Evidence map›Paper›PMID 33248430›Full record

ArticleClinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology2021

Night-to-night variability of sleep electroencephalography-based brain age measurements.

Jacob Hogan, Haoqi Sun, Luis Paixao, Mike Westmeijer, Pooja Sikka, Jing Jin, Ryan Tesh, Madalena Cardoso, Sydney S Cash, Oluwaseun Akeju and 2 more

Abstract read
In one paragraph

Article in Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
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

12 citing papers in PubMed.

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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

12 authors.

Jacob HoganDepartment of Neurology, Massachusetts General Hospital, Boston, MA, USA.
Haoqi SunDepartment of Neurology, Massachusetts General Hospital, Boston, MA, USA.
Luis PaixaoDepartment of Neurology, Massachusetts General Hospital, Boston, MA, USA.
Mike WestmeijerDepartment of Neurology, Massachusetts General Hospital, Boston, MA, USA.
Pooja SikkaDepartment of Neurology, Massachusetts General Hospital, Boston, MA, USA.
Jing JinDepartment of Neurology, Massachusetts General Hospital, Boston, MA, USA.
Ryan TeshDepartment of Neurology, Massachusetts General Hospital, Boston, MA, USA.
Madalena CardosoDepartment of Neurology, Massachusetts General Hospital, Boston, MA, USA.
Sydney S CashDepartment of Neurology, Massachusetts General Hospital, Boston, MA, USA.
Oluwaseun AkejuDepartment of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA.
Robert ThomasDivision of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA.
M Brandon WestoverDepartment of Neurology, Massachusetts General Hospital, Boston, MA, USA. Electronic address: mwestover@mgh.harvard.edu.

Funding

Integrative Motor Activity Biomarker for the Risk of Alzheimer's RiskRF1AG064312 · NIA · BRIGHAM AND WOMEN'S HOSPITAL · PI HU, KUN · 2019 to 2019
$3.6M
Multimodal Network Connectivity Architecture (MOCA) of the Brain and its Role in the Recovery of Consciousness in Comatose Cardiac Arrest PatientsR01NS102574 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI GREER, DAVID MATTHEW, WU, ONA · 2018 to 2022
$3.4M
Investigation of Sleep in the Intensive Care Unit (ICU-SLEEP)R01NS102190 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI WESTOVER, MICHAEL BRANDON · 2018 to 2022
$3.2M
Big Data and Deep Learning for the Interictal-Ictal-Injury ContiuumR01NS107291 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI WESTOVER, MICHAEL BRANDON · 2018 to 2022
$2.8M
NIA NIH HHS RF1 AG064312NINDS NIH HHS R01 NS102190NINDS NIH HHS R01 NS102574NINDS NIH HHS R01 NS107291
6 · The paper itself

Abstract

objectiveBrain Age Index (BAI), calculated from sleep electroencephalography (EEG), has been proposed as a biomarker of brain health. This study quantifies night-to-night variability of BAI and establishes probability thresholds for inferring underlying brain pathology based on a patient's BAI.

methods86 patients with multiple nights of consecutive EEG recordings were selected from Epilepsy Monitoring Unit patients whose EEGs reported as within normal limits. While EEGs with epileptiform activity were excluded, the majority of patients included in the study had a diagnosis of chronic epilepsy. BAI was calculated for each 12-hour segment of patient data using a previously established algorithm, and the night-to-night variability in BAI was measured.

resultsThe within-patient night-to-night standard deviation in BAI was 7.5 years. Estimates of BAI derived by averaging over 2, 3, and 4 nights had standard deviations of 4.7, 3.7, and 3.0 years, respectively.

conclusionsAveraging BAI over n nights reduces night-to-night variability of BAI by a factor of n, rendering BAI a more suitable biomarker of brain health at the individual level. A brain age risk lookup table of results provides thresholds above which a patient has a high probability of excess BAI. SIGNIFICANCE: With increasing ease of EEG acquisition, including wearable technology, BAI has the potential to track brain health and detect deviations from normal physiologic function. The measure of night-to-night variability and how this is reduced by averaging across multiple nights provides a basis for using BAI in patients' homes to identify patients who should undergo further investigation or monitoring.

Indexed as

Age FactorsAlgorithmsElectroencephalographyAdultAgingBrainBrain DiseasesChronic DiseaseEpilepsyFemaleHumansMaleMiddle AgedSignal-To-Noise RatioSleepSleep StagesBrain ageBrain healthEEGNight-to-night variabilitySleep

Identifiers

PMID33248430
PMCPMC7855943

What OpenQuestion holds

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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.