Evidence map›Paper›PMID 35272350›Full record

ArticleSleep2022

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

Magdy Younes, Bethany Gerardy, Allan I Pack, Samuel T Kuna, Cecilia Castro-Diehl, Susan Redline

Registry-linked trialOpen access · hybridAbstract read
In one paragraph

Article in Sleep, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05847374 (Relationship Between Asynchronies and Sleep Disruption in Mechanically Ventilated Patients), which is not on this map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
7.1field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT05847374 completednot on this map

Relationship Between Asynchronies and Sleep Disruption in Mechanically Ventilated Patients: a Prospective Cohort Study

TypeobservationalSponsorAlthaia Xarxa Assistencial Universitària de ManresaRan2019 to 2022Enrolled50ConditionsSleepArmsPolysomnography
3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 1 synthesis or guideline pooled it, 38 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Analytical amplitude/phase markers for neurological sleep apnea events.Neurobiology of sleep and circadian rhythms · 2026
    Article
  4. Observational
  5. Temporally Continuous Automated Sleep-Wake Classification Using Deep Learning.medRxiv : the preprint server for health sciences · 2025
    Article
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  8. Review
  9. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 4 institutions in 2 countries.

Magdy YounesSleep Disorders Centre, University of Manitoba, Winnipeg, Manitoba, Canada.
Bethany GerardyYRT Ltd., Winnipeg, Manitoba, Canada.
Allan I PackDivision of Sleep Medicine/Department of Medicine, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA.ORCID 0000-0002-2879-0484
Samuel T KunaDivision of Sleep Medicine/Department of Medicine, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA.
Cecilia Castro-DiehlDepartment of Medicine, Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.ORCID 0000-0003-3650-4684
Susan RedlineDepartment of Medicine, Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Brigham and Women's Hospital · USResearch Manitoba · CAPhiladelphia VA Medical Center · USUniversity of Pennsylvania · US

Funding

Phenotypic and Molecular Signatures for Sleep Apnea and Related MorbiditiesR35HL135818 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI REDLINE, SUSAN S. · 2017 to 2023
$7.2M
NHLBI NIH HHS R35 HL135818
6 · The paper itself

Abstract

STUDY

objectivesConventional 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.

methodsWe 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.

resultsThree 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.

conclusionsThe 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.

Indexed as

Sleep Apnea, ObstructiveSleep Initiation and Maintenance DisordersSleep Wake DisordersHumansOutcome Assessment, Health CarePrevalenceQuality of LifeSleepSleepinessEpworth sleepiness scaleinsomniaobstructive sleep apneaodds ratio productORPquality of lifesleep architecture

Identifiers

PMID35272350
PMCPMC9195236
OpenAlexW4220693977

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.