The Combined Use of Levodopa/Benserazide and Pramipexole Proves Beneficial for Managing Parkinson's Disease
Bibliographic record
Abstract
BACKGROUND: Parkinson's disease (PD), a prevalent neurological condition, is characterized by the progressive degeneration of dopamine-producing neurons, leading to motor dysfunction and non-motor symptoms. Therefore, this study aimed to evaluate the impact of combining levodopa/benserazide with pramipexole on PD patients, focusing on cognitive function, plasma monoamine neurotransmitter levels, and serum growth differentiation factor-15 (GDF-15) and angiopoietin-1 (Ang-1) levels. METHODS: This retrospective study included 120 PD patients admitted to the hospital between January 2021 and January 2023. Based on the treatment approaches, the patients were categorized into the control group (n = 61) and the observation group (n = 59). The control group received oral levodopa/benserazide tablets, while the observation group was treated with levodopa/benserazide tablets combined with pramipexole. The two experimental groups were assessed and compared across several parameters, including PD symptoms [Unified Parkinson's Disease Rating Scale (UPDRS)], cognitive function [Montreal Cognitive Assessment (MoCA)], the levels of plasma monoamine neurotransmitters, and serum GDF-15 and Ang-1 levels. RESULTS: The response rate to treatment was more significant in the observation group (96.55%) compared to the control group (87.93%, p = 0.162). Post-treatment, both groups demonstrated a decline in their UPDRS and overall scores, with the observation group indicating substantially lower scores than the control group (p < 0.05). Furthermore, both groups showed improvements in MoCA scores, with the observation group exhibiting higher scores than the control group (p < 0.05). Similarly, we observed significantly increased dopamine, 5-hydroxytryptamine, and norepinephrine levels in both groups, with the observation group showing a more pronounced increase (p < 0.05). Additionally, we observed a significant decrease in serum GDF-15 levels and an increase in Ang-1 levels across both groups after treatment. However, the observation group exhibited lower GDF-15 levels and higher Ang-1 levels than the control group (p < 0.05). CONCLUSIONS: The combined use of levodopa/benserazide and pramipexole proves beneficial for managing PD. This therapeutic regimen can improve cognitive abilities and plasma monoamine neurotransmitter levels in PD patients, reduce brain tissue damage and decrease serum levels of GDF-15.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".