Reduced cognitive function in patients with Parkinson disease and obstructive sleep apnea
Bibliographic record
Abstract
<h3>Objective:</h3> To assess the association between obstructive sleep apnea (OSA) and nonmotor symptoms (NMS), including cognitive dysfunction, in patients with Parkinson disease (PD). <h3>Methods:</h3> Patients with idiopathic PD, recruited from a movement disorder clinic, underwent overnight polysomnography. OSA was defined as an apnea-hypopnea index (AHI) ≥15/h. PD severity was assessed using the Hoehn & Yahr (H&Y) scale and the Movement Disorder Society Unified Parkinson9s Disease Rating Scale (MDS-UPDRS). NMS were assessed using the Montreal Cognitive Assessment (MoCA), Epworth Sleepiness Scale (ESS), Fatigue Severity Scale, Apathy Scale, Beck Depression Inventory, Hospital Depression and Anxiety Scale, and PD sleep Scale. <h3>Results:</h3> Sixty-seven patients (61.2% male), mean age 64.4 (SD 9.9) years and motor MDS-UPDRS 21.9 (12.6) using levodopa equivalent dose (LED) 752.4 (714.6) mg/d, were studied. OSA occurred in 47 patients (61.6%, mean AHI 27.1/h, SD 20.2/h), and NMS in 57 patients (85%). ESS and MoCA were associated with the AHI (ESS β = 0.0670, <i>p</i> = 0.031; MoCA β = −0.0520, <i>p</i> = 0.043, adjusted for age, sex, body mass index, LED, and H&Y). ESS was associated with respiratory arousals (β = 0.1015, <i>p</i> = 0.011) and intermittent hypoxemia (β = 0.1470, <i>p</i> = 0.006). MoCA was negatively associated with respiratory arousals (β = −0.0596, <i>p</i> = 0.049) but not intermittent hypoxemia. <h3>Conclusions:</h3> OSA is associated with sleepiness and cognitive dysfunction in PD, suggesting that OSA may be a reversible contributor to these NMS. Further studies will be required to evaluate whether OSA treatment can improve excessive sleepiness and cognitive dysfunction in PD.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; a candidate call from one teacher head, 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".