Sleep and cognition in individuals with mild cognitive impairment and subjective cognitive decline
Bibliographic record
Abstract
Background: Sleep and circadian rhythm disorders are potential markers of neurodegenerative diseases, especially for Alzheimer’s disease (AD). Poor sleep is known to have a significant impact on cognitive function, and frequency and severity of sleep disturbance appear to follow the evolution of cognitive impairment. Few studies have addressed the relations of sleep quality and daytime sleepiness problems with cognitive functions in patients with milder stages of cognitive impairment. Objective: Investigate the possible association of sleep quality and daytime sleepiness with cognitive performance in individuals with Mild Cognitive Impairment (MCI) and Subjective Cognitive Decline (SCD), potential stages of Alzheimer’s continuum. Materials and Methods: This is a quantitative observational cross-sectional study, part of a broader project already approved by the ethics committee. Sixty-five individuals (42 women, mean age 65.8 ±6.4) with clinical diagnosis of MCI and SCD (NIA-AA criteria) were included in this investigation. To evaluate the sleep, we used the scores in quality assessment questionnaires of sleep quality and daytime sleepiness: Pittsburgh Sleep Quality Index (PSQI) and Epworth Sleepiness Scale (ESS), respectively. We also used the score in the following neuropsychological tests: Montreal Cognitive Assessment, Clock Drawing Test, Rey Auditory-Verbal Learning Test, Rey-Osterrieth Complex Figure Test (copy, immediate recall and delayed recall), Trail Making Test (TMT-A and TMT-B), Verbal Fluency Test and Boston Naming Test. For statistical analysis, we used a partial correlation test, controlled for age and education. The significance was considered in p< 0.05. Results: We found a negative and weak correlation between PSQI and ROCF copy (r=-0.379; p=0.002), PSQI and ROCF immediate recall (r=-0.271; p=0.031), PSQI and ROCF delayed recall (r=-0.31; p=0.014), and a weak and positive correlation between PSQI and TMT-A (r=0.38; p=0.002), all controlled for age and education. There were no other significant correlations. Conclusion: These results suggest a role for sleep in cognitive performance for patients with MCI and SCD. Higher PSQI score, indicating worse sleep quality, was associated with lower ROCF score in copy, immediate recall and delayed recall, representing poor performance in constructive praxis, visuospatial abilities and visual memory. Also, it was associated with higher time in TMT-A, indication of worse sustained attention. We conclude that poor sleep quality is correlated with cognitive dysfunction, and especially executive visual episodic memory and visuospatial functions in our sample. Future research, with a longitudinal design and objective sleep metrics may better investigate this bidirectional association between sleep and AD.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".