Evidence map›Paper›PMID 41169394›Full record

ArticleFrontiers in immunology2025

Associations of sleep disturbances in systemic lupus erythematosus with physical and psychological outcomes: a cross-sectional latent profile analysis.

Ling Ma, Yan-Hong Li, Xin Guo, Ying Wang

Abstract read
In one paragraph

Article in Frontiers in immunology, 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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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Ling MaDepartment of Rheumatology and Immunology, West China Hospital, Sichuan University, Chengdu, China.
Yan-Hong LiDepartment of Rheumatology and Immunology, West China Hospital, Sichuan University, Chengdu, China.
Xin GuoDepartment of Rheumatology and Immunology, West China Hospital, Sichuan University, Chengdu, China.
Ying WangDepartment of Rheumatology and Immunology, West China Hospital, Sichuan University, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Patients with systemic lupus erythematosus (SLE) frequently experience poor sleep quality. This cross-sectional study aimed to identify distinct sleep disturbance profiles in SLE patients and examine their associations with demographic, disease-related, and psychosocial factors. Methods: A total of 331 patients with SLE were included. Latent profile analysis (LPA) was conducted using the tidyLPA package. Logistic regression models were constructed to assess associations between the identified sleep disturbance clusters and physical and psychological outcomes, based on factors significantly influencing the LPA results. The physical and psychological outcomes were estimated using the Hospital Anxiety and Depression Scale (HADS) and the Fatigue Severity Scale (FSS). Sleep clusters were analyzed through multivariate logistic regression. Results: Three distinct sleep disturbance profiles were identified: Cluster 1 (severe sleep disturbance) (n = 42), Cluster 2 (moderate sleep disturbance) (n = 174), and Cluster 3 (mild sleep disturbance) (n = 115). LPA yielded an entropy value of 0.996 for the three-cluster model. The mean total Pittsburgh Sleep Quality Index (PSQI) score for the SLE samples was 7.59 ± 3.44. Among the various sleep quality domains, sleep latency and subjective sleep quality were the most significantly affected in SLE patients. The analysis revealed that disease duration, severity of fatigue, use of calcium supplements, impaired renal function, anxiety, and depression were all significant factors influencing cluster membership. Conclusion: This study identified three distinct patterns of sleep disturbance among SLE patients. Cluster 1 (severe sleep disturbance) was characterized by prolonged sleep latency despite high sleep efficiency and subjective sleep quality scores. Cluster 2 (moderate sleep disturbance) exhibited longer sleep duration than Cluster 1, while Cluster 3 (mild sleep disturbance) had the lowest scores across all sleep quality domains. These findings suggest that sleep disturbance profiling may facilitate personalized sleep management strategies for patients with SLE.

Indexed as

Lupus Erythematosus, SystemicSleep Wake DisordersAdultCross-Sectional StudiesDepressionFatigueFemaleHumansMaleMiddle AgedQuality of LifeSeverity of Illness IndexSleep Qualitycluster analysisinfluencing factorlatent profile analysissleep qualitysystemic lupus erythematosus

Identifiers

PMID41169394
PMCPMC12568493

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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 OpenQuestion graph.