Analysis of potential categories of sleep problems in non-dialysis patients with chronic kidney disease

Introduction: Sleep disturbances are highly prevalent among patients with non-dialysis chronic kidney disease (CKD) and are associated with adverse clinical outcomes. However, current research predominantly relies on aggregate scale scores, which may overlook the heterogeneity of sleep symptoms. This study aims to identify distinct latent categories of sleep problems and their influencing factors among patients with non-dialysis CKD using latent class analysis, thereby providing an evidence base for phenotype-specific interventions. Methods: From June to July 2023, a convenience sampling was used to select 405 patients from the Nephrology Department of a tertiary hospital in Hangzhou. Data were collected using a general information questionnaire, the Pittsburgh Sleep Quality Index (PSQI), the Hospital Anxiety and Depression Scale (HADS), the International Restless Legs Syndrome Assessment Scale (IRLS), and a Visual Analog Scale (VAS). Mplus 8.0 was used for latent class analysis, and unordered multinomial logistic regression analysis was performed to evaluate factors associated with the different latent classes. Results: < 0.05). Conclusion: Sleep problems among patients with non-dialysis CKD are heterogeneous. Targeted, class-specific interventions should be developed to improve sleep quality for different patient subgroups.

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Publication Details

Journal
Frontiers in Physiology
Published
2026-04-22
DOI
https://doi.org/10.3389/fphys.2026.1744485
Primary Topic
Sleep and related disorders
Type
article
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article

Analysis of potential categories of sleep problems in non-dialysis patients with chronic kidney disease

Jie Zhou, Chunxiang Huang, Dan Liu, Jiamei Xu et al.
Frontiers in Physiology
Sleep and related disorders
article

Analysis of potential categories of sleep problems in non-dialysis patients with chronic kidney disease

Jie Zhou, Chunxiang Huang, Dan Liu, Jiamei Xu, Xiaoke Zhu
article en

Abstract

Introduction: Sleep disturbances are highly prevalent among patients with non-dialysis chronic kidney disease (CKD) and are associated with adverse clinical outcomes. However, current research predominantly relies on aggregate scale scores, which may overlook the heterogeneity of sleep symptoms. This study aims to identify distinct latent categories of sleep problems and their influencing factors among patients with non-dialysis CKD using latent class analysis, thereby providing an evidence base for phenotype-specific interventions. Methods: From June to July 2023, a convenience sampling was used to select 405 patients from the Nephrology Department of a tertiary hospital in Hangzhou. Data were collected using a general information questionnaire, the Pittsburgh Sleep Quality Index (PSQI), the Hospital Anxiety and Depression Scale (HADS), the International Restless Legs Syndrome Assessment Scale (IRLS), and a Visual Analog Scale (VAS). Mplus 8.0 was used for latent class analysis, and unordered multinomial logistic regression analysis was performed to evaluate factors associated with the different latent classes. Results: < 0.05). Conclusion: Sleep problems among patients with non-dialysis CKD are heterogeneous. Targeted, class-specific interventions should be developed to improve sleep quality for different patient subgroups.

Frontiers in PhysiologyVol. 17
Zhejiang Chinese Medical University (CN), CM Hospital (KR)
Openalex Percentile: Top 20%
Sleep and related disorders
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