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Record W3112482287 · doi:10.1002/alz.045275

Increased self‐reported sleepiness is associated with larger brain volume and less ischemic brain injury in a community sample

2020· article· en· W3112482287 on OpenAlexaff
Andrée‐Ann Baril, Alexa Beiser, Charles DeCarli, Erlan Sanchez, Vincent Mysliwiec, Sudha Seshadri, Jayandra J. Himali, Matthew P. Pase

Bibliographic record

VenueAlzheimer s & Dementia · 2020
Typearticle
Languageen
FieldMedicine
TopicObstructive Sleep Apnea Research
Canadian institutionsCanadian Sleep & Circadian Network
Fundersnot available
KeywordsEpworth Sleepiness ScaleBrain sizeInternal medicineBody mass indexMedicineFramingham Heart StudyPsychologyHyperintensityFramingham Risk ScoreCardiologyMagnetic resonance imagingDiseasePolysomnography

Abstract

fetched live from OpenAlex

Abstract Background Sleepiness has been associated with an increased risk of Alzheimer’s disease (AD) and vascular dementia, but few studies have investigated its association with markers of accelerated brain aging. We evaluated the association between sleepiness and MRI measures; and whether the apolipoprotein E4 (APOE4) allele status moderates this relationship. Method We studied 492 participants (58.8 ± 8.8 years, 49.4%M) in the Framingham Heart Study aged >40 years without significant neurological diseases, such as dementia and stroke. We used the Epworth Sleepiness Scale (ESS) to assess sleepiness. Brain MRI metrics were volumes of white matter hyperintensities (WMH), total brain, cortical gray matter (GM) and subcortical GM, all investigated as a percentage of total intracranial volume; we also identified covert brain infarcts (CBI). Linear and logistic regressions were used to assess the association between ESS scores and brain structure. Model 1 adjusted for age, age squared, sex, and time between the ESS and MRI (3.3 ± 1.0 years). Model 2 additionally adjusted for APOE4 allele carrier status, Framingham Stroke Risk Profile scores, sleep medication, body mass index, and depression. We included an interaction term between APOE4 allele status and ESS score, adjusted for model 1 covariates, to evaluate potential effect modification. Result Higher ESS scores, indicating greater sleepiness, were associated with higher total brain volume (b = 0.33; SE = 0.13; p = 0.02), higher cortical GM volume (b = 0.26; SE = 0.12; p = 0.03), and a lower risk of CBI (OR = 0.57; 95%CI = 0.36‐0.93; p = 0.02) adjusted for both models 1 and 2 covariates. These associations were present when further adjusting for the apnea‐hypopnea index, education and habitual sleep duration. A significant interaction was observed between APOE4 and ESS scores (p = 0.008), where higher ESS was associated with higher cortical GM in non‐carriers (b = 0.43; SE = 0.14; p = 0.002). Conversely, in carriers, higher ESS was associated with lower cortical GM (b = ‐0.36; SE = 0.22; p = 0.09, trend). Conclusion Increased self‐reported sleepiness was associated with findings of better brain health, including higher cortical GM volume and less CBI. Genetic susceptibility to AD modified this relationship, where increased sleepiness was associated with higher cortical GM volume only in APOE4 non‐carriers. Better brain health may be associated with higher self‐reported sleepiness via better cognition and self‐awareness in those who are not at increased risk of developing AD.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.040
GPT teacher head0.301
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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