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Record W3112484180 · doi:10.1002/alz.041440

Pointer‐ZZZ: Sleep ancillary to U.S. Study to Protect Brain Health Through Lifestyle Intervention to Reduce Risk of Alzheimer's disease

2020· article· en· W3112484180 on OpenAlexaff
Doris Molina-Henry, Laura D. Baker, Nancy Woolard, Mark A. Espeland, Xiaoyan Leng, Andrew Lim, Susan Redline, Katie L. Stone, Kathleen M. Hayden

Bibliographic record

VenueAlzheimer s & Dementia · 2020
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineCognitive declinePsychological interventionDementiaActigraphyDiseaseGerontologyCognitionSleep (system call)Physical therapyPsychiatryInsomniaInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background Non‐pharmacological approaches that target modifiable risks through lifestyle interventions provide the most promising evidence to delay disease. In older adults, chronic sleep disturbances marked by sleep‐disordered breathing (SDB) and sleep fragmentation are associated with impaired hippocampal functioning, increased beta‐amyloid burden, and greater Alzheimer’s risk. These and other sleep abnormalities are associated with reduced vascular health. Although some evidence suggests that diet, exercise, and cardiovascular risk reduction can improve sleep and improved sleep benefits cognition in older adults, these effects have not been confirmed in a rigorous clinical trial. Methods The U.S. study to PrOtect brain health through lifestyle INTErvention to Reduce risk (U.S. POINTER), funded by the Alzheimer’s Association, was launched in the Fall of 2018. It is investigating whether lifestyle interventions ‐ Self‐Guided (SG) versus a Structured (STR) lifestyle intervention ‐ influence cognitive trajectories over 2 years in 2000 older cognitively normal adults (aged 60‐79 yrs) who are at increased risk for cognitive decline, Alzheimer’s disease and other dementias. The NIH‐funded POINTER‐zzz ancillary study adds in‐home objective sleep assessments for 700 participants to examine the effects of lifestyle modification and cardiovascular risk management on sleep disturbances that are linked to cognitive decline and Alzheimer’s disease and that may improve with U.S. POINTER interventions. Results POINTER‐zzz methods and study design will be presented, which will permit over 2000 objective sleep assessments to be completed over 2 years. These assessments will provide extensive oximetry and actigraphy data for analysis by lifestyle intervention group assignment. Sleep data will be examined relative to intervention effects on cognition and other parent trial and ancillary study outcomes, including MRI and amyloid/tau PET brain imaging. POINTER‐zzz leverages resources provided by the parent trial and other funded ancillary studies, and by well‐established collaborations with sleep experts. Conclusions POINTER‐zzz provides an unparalleled opportunity to test the effects of a multi‐domain lifestyle intervention on sleep abnormalities that are linked to cognitive decline and Alzheimer’s in a well‐characterized, diverse cohort of at‐risk older adults. The study may identify an effective strategy for improving sleep that could have important consequences for reduced risk of Alzheimer’s disease and related dementias.

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)0.005
metaresearch head score (Gemma)0.008
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0020.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0210.004

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 head0.032
GPT teacher head0.336
Teacher spread0.303 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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