Longitudinal association between daytime sleepiness and cognitive decline in dementia: A study protocol
Bibliographic record
Abstract
Introduction Dementia is a major cause of disability worldwide. About 25%-40% of patients with mild to moderate dementia are affected by sleep-awake cycle disturbances, including increased daytime sleepiness and insomnia. However, little is known about the specific impact of excessive daytime sleepiness on the cognitive decline of dementia patients. Objectives To evaluate the impact of daytime sleepiness on the cognitive decline of dementia patients. Additionally, longitudinal associations with functional impairment and neuropsychiatric symptoms will be explored. Methods A longitudinal study will be conducted in a psychogeriatric consultation. Patients will be consecutively invited according to predefined eligibility criteria. Those aged ≥65 years, with dementia diagnosis or Mini-Mental State Examination (MMSE) <24, and with a knowledgeable caregiver, will be included. The exclusion criteria are: a caregiver <18 years, terminally ill, incapable to communicate or with a known diagnosis of insomnia, sleep related respiratory disorders, central hyperinsomnia, restless legs syndrome or sleep paralysis. Participants will undergo an assessment with a comprehensive protocol including: Montreal Cognitive Assessment (MoCA), Barthel and Lawton Index, Epworth Sleepiness Scale (ESS), Neuropsychiatric Inventory (NPI) and Global Deterioration Scale (GDS). Participants will be re-assessed 6 months after the initial evaluation. The Health Ethics Committee of Hospital Universitário de São João granted the study authorization (nº 260/2020). Results Findings will be disseminated via publication in peer-reviewed journals and presentations at national and international scientific conferences. Conclusions This study will address key questions on the relation of daytime sleepiness and dementia outcomes, in order to undertake corrective and preventive non-pharmacological and pharmacological approaches.
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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 | 0.034 | 0.015 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.038 | 0.009 |
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".