Safety and Tolerability of Pardoprunox, a New Partial Dopamine Agonist, in a Randomized, Controlled Study of Patients with Advanced Parkinson’s Disease
Bibliographic record
Abstract
AIMS: To investigate the safety and tolerability of pardoprunox (SLV308), a novel partial dopamine agonist, as an adjunct to levodopa in patients with advanced Parkinson's disease, using two titration schedules. METHODS: Patients were randomized to pardoprunox (n = 51) or placebo (n = 11). Pardoprunox was titrated to the highest tolerated dose (range, 0.3-42 mg/day) over 7 weeks, using a gradual dose escalation without intermediate steps (group 1) or with intermediate steps (group 2). RESULTS: The cumulative drop-out rate was greater in group 1 (without intermediate steps, 56.0%) than in group 2 (with intermediate steps, 34.6%), or with placebo (9.1%). In group 2, doses up to 18 mg/day were well tolerated with a cumulative drop-out rate of 7.7% (2/26) and a drop-out rate due to adverse events of 4.0% (1/26). The most common adverse events reported were nausea, vomiting, headache, and dizziness. There was a trend for reduced OFF time (p = 0.054) in the combined pardoprunox group compared to placebo. CONCLUSIONS: The pardoprunox safety and tolerability profile as an adjunct to levodopa was improved using a gradual titration schedule that included intermediate dose steps. Using this titration, doses up to 18 mg/day were well tolerated.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 | 0.000 |
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".