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Record W4416707624 · doi:10.5327/cbn241493

Sleep and cognition in individuals with mild cognitive impairment and subjective cognitive decline

2024· article· W4416707624 on OpenAlexaboutno aff
Tania Aparecida Marchiori, Liara Rizzi, Isadora Cristina Ribeiro, Ítalo Karmann Aventurato, Marjorie Cristina Rocha da Silva, Brenda Costa Gonçalves, Márcio Luiz Figueredo Balthazar

Bibliographic record

VenueArquivos de Neuro-Psiquiatria · 2024
Typearticle
Language
FieldPsychology
TopicSleep and related disorders
Canadian institutionsnot available
Fundersnot available
KeywordsPittsburgh Sleep Quality IndexEpworth Sleepiness ScaleCognitionVerbal fluency testNeuropsychologyCognitive declineRecallSleep (system call)Effects of sleep deprivation on cognitive performanceExcessive daytime sleepiness

Abstract

fetched live from OpenAlex

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.

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)0.002
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.012
GPT teacher head0.287
Teacher spread0.275 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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