Sleep apnea and the risk of dementia: A systematic review and meta‐analysis
Bibliographic record
Abstract
Sleep apnea (SA) is potentially a modifiable risk factor for dementia. However, its associations to specific aetiologies of dementia remain uncertain. A systematic review and meta-analysis of cohort studies investigating the association between sleep apnea and specific aetiologies of dementia, including Alzheimer's disease (AD), Parkinson's disease (PD), Lewy body dementia (LBD), vascular dementia (VaD), and frontotemporal dementia (FTD) was performed. The use of biomarkers to support clinical diagnoses in eligible studies was collected. Eleven studies were included, comprising 1,333,424 patients. Patients with sleep apnea had an increased risk of developing any type of neurocognitive disorder (HR: 1.43 [95% CI 1.26-1.62]), Alzheimer's disease (HR: 1.28 [95% CI 1.16-1.41]), and Parkinson's disease (HR: 1.54 [95% CI 1.30-1.84]). No statistically significant association was found for vascular dementia. One study reported a two-fold increased risk for Lewy body dementia (HR: 2.06 [95% CI 1.45-2.91]). No studies investigated the risk for frontotemporal dementia and none of the studies reported results pertaining to biomarkers. Sleep apnea is associated with a significantly increased risk of dementia, particularly for Alzheimer's disease and Parkinson's disease, but not for vascular dementia. Future studies should look at the impact of sleep apnea on specific dementia biomarkers.
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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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.031 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".