Sleep Disturbances Predict Cognitive Decline in Cognitively Healthy Adults
Bibliographic record
Abstract
BACKGROUND: The effect of nighttime behaviors on cognition has not been studied independently from other neuropsychiatric symptoms. OBJECTIVE: We evaluate the following hypotheses that sleep disturbances bring increased risk of earlier cognitive impairment, and more importantly that the effect of sleep disturbances is independent from other neuropsychiatric symptoms that may herald dementia. METHODS: We used the National Alzheimer's Coordinating Center database to evaluate the relationship between Neuropsychiatric Inventory Questionnaire (NPI-Q) determined nighttime behaviors which served as surrogate for sleep disturbances and cognitive impairment. Montreal Cognitive Assessment scores defined two groups: conversion from 1) normal to mild cognitive impairment (MCI) and 2) MCI to dementia. The effect of nighttime behaviors at initial visit and covariates of age, sex, education, race, and other neuropsychiatric symptoms (NPI-Q), on conversion risk were analyzed using Cox regression. RESULTS: Nighttime behaviors predicted earlier conversion time from normal cognition to MCI (hazard ratio (HR): 1.09; 95% CI: [1.00, 1.48], p = 0.048) but were not associated with MCI to dementia conversion (HR: 1.01; [0.92, 1.10], p = 0.856). In both groups, older age, female sex, lower education, and neuropsychiatric burden increased conversion risk. CONCLUSION: Our findings suggest that sleep disturbances predict earlier cognitive decline independently from other neuropsychiatric symptoms that may herald dementia.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".