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Record W6907619581 · doi:10.25384/sage.c.7228483

Interrelationship of Sleep Disturbances and Cognitive Status on Mortality

2024· other· en· W6907619581 on OpenAlexaboutno aff

Bibliographic record

VenueSage Journals Data · 2024
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsSleep (system call)CognitionSleep disorderCognitive impairmentProportional hazards modelSurvival analysisCognitive decline

Abstract

fetched live from OpenAlex

Sleep disturbances may promote the development and advancement of Alzheimer’s disease. Our purpose was to determine if sleep disturbances were associated with earlier mortality while accounting for cognition. The National Alzheimer’s Coordinating Center database was used to evaluate mortality risk conferred by sleep, and the Montreal Cognitive Assessment score determined cognitive status. Demographics, sleep disturbances, cognitive status, and comorbid/other neuropsychiatric conditions were examined as predictors of survival time via Cox regression. The sample (N = 31,110) had a median age [interquartile range] of 72 [66, 79] years, MoCA score of 23 [16, 26], and survival time of 106.0 months [104.0,108.0]; 10,278 (33%) died during follow-up; 21% (n = 6461) experienced sleep disturbances. Sleep disturbances impacted survival time depending on cognition, with the greatest effect in transition from normal to cognitive impairment (P < .001). Findings support that sleep disturbances negatively impact survival time, and the impact of sleep disturbances on survival time is interrelated with cognition.

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)0.005
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: Other · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.126
GPT teacher head0.398
Teacher spread0.272 · 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
GenreOther

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
Published2024
Admission routes1
Has abstractyes

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Same venueSage Journals DataFrench-language works237,207