The Complex Interplay between Sleep and Neurodegenerative Diseases: An Epidemiological View
Bibliographic record
Abstract
BACKGROUND: Sleep disorders and neurodegeneration (NDG) are mutually related but the nature of this relationship is unclear. We aimed to better understand the relationship between sleep and neurodegenerative disease by performing a critical review of epidemiological studies that investigated the association of sleep disorders and the subsequent development of Alzheimer's disease (AD), Parkinson's disease (PD), or general dementia. METHODS: We searched for all case-control or prospective cohort studies published in PubMed until August 8 2024 evaluating a series of sleep features and subsequent development of AD, PD, or general dementia over certain observation periods. Patient data, sleep features, and outcome data related to PD, AD, and general dementia were extracted following the PRISMA guidelines. Relative risks for the different NDG diseases were extracted. Study quality was assessed with the Newcastle-Ottawa quality assessment scale. RESULTS: Of 1,139 identified articles 52 were selected from 30 independent studies (29 cohort and one case-control study), including >2.9 million individuals with follow-up periods ranging from 3 to 40 years. The included articles reported on 18,765 AD outcomes, 14,312 PD outcomes, and 100,453 dementia outcomes. Forty-five articles were classified as having a high-quality. Despite that, there was a great variability in the main aim of the studies, the sleep features evaluated, the diagnostic system employed, or the duration of the follow-ups. Only twelve studies assessed sleep with objective measures. The influence of sleep duration and sleep quality, chronotype, and the presence of excessive daytime sleepiness, insomnia, obstructive sleep apnea, snoring, restless legs syndrome showed varying risk ratios or no statistically significant association with PD, AD, and dementia over time. CONCLUSION: Our systematic review underlines the need for further comprehensive epidemiological studies with homogenous and objective sleep measures to evaluate the different sleep features and understand the relationship between sleep and NDG disease.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".