Evidence map›Paper›PMID 35992215›Full record

ArticleAlzheimer's & dementia (New York, N. Y.)2022

Home EEG sleep assessment shows reduced slow-wave sleep in mild-moderate Alzheimer's disease.

Brianne A Kent, Amelia A Casciola, Sebastiano K Carlucci, Meghan Chen, Sam Stager, Maryam S Mirian, Penelope Slack, Jason Valerio, Martin J McKeown, Howard H Feldman and 1 more

Open access · goldAbstract read
In one paragraph

Article in Alzheimer's & dementia (New York, N. Y.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
1.8field-weighted citation impact, top 16% 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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.

  1. Pooled it
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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

11 authors at 1 institution in 2 countries.

Brianne A KentDivision of Neurology Djavad Mowafaghian Centre for Brain Health University of British Columbia Vancouver BC V6T1Z3 Canada.
Amelia A CasciolaDivision of Neurology Djavad Mowafaghian Centre for Brain Health University of British Columbia Vancouver BC V6T1Z3 Canada.
Sebastiano K CarlucciDivision of Neurology Djavad Mowafaghian Centre for Brain Health University of British Columbia Vancouver BC V6T1Z3 Canada.
Meghan ChenDivision of Neurology Djavad Mowafaghian Centre for Brain Health University of British Columbia Vancouver BC V6T1Z3 Canada.
Sam StagerDivision of Neurology Djavad Mowafaghian Centre for Brain Health University of British Columbia Vancouver BC V6T1Z3 Canada.
Maryam S MirianDivision of Neurology Djavad Mowafaghian Centre for Brain Health University of British Columbia Vancouver BC V6T1Z3 Canada.
Penelope SlackDivision of Neurology Djavad Mowafaghian Centre for Brain Health University of British Columbia Vancouver BC V6T1Z3 Canada.
Jason ValerioDivision of Neurology Djavad Mowafaghian Centre for Brain Health University of British Columbia Vancouver BC V6T1Z3 Canada.
Martin J McKeownDivision of Neurology Djavad Mowafaghian Centre for Brain Health University of British Columbia Vancouver BC V6T1Z3 Canada.
Howard H FeldmanDivision of Neurology Djavad Mowafaghian Centre for Brain Health University of British Columbia Vancouver BC V6T1Z3 Canada.
Haakon B NygaardDivision of Neurology Djavad Mowafaghian Centre for Brain Health University of British Columbia Vancouver BC V6T1Z3 Canada.
University of British Columbia · CA

Funding

Research Education ComponentP30AG062421 · NIA · MASSACHUSETTS GENERAL HOSPITAL · PI Christine S Ritchie · 2019 to 2026
$36.5M
NIA NIH HHS P30 AG062421
6 · The paper itself

Abstract

Introduction: Sleep disturbances are common in Alzheimer's disease (AD), with estimates of prevalence as high as 65%. Recent work suggests that specific sleep stages, such as slow-wave sleep (SWS) and rapid eye movement (REM), may directly impact AD pathophysiology. A major limitation to sleep staging is the requirement for clinical polysomnography (PSG), which is often not well tolerated in patients with dementia. We have recently developed a deep learning model to reliably analyze lower quality electroencephalogram (EEG) data obtained from a simple, two-lead EEG headband. Here we assessed whether this methodology would allow for home EEG sleep staging in patients with mild-moderate AD. Methods: A total of 26 mild-moderate AD patients and 24 age-matched, healthy control participants underwent home EEG sleep recordings as well as actigraphy and subjective sleep measures through the Pittsburgh Sleep Quality Index (PSQI). Each participant wore the EEG headband for up to three nights. Sleep was staged using a deep learning model previously developed by our group, and sleep stages were correlated with actigraphy measures as well as PSQI scores. Results: We show that home EEG with a headband is feasible and well tolerated in patients with AD. Patients with mild-moderate AD were found to spend less time in SWS compared to healthy control participants. Other sleep stages were not different between the two groups. Actigraphy or the PSQI were not found to predict home EEG sleep stages. Discussion: Our data show that home EEG is well tolerated, and can ascertain reduced SWS in patients with mild-moderate AD. Similar findings have previously been reported, but using clinical PSG not suitable for the home environment. Home EEG will be particularly useful in future clinical trials assessing potential interventions that may target specific sleep stages to alter the pathogenesis of AD. Highlights: Home electroencephalogram (EEG) sleep assessments are important for measuring sleep in patients with dementia because polysomnography is a limited resource not well tolerated in this patient population.Simplified at-home EEG for sleep assessment is feasible in patients with mild-moderate Alzheimer's disease (AD).Patients with mild-moderate AD exhibit less time spent in slow-wave sleep in the home environment, compared to healthy control participants.Compared to healthy control participants, patients with mild-moderate AD spend more time in bed, with decreased sleep efficiency, and more awakenings as measured by actigraphy, but these measures do not correlate with EEG sleep stages.

Indexed as

actigraphyAlzheimer's diseasedeep learninghome electroencephalogramN3Pittsburgh Sleep Quality Indexpolysomnographyrapid eye movementsleep stagingslow‐wave sleep

Identifiers

PMID35992215
PMCPMC9381912
OpenAlexW4292295071

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.