Effects of dopaminergic medication on upper limb motor function, strength and hand dexterity in people with Parkinson’s disease
Bibliographic record
Abstract
Background: Dopaminergic medications improve motor symptoms and hand dexterity in people with Parkinson's disease (PD). The contribution of altered muscle contractile properties to these functional improvements are not well understood. Objective: To compare the treated (ON) and untreated (OFF) states in people with PD to examine effects of dopaminergic medication on hand dexterity, motor symptom severity, muscle twitch properties and maximal voluntary contraction (MVC). Methods: Sixteen individuals with PD (mean disease duration 6.4 years) completed two sessions: one ON and one OFF dopaminergic medication. Measures included motor symptom severity (MDS-UPDRS III), Grooved Pegboard Test (GPT) time, Purdue Pegboard Test (PPT) peg count, elbow flexion MVC, voluntary activation, and electrically induced twitch properties. Results: MDS-UPDRS III subscores improved by 27 % ON dopaminergic medication compared to OFF medication, and performance improved on GPT (11 %) and PPT (34 %; p < 0.05). Comparing ON and OFF states, electrically induced contractile properties did not differ, while voluntary elbow flexor MVC increased by 4 %. Normalized MVC was moderately associated with GPT and PPT performance in both ON (GPT: r = -0.48, PPT: r = 0.48) and OFF (GPT: r = -0.61, PPT: r = 0.45) states. Motor symptom severity in the OFF state showed moderate correlations with GPT (r = 0.48) and PPT (r = -0.58), but these associations were not significant in the ON phase (p > 0.05). Conclusion: Dopaminergic treatment improved motor symptoms, hand dexterity, and strength, without altering electrically induced contractile properties. Improved hand dexterity during treatment appears to be linked to strength gains independent of peripheral muscle changes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".