Ten‐year follow‐up of Parkinson's disease patients randomized to initial therapy with ropinirole or levodopa
Bibliographic record
Abstract
In a 5-year, double-blind study, subjects with Parkinson's disease (PD) who were randomized to initial treatment with ropinirole had a significantly lower incidence of dyskinesia compared with subjects randomized to levodopa, although Unified Parkinson's Disease Rating Scale (UPDRS) motor scores were significantly more improved in the levodopa group. Subjects who completed the original study were eligible to participate in a long-term extension study conducted according to an open, naturalistic design and were evaluated approximately every 6 months until they had been followed for a total of 10 years. Comparing subjects randomized to initial treatment with ropinirole (n = 42) and levodopa (n = 27), the incidence of dyskinesia was significantly lower in the ropinirole group (adjusted odds ratio [OR] = 0.3; 95% confidence interval [CI]: 0.1, 1.0; P = 0.046) and the median time to dyskinesia was significantly longer (adjusted hazard ratio = 0.4; 95% CI: 0.2, 0.8; P = 0.007). The incidence of at least moderate wearing off ("off" time >/=26% of the awake day) was also significantly lower in the ropinirole group (adjusted OR = 0.3; 95% CI: 0.09, 0.03; P = 0.03). There were no significant differences in change in UPDRS activities of daily living or motor scores, or scores for the 39-item PD questionnaire, Clinical Global Impression, or the Epworth Sleepiness Scale. Early treatment decisions for individual patients depend largely on the anticipated risk of side effects and long-term complications. Both ropinirole and levodopa are viable treatment options in early PD.
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) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".