Sleep disorders in a sample of Egyptian patients with Parkinson's disease: a case–control polysomnography study
Bibliographic record
Abstract
Abstract Background Up to 96% of patients with Parkinson's disease (PD) experience sleep disturbances, which can emerge before motor symptoms. This study aims to determine the type of sleep disturbances in PD compared to controls using Parkinson's Disease Sleep Scale-2 (PDSS-2) and polysomnography (PSG). Twenty-four PD patients with sleep difficulties and 24 matched controls were included in this prospective case–control study. Sleep disturbances were diagnosed using screening questionnaires and PDSS-2. Patients were clinically assessed using Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS). All participants were evaluated using Beck Depression Inventory (BDI), Montreal Cognitive Assessment (MoCA), and full-night video PSG. Results The PD group had significantly higher BDI and lower MoCA scores than the controls. PD patients had significantly lower sleep efficiency (87.32% versus 95.48%) and longer sleep latency (29 versus 2.45 min), shorter REM latency (37.97 versus 78.94 min), higher N2 sleep percentage (65.32% versus 51.43%), and lower REM sleep percentage (15.89% versus 19.22%). PD patients also had a higher arousal index (11.35 ± 9.46/h versus 3.44 ± 2.93/h), more periodic leg movements (7 ± 6.64 versus 2.21 ± 2.39), and a higher apnea–hypopnea index (7.96 ± 4.91 versus 4.12 ± 3.71). Sleep latency showed a negative correlation with MoCA and a positive correlation with disease duration. REM sleep percentage was negatively correlated with BDI. Arousal index /hour was negatively correlated with age onset. Conclusions This study confirms significant sleep architecture differences between PD patients and controls, emphasising the importance of comprehensive sleep assessment and management in PD care. Trial registration: The study was registered prospectively on 25/10/2022 at the clinicaltrial.gov website with the registration ID: NCT05599035, https://clinicaltrials.gov/study/NCT05599035 .
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".