The Effect of Rotigotine on Cognitive Function, Daytime Sleepiness, and Sleep Problems in Parkinson Disease: An Open-Label Pilot Study
Bibliographic record
Abstract
BACKGROUND: We hypothesized that rotigotine may have a positive effect on cognitive function in patients with Parkinson disease (PD) by improving daytime motor function and sleep status. METHODS: Fifteen PD patients with sleep disturbances, defined as a PD Sleep Scale (PDSS)-2 score of 15 or greater, were included in this single-center, 3-month open-label study. Participants received 2 to 4 mg/24 h (patch content: 4.5-9 mg) rotigotine for a 3-month period. At baseline and 3 months, the patients were evaluated on the Movement Disorder Society Revision of the Unified PD Rating Scale (MDS-UPDRS) parts III and IV and cognitive assessments, such as the Mini-Mental State Examination, frontal assessment battery, and Montreal Cognitive Assessment (MoCA). The Epworth Sleepiness Scale (ESS) and PDSS-2 were administered at baseline and at 1, 2, and 3 months. RESULTS: At 3 months, the MDS-UPDRS part III (-11.1, P < 0.0001) and MDS-UPDRS part IV (-1.1, P = 0.0013) scores significantly decreased, and off time significantly decreased (-34.6 minutes, P = 0.0085) from baseline. The PDSS-2 scores significantly decreased from baseline at 1 month (-4.2, P < 0.01), 2 months (-7.7, P < 0.0001), and 3 months (-7.3, P < 0.0001). The ESS also decreased at 1 month (-2.5, P < 0.05) and 3 months from baseline (-4.5, P < 0.01). The MoCA scores (1.6, P = 0.0029) significantly improved, but the Mini-Mental State Examination or frontal assessment battery scores did not significantly change. The mean changes from baseline to 3 months in the MoCA were negatively correlated with mean changes in the ESS scores. CONCLUSIONS: We suggest that rotigotine could improve cognitive function by improving motor symptoms, sleep disturbance, and daytime sleepiness in patients with PD.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".