Rivastigmine for mild cognitive impairment in Parkinson disease: A placebo‐controlled study
Bibliographic record
Abstract
Mild cognitive impairment (MCI) in Parkinson's disease (PD) may be associated with subtle functional impairment and worse quality of life. The objective of this study was to determine the efficacy and tolerability of rivastigmine for PD-MCI. Patients with PD-MCI (n = 28) were enrolled in a 24-week, randomized, double-blind, placebo-controlled, crossover, single-site study of the rivastigmine transdermal patch. The primary outcome measure was the Alzheimer's Disease Cooperative Study-Clinical Global Impression of Change (ADCS-CGIC). Secondary outcomes included the Montreal Cognitive Assessment (MoCA), Dementia Rating Scale-2 (DRS-2), Neurotrax computerized cognitive battery, the Everyday Cognition Battery (ECB), and the Parkinson's Disease Questionnaire (PDQ-8). Twenty-six participants (92.9%) completed both study phase assessments, and 23 (82.1%) completed both phases on study medication. The CGIC response rate demonstrated a trend effect in favor of rivastigmine (regression coefficient for interaction term in linear mixed-effects model = 0.44, F[df] = 3.01 [1, 24], P = 0.096). For secondary outcomes, a significant rivastigmine effect on the ECB (regression coefficient = -2.41, F[df] = 5.81 [1, 22.05], P = 0.03) was seen, but no treatment effect was found on any cognitive measures. Trend effects also occurred in favor of rivastigmine on the PDQ-8 (regression coefficient = 4.55, F[df] = 3.93 [1, 14. 79], P = 0.09) and the State Anxiety Inventory (regression coefficient = -1.24, F[df] = 3.17 [1, 33], P = 0.08). Rivastigmine in PD-MCI showed a trend effect for improvements on a global rating of cognition, disease-related health status, and anxiety severity, and significant improvement on a performance-based measure of cognitive abilities. © 2015 International Parkinson and Movement Disorder Society.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".