Sleep disordered breathing during REM sleep is associated with cognitive impairment a decade later
Bibliographic record
Abstract
Objective: Sleep Disordered Breathing (SDB) during rapid eye movement (REM) sleep is associated with cardiovascular and metabolic risk. We examined the association between ODI4% during REM sleep and cognitive impairment over 10-12 years. Methods: Data from a racially diverse community-based prospective cohort assessing cardiovascular risk were analyzed. REM SDB severity was measured using a polysomnography (PSG) derived oxygen desaturation index (ODI4%; desaturation events ≥4 % from baseline per hour of sleep). Cognition was evaluated 10-12 years after PSG using the Montreal Cognitive Assessment (MoCA). A MoCA score of <27 indicated impaired cognitive function. Results: Participants were 220 middle-aged adults (mean age 58±7), 108 (49% female), and 94 (43% Black). Moderate-severe SDB during REM sleep (REM ODI4% ≥ 15) had a higher prevalence of hypertension (70% versus 31%, OR=2.2, 95% CI 1.6-3.3, p<0.01) and a higher body mass index (32.4±5.3 versus 28.2±4.8, p<0.01) when compared to those without REM-OSA (REM ODI4%<5). In a univariate model, moderate-severe REM-SDB (REM ODI4%≥15) was associated with cognitive impairment (47.4% versus 28.4%; OR=2.3, 95% CI 1.0-5.2, p=0.05). In a multivariable model, individuals with moderate-severe REM-SDB had higher odds of having cognitive impairment compared to those without REM-SDB (adjusted OR=3.22, 95% CI 1.2-10.0, p=0.02). Moderate-severe SDB determined by total ODI4%≥15 and non-REM ODI4%≥15 were not significantly associated with cognitive impairment in any of the models. Conclusion: In a racially diverse community cohort of middle-aged adults, moderate-severe REM-ODI4% was associated with cognitive impairment a decade later.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".