialysis patients. The present study aimed to identify subgroups of patients receiving hemodialysis based on depression and explore the influencing factors in a multicenter hemodialysis population in China.

methodsA total of 1,090 hemodialysis patients (682 men, mean aged 61.5 ± 12.6 years) from 7 facilities in Shanghai of China during 2020-2023. Depression was assessed by Patient Health Questionnaire 9 (PHQ-9). Latent class analysis (LCA) was performed to identify homogeneous groups of depressive symptoms. Analysis of variance and chi-square test were performed to establish class-dependent differences in depression severity. Multinomial logistic regression revealed the associations and related factors on most probable class.

resultsThree latent classes were identified: High depressive symptoms (Class 1,

conclusionsThe current study provides evidence for the heterogeneity of depression severity. A better understanding of depression risk factor profiles could help develop targeted prevention and intervention programs for the hemodialysis population.

Indexed as

DepressionKidney Failure, ChronicRenal DialysisAdultAgedBody Mass IndexChinaCross-Sectional StudiesFemaleHumansLatent Class AnalysisLogistic ModelsMaleMiddle AgedRisk FactorsSeverity of Illness IndexDepressionhemodialysis patientslatent class analysisrisk factors

Identifiers

PMID40926186
PMCPMC12422040

What Socratic holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.