Literature DB >> 31328230

Microsleep episodes in the borderland between wakefulness and sleep.

Anneke Hertig-Godeschalk1,2, Jelena Skorucak3,4,5, Alexander Malafeev3,4, Peter Achermann3,4,5,6, Johannes Mathis1, David R Schreier1,2,7.   

Abstract

STUDY
OBJECTIVES: The wake-sleep transition zone represents a poorly defined borderland, containing, for example, microsleep episodes (MSEs), which are of potential relevance for diagnosis and may have consequences while driving. Yet, the scoring guidelines of the American Academy of Sleep Medicine (AASM) completely neglect it. We aimed to explore the borderland between wakefulness and sleep by developing the Bern continuous and high-resolution wake-sleep (BERN) criteria for visual scoring, focusing on MSEs visible in the electroencephalography (EEG), as opposed to purely behavior- or performance-defined MSEs.
METHODS: Maintenance of Wakefulness Test (MWT) trials of 76 randomly selected patients were retrospectively scored according to both the AASM and the newly developed BERN scoring criteria. The visual scoring was compared with spectral analysis of the EEG. The quantitative EEG analysis enabled a reliable objectification of the visually scored MSEs. For less distinct episodes within the borderland, either ambiguous or no quantitative patterns were found.
RESULTS: As expected, the latency to the first MSE was significantly shorter in comparison to the sleep latency, defined according to the AASM criteria. In certain cases, a large difference between the two latencies was observed and a substantial number of MSEs occurred between the first MSE and sleep. Series of MSEs were more frequent in patients with shorter sleep latencies, while isolated MSEs were more frequent in patients who did not reach sleep.
CONCLUSION: The BERN criteria extend the AASM criteria and represent a valuable tool for in-depth analysis of the wake-sleep transition zone, particularly important in the MWT. © Sleep Research Society 2019. 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:  AASM scoring criteria; Maintenance of Wakefulness Test; electroencephalography; microsleep; sleep; sleepiness; wake-sleep transition zone; wakefulness

Year:  2020        PMID: 31328230     DOI: 10.1093/sleep/zsz163

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


  9 in total

1.  Exclusion of EEG-based arousals in wake epochs of polysomnography leads to underestimation of the arousal index.

Authors:  Danielle L Wilson; Julie Tolson; Thomas J Churchward; Kerri Melehan; Fergal J O'Donoghue; Warren R Ruehland
Journal:  J Clin Sleep Med       Date:  2022-05-01       Impact factor: 4.062

2.  Enhanced Visual Cortex Activation in People With Narcolepsy Type 1 During Active Sleep Resistance: An fMRI-EEG Study.

Authors:  Jari K Gool; Rolf Fronczek; Peter Bosma; Johan N van der Meer; Ysbrand D van der Werf; Gert Jan Lammers
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Review 3.  Epidemiology, Physiology and Clinical Approach to Sleepiness at the Wheel in OSA Patients: A Narrative Review.

Authors:  Maria R Bonsignore; Carolina Lombardi; Simone Lombardo; Francesco Fanfulla
Journal:  J Clin Med       Date:  2022-06-27       Impact factor: 4.964

Review 4.  Sleepiness as a Local Phenomenon.

Authors:  Sasha D'Ambrosio; Anna Castelnovo; Ottavia Guglielmi; Lino Nobili; Simone Sarasso; Sergio Garbarino
Journal:  Front Neurosci       Date:  2019-10-18       Impact factor: 4.677

5.  Automatically Detected Microsleep Episodes in the Fitness-to-Drive Assessment.

Authors:  Jelena Skorucak; Anneke Hertig-Godeschalk; Peter Achermann; Johannes Mathis; David R Schreier
Journal:  Front Neurosci       Date:  2020-01-23       Impact factor: 4.677

6.  The Relationship between Simple Snoring and Sleep Bruxism: A Polysomnographic Study.

Authors:  Monika Michalek-Zrabkowska; Mieszko Wieckiewicz; Piotr Macek; Pawel Gac; Joanna Smardz; Anna Wojakowska; Rafal Poreba; Grzegorz Mazur; Helena Martynowicz
Journal:  Int J Environ Res Public Health       Date:  2020-12-02       Impact factor: 3.390

7.  Automatic Detection of Microsleep Episodes With Deep Learning.

Authors:  Alexander Malafeev; Anneke Hertig-Godeschalk; David R Schreier; Jelena Skorucak; Johannes Mathis; Peter Achermann
Journal:  Front Neurosci       Date:  2021-03-24       Impact factor: 4.677

8.  Microsleep assessment enhances interpretation of the Maintenance of Wakefulness Test.

Authors:  Angela M Anniss; Alan Young; Denise M O'Driscoll
Journal:  J Clin Sleep Med       Date:  2021-08-01       Impact factor: 4.324

9.  Sleep onset is a creative sweet spot.

Authors:  Célia Lacaux; Thomas Andrillon; Céleste Bastoul; Yannis Idir; Alexandrine Fonteix-Galet; Isabelle Arnulf; Delphine Oudiette
Journal:  Sci Adv       Date:  2021-12-08       Impact factor: 14.136

  9 in total

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