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Patterns of polysomnography parameters in 27 neuropsychiatric diseases: an umbrella review

Published online by Cambridge University Press:  15 November 2022

Ye Zhang ,
Rong Ren ,
Linghui Yang ,
Haipeng Zhang ,
Yuan Shi ,
Michael V. Vitiello ,
Larry D. Sanford  and
Xiangdong Tang
Ye Zhang
Affiliation:
Sleep Medicine Center, Mental Health Center, West China Hospital, Sichuan University, Chengdu, China
Rong Ren*
Affiliation:
Sleep Medicine Center, Mental Health Center, West China Hospital, Sichuan University, Chengdu, China
Linghui Yang
Affiliation:
Sleep Medicine Center, Mental Health Center, West China Hospital, Sichuan University, Chengdu, China
Haipeng Zhang
Affiliation:
Sleep Medicine Center, Mental Health Center, West China Hospital, Sichuan University, Chengdu, China
Yuan Shi
Affiliation:
Sleep Medicine Center, Mental Health Center, West China Hospital, Sichuan University, Chengdu, China
Michael V. Vitiello
Affiliation:
Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA 98195-6560, USA
Larry D. Sanford
Affiliation:
Sleep Research Laboratory, Center for Integrative Neuroscience and Inflammatory Diseases, Pathology and Anatomy, Eastern Virginia Medical School, Norfolk, VA, USA
Xiangdong Tang*
Affiliation:
Sleep Medicine Center, Mental Health Center, West China Hospital, Sichuan University, Chengdu, China
*
Author for correspondence: Xiangdong Tang, E-mail: 2372564613@qq.com; Rong Ren, E-mail: 498880651@qq.com
Author for correspondence: Xiangdong Tang, E-mail: 2372564613@qq.com; Rong Ren, E-mail: 498880651@qq.com
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Abstract

Background

We provide an umbrella review of the reported polysomnographic changes in patients with neuropsychiatric diseases compared with healthy controls.

Methods

An electronic literature search was conducted in EMBASE, MEDLINE, All EBM databases, CINAHL, and PsycINFO. Meta-analyses of case–control studies investigating the polysomnographic changes in patients with neuropsychiatric diseases were included. For each meta-analysis, we estimated the summary effect size using random effects models, the 95% confidence interval, and the 95% prediction interval. We also estimated between-study heterogeneity, evidence of excess significance bias, and evidence of small-study effects. The levels of evidence of polysomnographic changes in neuropsychiatric diseases were ranked as follows: not significant, weak, suggestive, highly suggestive, or convincing.

Results

We identified 27 articles, including 465 case–control studies in 27 neuropsychiatric diseases. The levels of evidence of polysomnographic changes in neuropsychiatric diseases were highly suggestive for increased sleep latency and decreased sleep efficiency (SE) in major depressive disorder (MDD), increased N1 percentage, and decreased N2 percentage, SL and REML in narcolepsy, and decreased rapid eye movement (REM) sleep percentage in Parkinson's disease (PD). The suggestive evidence decreased REM latency in MDD, decreased total sleep time and SE in PD, and decreased SE in posttraumatic stress disorder and in narcolepsy.

Conclusions

The credibility of evidence for sleep characteristics in 27 neuropsychiatric diseases varied across polysomnographic variables and diseases. When considering the patterns of altered PSG variables, no two diseases had the same pattern of alterations, suggesting that specific sleep profiles might be important dimensions for defining distinct neuropsychiatric disorders.

Keywords

Neuropsychiatric diseasepolysomnographyumbrella review
Type
Original Article
Information
Psychological Medicine , Volume 53 , Issue 10 , July 2023 , pp. 4675 - 4695
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Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press

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