Polysomnography results and cognitive performance in early‐stage Parkinson’s disease
Bibliographic record
Abstract
Abstract Background Parkinson’s disease (PD) is a progressive neurological disorder that involves a range of motor and non‐motor symptoms. About 66% of individuals with PD report sleep disturbance impacts their quality of life. Sleep disorders may precede the cardinal motor features in PD and can influence motor and non‐motor symptom severity, including cognition. Yet current evidence of this association with objective assessments remains limited. The goal of this pilot study was to evaluate the associations between cognition and overnight polysomnography results in early‐stage PD. Methods Participants completed neuropsychological assessments and an overnight in‐clinic polysomnography. Associations between polysomnography results and cognitive performance were evaluated using partial correlations controlling for age and education. Results Twenty participants (mean age 69±8; 25% female) without dementia and with a diagnosis of early‐stage PD (Hoehn and Yahr stage 1‐2) were enrolled (Table 1). Table 2 displays the associations between polysomnography results and cognitive assessments. Greater percentage time in stage N1 sleep and increased duration of wakefulness time after sleep onset (WASO) were associated with poorer phonemic fluency (r = ‐0.626, p = .005 and r = ‐0.512, p = .030, respectively); whereas increased time spent in stage N2 sleep and higher sleep efficiency index were correlated with better phonemic fluency (r = 0.829, p < .001 and r = 0.513, p = .029, respectively). Greater percentage in stage N2 was associated with better verbal learning (Hopkins Verbal Learning Test–Revised (HVLT‐R) Immediate Recall, r = 0.521, p = .027). Higher percent time in REM sleep was correlated with increased basic attention (Digit Span Forward, r = 0.483, p = .042). No associations were found between total sleep time and cognitive performance. Conclusion While total sleep time was not associated with cognition, higher percent time spent in Stage N2, Stage N3, and REM sleep were associated with better cognitive performance. In contrast, higher percentage of Stage N1 sleep and increased duration of WASO were associated with poorer verbal fluency. The preliminary results highlight the importance of increased time in deeper stages of sleep for cognition in adults with early‐stage PD. Future longitudinal studies will be necessary to evaluate long‐term cognitive trajectories and transition to dementia in association with diminished sleep quality in Parkinson’s disease.
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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 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".