Sleep Disorders as Predictors of Cognitive Decline and Dementia: A Systematic Review
Bibliographic record
Abstract
Abstract: Sleep disturbances are increasingly recognized as early indicatorsand potentially modifiable contributors to cognitive decline and dementia.This systematic review synthesizes evidence from 31 original studiespublished between 2015 and 2025, encompassing observational, populationbased,and interventional designs. Consistent findings indicate that insomniaand obstructive sleep apnoea (OSA) are associated with increased risk ofcognitive decline and dementia, with hazard ratios ranging from 1.36 to 1.84.Mechanistic studies show that insomnia accelerates amyloid-β and tauaccumulation through impaired glymphatic clearance andneuroinflammation, while OSA contributes via intermittent hypoxia,oxidative stress, and cerebrovascular dysfunction. Circadian rhythmdisturbances, hypersomnia, and REM sleep behaviour disorder (RBD) werealso linked to cognitive impairment, particularly non-Alzheimer dementiassuch as Lewy body and front temporal dementia. Interventional evidencesuggests that continuous positive airway pressure (CPAP) and cognitivebehavioural therapy for insomnia (CBT-I) improve cognitive outcomes andmay mitigate dementia risk. Study quality was appraised using theNewcastle–Ottawa Scale and Cochrane RoB-2 tools, and overall certainty ofevidence was evaluated using the GRADE framework, indicating low-tomoderateconfidence in current findings. This review provides an updated,integrative synthesis highlighting sleep disorders as biologically plausible,clinically actionable, and underutilized targets for dementia prevention.Future large-scale, biomarker-based randomized trials are essential toconfirm causality and strengthen the evidence base for sleep-focuseddementia risk reduction.Keywords: Sleep disorders; Insomnia; Obstructive sleep apnoea; Cognitivedecline; Dementia; REM sleep behaviour disorder; Circadian rhythm;Neurodegeneration
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".