Opicapone in Parkinson's Disease on Levodopa‐Carbidopa Intestinal Gel Treatment: A Pilot, Randomized Study
Bibliographic record
Abstract
BACKGROUND: Levodopa-carbidopa intestinal gel infusion (LCIG) is an effective therapy for advanced Parkinson's disease (PD). Opicapone (OPC) is an enzyme inhibitor that enhances the bioavailability of levodopa in the brain. OBJECTIVES: This study evaluates the effect of Opicapone addition in PD-LCIG patients, assessing its impact on motor fluctuations and dyskinesias. Secondly, the study analyses the impact of OPC on non-motor symptoms, LCIG dosage, and peripheral neuropathy. METHODS: In this pilot study, 22 PD patients on LCIG were randomized to receive OPC or not, based on persistent or reemergent fluctuations. The Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS), Unified Dyskinesia Rating Scale (UDysRS), Montreal Cognitive Assessment (MoCA), electroneurography (ENG), LCIG doses, homocysteine, vitamin B12, and folic acid levels were measured at baseline (T0) and after 12 months (T1). RESULTS: Eleven patients added OPC (addOPC group), while 11 maintained standard treatment (nOPC group). At baseline, both groups had similar disease duration and severity. At T1, the addOPC group showed significant: (i) improvement in motor fluctuations evaluated by the MDS-UPDRS part IV; (ii) reduction in dyskinesias (UDyRS); (iii) decrease in LCIG infusion rate; (iv) improvement in motor and non-motor symptoms (MDS-UPDRS parts I-III); (v) increase in Vitamin B12. No significant differences were observed in the ENG data, and no serious adverse events occurred. Four addOPC patients (36%) discontinued OPC after 15 ± 2 months, mainly due to hallucinations. CONCLUSIONS: OPC addition appeared well tolerated and beneficial in reducing motor fluctuations, dyskinesia, and LCIG dose. Randomized controlled trials are needed to confirm these findings.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".