Literature DB >> 33249509

Characteristics associated with hypersomnia and excessive daytime sleepiness identified by extended polysomnography recording.

Elisa Evangelista1,2, Anna Laura Rassu1, Lucie Barateau1,2, Régis Lopez1,2, Sofiène Chenini1, Isabelle Jaussent2, Yves Dauvilliers1,2.   

Abstract

STUDY
OBJECTIVES: Hypersomnolence, defined by excessive daytime sleepiness (EDS) or excessive quantity of sleep (EQS), has been associated with increased morbidity. The aim of this study was to determine the clinical and polysomnographic characteristics associated with EQS and EDS assessed objectively during extended polysomnography recording.
METHODS: A total of 266 drug-free subjects (201 women; mean age: 26.5 years [16.08; 60.87]) underwent 32-h bed-rest polysomnography recording preceded by polysomnography and modified multiple sleep latency test (mMSLT). Participants were categorized according to their total sleep time (bed-rest TST ≥19 h, hypersomnia), objective EDS (mean sleep latency on MSLT ≤8 min), and self-reported EDS (Epworth sleepiness scale score >10) and EQS (≥9 h/24 h per week).
RESULTS: Subjects with hypersomnia were often younger, with normal sleep architecture, high nighttime sleep efficiency, and severe objective EDS. No association with sex, body mass index, Epworth sleepiness scale, EQS, and depressive symptoms was detected. Subjects with objective EDS had less EQS, higher sleep efficiency, and increased hypersomnia. Discrepancies were observed between objective and self-reported measures of sleep duration and EDS. Finally, 71 subjects were identified who had objective hypersomnia and/or EDS, no medical and psychiatric conditions and normal polysomnography parameters, and therefore met the stringent criteria of idiopathic hypersomnia, an orphan disorder.
CONCLUSIONS: Sleep duration and EDS should be quantified using self-reported and objective measures in a controlled procedure to differentiate long sleepers, patients with hypersomnia, and patients with idiopathic hypersomnia. This will help to better understand their biology, to identify specific biomarkers, and to assess related health outcomes. © Sleep Research Society 2020. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.

Entities:  

Keywords:  daytime sleepiness; depression; hypersomnia; hypersomnolence; long sleep; obesity; sleep inertia; total sleep time

Mesh:

Year:  2021        PMID: 33249509     DOI: 10.1093/sleep/zsaa264

Source DB:  PubMed          Journal:  Sleep        ISSN: 0161-8105            Impact factor:   5.849


  3 in total

1.  Idiopathic Hypersomnia Severity Scale to better quantify symptoms severity and their consequences in idiopathic hypersomnia.

Authors:  Anna Laura Rassu; Elisa Evangelista; Lucie Barateau; Sofiene Chenini; Régis Lopez; Isabelle Jaussent; Yves Dauvilliers
Journal:  J Clin Sleep Med       Date:  2022-02-01       Impact factor: 4.062

2.  Data-Driven Phenotyping of Central Disorders of Hypersomnolence With Unsupervised Clustering.

Authors:  Jari K Gool; Zhongxing Zhang; Martijn S S L Oei; Stephanie Mathias; Yves Dauvilliers; Geert Mayer; Giuseppe Plazzi; Rafael Del Rio-Villegas; Joan Santamaria Cano; Karel Šonka; Markku Partinen; Sebastiaan Overeem; Rosa Peraita-Adrados; Raphael Heinzer; Antonio Martins da Silva; Birgit Högl; Aleksandra Wierzbicka; Anna Heidbreder; Eva Feketeova; Mauro Manconi; Jitka Bušková; Francesca Canellas; Claudio L Bassetti; Lucie Barateau; Fabio Pizza; Markus H Schmidt; Rolf Fronczek; Ramin Khatami; Gert Jan Lammers
Journal:  Neurology       Date:  2022-04-18       Impact factor: 11.800

3.  Multidimensional assessment and cluster analysis for OSA phenotyping.

Authors:  Xiao Lei Zhang; Li Zhang; Yi Ming Li; Bo Yun Xiang; Teng Han; Yan Wang; Chen Wang
Journal:  J Clin Sleep Med       Date:  2022-07-01       Impact factor: 4.324

  3 in total

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