Sleep architecture based on sleep depth and propensity: patterns in different demographics and sleep disorders and association with health outcomes.


Journal

Sleep
ISSN: 1550-9109
Titre abrégé: Sleep
Pays: United States
ID NLM: 7809084

Informations de publication

Date de publication:
13 06 2022
Historique:
received: 04 01 2022
revised: 10 02 2022
pubmed: 11 3 2022
medline: 15 6 2022
entrez: 10 3 2022
Statut: ppublish

Résumé

Conventional metrics of sleep quantity/depth have serious shortcomings. Odds-Ratio-Product (ORP) is a continuous metric of sleep depth ranging from 0 (very deep sleep) to 2.5 (full-wakefulness). We describe an ORP-based approach that provides information on sleep disorders not apparent from traditional metrics. We analyzed records from the Sleep-Heart-Health-Study and a study of performance deficit following sleep deprivation. ORP of all 30-second epochs in each PSG and percent of epochs in each decile of ORPs range were calculated. Percentage of epochs in deep sleep (ORP < 0.50) and in full-wakefulness (ORP > 2.25) were each assigned a rank, 1-3, representing first and second digits, respectively, of nine distinct types ("1,1", "1,2" … "3,3"). Prevalence of each type in clinical groups and their associations with demographics, sleepiness (Epworth-Sleepiness-Scale, ESS) and quality of life (QOL; Short-Form-Health-Survey-36) were determined. Three types ("1,1", "1,2", "1,3") were prevalent in OSA and were associated with reduced QOL. Two ("1,3" and "2,3") were prevalent in insomnia with short-sleep-duration (insomnia-SSD), but only "1,3" was associated with poor sleep depth and reduced QOL, suggesting two phenotypes in insomnia-SSD. ESS was high in types "1,1" and "1,2", and low in "1,3" and "2,3". Prevalence of some types increased with age while in others it decreased. Other types were either rare ("1,1" and "3,3") or high ("2,2") at all ages. The proposed ORP histogram offers specific and unique information on the underlying neurophysiological characteristics of sleep disorders not captured by routine metrics, with potential of advancing diagnosis and management of these disorders.

Identifiants

pubmed: 35272350
pii: 6546700
doi: 10.1093/sleep/zsac059
pmc: PMC9195236
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : NHLBI NIH HHS
ID : R35 HL135818
Pays : United States

Informations de copyright

© Sleep Research Society 2022. Published by Oxford University Press on behalf of the Sleep Research Society.

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Auteurs

Magdy Younes (M)

Sleep Disorders Centre, University of Manitoba, Winnipeg, Manitoba, Canada.
YRT Ltd., Winnipeg, Manitoba, Canada.

Bethany Gerardy (B)

YRT Ltd., Winnipeg, Manitoba, Canada.

Allan I Pack (AI)

Division of Sleep Medicine/Department of Medicine, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA.

Samuel T Kuna (ST)

Division of Sleep Medicine/Department of Medicine, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA.
Department of Medicine, Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA.

Cecilia Castro-Diehl (C)

Department of Medicine, Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

Susan Redline (S)

Department of Medicine, Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

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Classifications MeSH