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Record W3112613046 · doi:10.1002/alz.047548

Effects of early surgical menopause on sleep, memory, and medial temporal lobe structure at midlife

2020· article· en· W3112613046 on OpenAlexaff
Nicole Gervais, Claire Lauzon, Alana Brown, Laura Gravelsins, Gina Nicoll, Elizabeth Baker‐Sullivan, Anne Almey, Rebekah Reuben, Annie Duchesne, Leanne Mendoza, Mateja Perović, Courtney Kannampuzha, Cheryl L. Grady, Rosanna K. Olsen, Gillian Einstein

Bibliographic record

VenueAlzheimer s & Dementia · 2020
Typearticle
Languageen
FieldMedicine
TopicMenopause: Health Impacts and Treatments
Canadian institutionsUniversity of Northern British ColumbiaBaycrest HospitalUniversity of Toronto
Fundersnot available
KeywordsEntorhinal cortexAtrophyMedicineDementiaTemporal lobeCognitive declineMenopauseAudiologyPsychologyPolysomnographySleep disorderHippocampusInternal medicineCognitionNeuroscienceDisease

Abstract

fetched live from OpenAlex

Abstract Background Women bear the greatest burden of Alzheimer’s disease (AD) with menopause‐associated estrogen (E) loss becoming increasingly implicated. Surgical menopause <45 years of age (via bilateral salpingo‐oophorectomy, BSO) is thought to further increase the risk (Rocca et al., 2007). Neurodegeneration and atrophy in medial temporal lobe (MTL) structures including the perirhinal (PRC) and entorhinal (ERC) cortices occur in the very early stages of AD (e.g. Khan et al., 2013; Wolk et al., 2017). Further, sleep disturbance is also implicated in AD progression (Lim et al., 2013). Unknown is whether BSO‐associated sleep disturbance contributes to reduced memory performance and MTL atrophy via sleep disturbance, and whether E2 supplementation influences this relation. Our study aimed to determine the effect of early hormone deprivation (via BSO) on MTL volume, visual recognition memory, and whether this is correlated with sleep disturbance. Method Demographic and cognitive measures were administered to women with an oophorectomy <45 years who were either taking estradiol‐based hormone therapy (BSO+E2: n=19), or not taking E2 (BSO no E2: n=15). Data was also collected from age‐matched premenopausal women (AMC: n=27). High‐resolution T2‐weighted scans were acquired using a Siemens 3T Prisma scanner, and hippocampal subfields, PRC, ERC, and parhippocampal cortex were manually segmented (Olsen et al., 2017) in FSLView. The interference match‐to‐sample (IMTS) task was used to asses and recognition memory (Watson et al., 2013). Sleep was assessed using an at‐home polysomnography device (Vitaport‐5/REMbo‐234, Temec Technologies). Result Relative to AMCs, the BSO no E2 group had smaller volumes in the dentate gyrus, CA2, and CA3 (DGCA23) (p<.05, d=1.03). Relative to BSO+E2 women with BSO no E2 had reduced recognition memory performance (p<.05; d=1.36) and their sleep was more disrupted, indicated by increased sleep latency (p<.05, d=.71), and cortical arousals ( p<.05, d=.87]. DGCA23 volume and nighttime arousals were correlated negatively (r=‐.503, p<.05). Conclusion Our findings demonstrate that HPC, recognition memory, and sleep are sensitive to E2 loss and suggest that reduced HPC volume relates to disrupted sleep. Taken together these findings begin to explicate the path from early menopause to late‐life dementia and the importance of E2 for women’s brain health.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.025
GPT teacher head0.290
Teacher spread0.264 · 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".

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Citations1
Published2020
Admission routes1
Has abstractyes

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