Sleep Disturbance and Depression Symptoms Mediate Relationship Between Pain and Cognitive Dysfunction in Lupus

Lillis, Teresa; Tirone, Vanessa; Gandhi, Nisarg; Weinberg, Stacy; Nika, Ailda; Sequeira, Winston; Hobfoll, Stevan E.; Block, Joel A.; Jolly, Meenakshi

doi:10.1002/acr.23593

Cited by 26 publications

(25 citation statements)

References 39 publications

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“…Furthermore, resilience could partially mediate the relationship between sleep disturbance and PSD. It was found that sleep disturbance contributed the most to PSD in this study, which was in agreement with most previous studies showing that sleep disturbance was positively associated with depression in patients with heart disease (48), lupus (49), and chronic obstructive pulmonary disease (50). PSD is the most common clinical complication and sequelae of stroke, studies have shown that the levels of IL-6, IL-1β, and Hcy in patients with PSD are significantly higher than those in the normal population (51).…”

Section: Discussionsupporting

confidence: 93%

Resilience as the Mediating Factor in the Relationship Between Sleep Disturbance and Post-stroke Depression of Stroke Patients in China: A Structural Equation Modeling Analysis

et al. 2021

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Background: Stroke patients may suffer from a variety of symptoms which can result in sleep disturbance and post-stroke depression (PSD). Whereas, resilience can alleviate sleep disturbance and help maintain well-being after stroke.Objective: The aim of this study is to explore whether resilience plays a mediating role in the relationship between sleep disturbance and PSD of stroke patients in China.Methods: A cross-sectional study with a multi-stage sampling was carried out in Liaoning Rehabilitation Center and the Third People's Hospital of Chongqing in China from May to September 2019. A total of 353 stroke patients were enrolled in this study. Structural equation model (SEM) was used to test the mediating effect of resilience on the relationship between sleep disturbance and PSD.Results: The prevalence of PSD of stroke patients was 34.56%. Sleep disturbance contributed most to the variance of PSD and had a significantly positive association with PSD among stroke patients (P < 0.01). Resilience was negatively associated with PSD, and acted as a mediator between sleep disturbance and PSD (a * b = 0.201, BCa 95% CI: 0.156~0.254).Conclusions: The prevalence of PSD was high among the Chinese stroke patients. Sleep disturbance was highly associated with PSD, resulting in the increased risk of PSD. Furthermore, resilience has a mediating effect on the relationship between sleep disturbance and PSD, and could reduce the negative effect of sleep disturbance on the development of PSD.

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Section: Discussionsupporting

confidence: 93%

Resilience as the Mediating Factor in the Relationship Between Sleep Disturbance and Post-stroke Depression of Stroke Patients in China: A Structural Equation Modeling Analysis

et al. 2021

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“…Besides, more scholars have paid attention to anxiety and depression in SLE patients. Moreover, previous study 23 found that fragmented sleep and depression can increase the incidence of CD. And only depression levels, among clinical variables, significantly predicted cognitive performance by multivariate analysis.…”

Section: Discussionmentioning

confidence: 92%

Prevalence, involved domains, and predictor of cognitive dysfunction in systemic lupus erythematosus

Yue

Gurung

Long

et al. 2020

Lupus

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Background Cognitive Dysfunction (CD) can occur in Systemic Lupus Erythematosus (SLE) before the occurrence of Neuropsychiatric Lupus Erythematosus (NPSLE). Given the reversibility and fluctuation of SLE-related CD, the research for possible predictors is of great significance for early detection and intervention. Objective We sought to determine the prevalence, involved domains, and possible predictors of CD in SLE patients. Methods We conducted a retrospective cross-sectional study at Nanfang Hospital from 2018 to 2019. A total of 78 SLE patients were recruited. The Montreal Cognitive Assessment (MoCA) scale was used to screen cognitive function. Demographic, clinical, and laboratory characteristics were collected. The serum anti-methyl-d-aspartate receptor (anti-NMDAR) antibody and S100β were measured by enzyme-linked immunosorbent assay (ELISA). Multivariate logistic regression analysis and ROC curve were used to assess the predictor of SLE-related CD. Results Of 78 recruited patients,53 (67.9%) had CD. It mainly involved delayed recall, abstract generalization, verbal repetition, and fluency. The disease activity index (SLEDAI) was not associated with SLE-related CD ( p > 0.05). Multivariate logistic regression showed that an increase in each year of education there was a decrease in the likelihood of CD (OR 0.261, CI 0.080-0.857, p = 0.027) whereas with each unit increase in serum anti-NMDAR antibody there was an increased likelihood of SLE-related CD (OR 1.568, CI 1.073–2.292, p = 0.020). Conclusion The prevalence of SLE-related CD was 67.9% in our study and SLE-related CD was not associated with disease activity. Serum anti-NMDAR antibody can be used as a predictor for SLE-related CD.

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“…Irrespective of the origin of the symptoms, current treatment recommendations for fibromyalgia in SLE are similar to those of primary fibromyalgia and include graded exercise, improvement in restorative sleep, cognitive and behavioral therapy for underlying mood disorders, and pharmacologic therapies directed at depression and neuropathic pain (43–46). Aerobic exercise has demonstrated safety and efficacy for alleviating fatigue and depression in patients with SLE (47–49).…”

Section: Discussionmentioning

confidence: 99%

Using Clinical Characteristics and Patient‐Reported Outcome Measures to Categorize Systemic Lupus Erythematosus Subtypes

Rogers

Eudy

Pisetsky

et al. 2021

Arthritis Care & Research

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Objective The type 1 and type 2 systemic lupus erythematosus (SLE) categorization system was recently proposed to validate the patients’ perspective of disease and to capture a more comprehensive spectrum of symptoms. The objective of this study was to characterize the clinical manifestations of SLE subtypes and to determine the correlation between the patient‐ and physician‐reported measures used in the model. Methods This was a cross‐sectional study of patients with SLE in a university clinic. Patients completed the Systemic Lupus Activity Questionnaire (SLAQ) and 2011 American College of Rheumatology fibromyalgia (FM) criteria. Active SLE was defined as Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) score ≥6, clinical SLEDAI score ≥4, or active lupus nephritis. We identified 4 groups: type 1 SLE (active SLE without FM), type 2 SLE (inactive SLE with FM), mixed SLE (active SLE with FM), and minimal SLE (inactive SLE without FM). Results In this cohort of 212 patients (92% female, mean age 45 years), 30% had type 1 SLE, 8% had type 2 SLE, 13% had mixed SLE, and 49% had minimal SLE. Regardless of SLE disease activity, patients with FM (21%), reported higher SLAQ scores, patient global assessment scores, and self‐reported lupus flare that resulted in discordance between patient‐ and physician‐reported measures. Conclusion Fatigue, widespread pain, sleep dysfunction, and mood disorders are common symptoms in SLE. Identifying these symptoms as type 2 SLE may be a method to improve patient communication and understanding. The level of type 2 SLE impacts patients’ perception of disease and self‐reported symptoms. The SLAQ may need to be reinterpreted based on the FM severity scale.

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Sleep Disturbance and Depression Symptoms Mediate Relationship Between Pain and Cognitive Dysfunction in Lupus

Cited by 26 publications

References 39 publications

Resilience as the Mediating Factor in the Relationship Between Sleep Disturbance and Post-stroke Depression of Stroke Patients in China: A Structural Equation Modeling Analysis

Resilience as the Mediating Factor in the Relationship Between Sleep Disturbance and Post-stroke Depression of Stroke Patients in China: A Structural Equation Modeling Analysis

Prevalence, involved domains, and predictor of cognitive dysfunction in systemic lupus erythematosus

Using Clinical Characteristics and Patient‐Reported Outcome Measures to Categorize Systemic Lupus Erythematosus Subtypes

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