Impaired Fine Motor Function of the Asymptomatic Hand in Unilateral Parkinson’s Disease
Bibliographic record
Abstract
The early detection of Parkinson’s disease (PD) still remains a challenge to date. Although studies have previously reported subtle motor function abnormalities in early PD patients, it is unclear whether such clinical signs can be better detected while patients are concurrently performing a cognitive task, and whether they can be useful in predicting patients’ clinical conversion state. Seventy-two right-handed participants (40 drug-naive patients with idiopathic unilateral PD and 32 age-matched healthy controls) were enrolled in this study. All participants were asked to perform the Purdue Pegboard test (PPT) either alone (single-task condition) or during a concurrent mental subtraction-by-3 task (dual-task condition). A 4-year telephone follow-up was later conducted to determine whether PD patients converted to bilateral signs. We found that PD patients showed a significant reduction in dexterity on the PPT compared to the controls in both single- and dual-task conditions. Yet patients’ performance in the dual-task condition revealed a greater interference effect when patients performed the task with their right hand than with their left hand. PPT also revealed reasonable discriminative ability for prediagnosing PD. However, dual-tasking did not have added value in differentiating early patients and controls. At follow-up, the baseline PPT performance of the asymptomatic hands was positively correlated with time to convert from unilaterally to bilaterally affected states (r =0.62, P = 0.031). Together, these findings suggest that PPT can serve as a useful auxiliary tool in evaluating early PD, and shed light on the neuroplasticity mechanism of fine motor deficit at this very early stage.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".