Exploring obstructive sleep apnea and sleep architecture in Parkinson's disease motor subtypes
Bibliographic record
Abstract
INTRODUCTION: Parkinson's disease (PD) can be divided into motor subtypes: postural instability/gait difficulty (PIGD), tremor dominant, and indeterminate. This study aimed to assess differences in sleep structure and obstructive sleep apnea (OSA) between the PIGD and non-PIGD subtypes. METHODS: PD participants with or without OSA (defined as apnea-hypopnea index (AHI) ≥ 15 events/hour on overnight polysomnography) were included. Patients were separated into two groups: PIGD and non-PIGD. Linear regression was used to explore differences in sleep, AHI, and other respiratory parameters between groups (adjusted for variables determined a priori). Logistic regression adjusted for the same variables was used to determine if the proportion of patients with OSA differed across groups. Subset analyses were performed: subset 1 excluding patients on psychoactive medication; subset 2 excluding patients taking levodopa or dopaminergic agonists (DAs) at nighttime and subset 3 excluding patients on either of the abovementioned drugs. RESULTS: 146 participants were studied. The non-PIGD group had less N3 sleep compared to the PIGD group (12.4% vs 16.9% p = 0.06), reaching significance in subsets 1 and 3. The AHI was significantly lower in the PIGD group (p = 0.047), including when medication effects were removed (p < 0.05). OSA was more frequent in the non-PIGD group, but only significantly in subset 3 (adjusted OR 0.3, p = 0.04). CONCLUSION: OSA may be more severe in non-PIGD subtypes, and more frequent, in a subset free of psychoactive medication, and of levodopa and DAs, possibly owing to motor complications and dyskinesia. Future studies are required to confirm this.
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".