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Record W4390192493 · doi:10.1002/alz.072514

POINTER‐zzz: Study Design and Baseline Characteristics from the U.S. Study to Protect Brain Health Through Lifestyle Intervention to Reduce Risk (U.S. POINTER) Sleep Ancillary

2023· article· en· W4390192493 on OpenAlexaff
Kathleen M. Hayden, Margaret L. Scales, Marjorie Howard, Pankaja Desai, Xiaoyan Leng, Andrew Lim, Doris P. Molina‐Henry, Susan Redline, Heather M. Snyder, Katie L. Stone, Nancy Woolard, Mark A. Espeland, Laura D. Baker

Bibliographic record

VenueAlzheimer s & Dementia · 2023
Typearticle
Languageen
FieldMedicine
TopicObstructive Sleep Apnea Research
Canadian institutionsHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsDementiaMedicineCognitive declinePsychological interventionPhysical therapySleep apneaCognitionGerontologyDiseasePsychiatryInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background Sleep disordered breathing (SDB) leads to nocturnal hypoxemia and sleep disruption, which are linked to adverse health conditions, particularly in older adults at risk for dementia. Few prospective studies of SDB examine cognitive decline among those at increased risk for cognitive impairment and dementia. POINTER‐zzz, a sleep ancillary study of U.S. study to PrOtect brain health through lifestyle INTErvention to Reduce risk (U.S. POINTER), allows us to examine the role of lifestyle intervention on sleep quality, and potential moderating effects of sleep on cognition to the intervention in medically and cognitively vulnerable older adults. Method U.S. POINTER was designed to investigate the effects of two 2‐year lifestyle interventions on cognitive trajectories in 2,000 older, cognitively normal adults (aged 60‐79 yrs) at increased risk for cognitive decline and dementia due to physical inactivity, poor diet and cardiovascular disease. POINTER‐zzz enrolled a subset of parent trial participants and administered in‐home sleep assessments using WatchPAT (1 night) and ActiGraph (6 nights) devices. We summarize participants’ baseline characteristics including apnea hypopnea index (AHI), sleep duration and sleep efficiency. Result To date, 688 POINTER‐zzz participants enrolled and completed baseline WatchPAT and/or Actigraph assessments. Participant ages averaged 68.6 years old (standard deviation, 5.13); 21% of participants self‐identified as Black/African American, 4% Hispanic/Latino, and 66% White. More than half (68%) were female, and 69% had a Bachelor’s degree or higher. Overall, 87% of participants had at least mild sleep apnea (AHI>5). Severe sleep apnea (AHI≥30) was observed in 14% of participants overall, and 21% of those aged ≥75 yrs. Severe sleep apnea was more prevalent among males (19%) than females (11%). Overall, nightly sleep duration for the cohort averaged 6.6 hours, with 83% sleep efficiency, and an average of 79.3 minutes awake after sleep onset. Conclusion POINTER‐zzz participants have sleep characteristics that align with expectations for a cohort that is broadly representative of a diverse older adult population in the US. POINTER‐zzz provides an unparalleled opportunity to test the effects of a multi‐domain lifestyle intervention on sleep disturbances that are linked to cognitive decline and AD in a well‐characterized, diverse cohort of at‐risk older adults.

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)0.004
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: Observational
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.002

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 head0.052
GPT teacher head0.356
Teacher spread0.304 · 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
GenreProtocol

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
Published2023
Admission routes1
Has abstractyes

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