Relationship between Cognitive Performance and Motor Dysfunction in Patients with Parkinson’s Disease: A Pilot Cross-Sectional Study
Bibliographic record
Abstract
The aim of this pilot cross-sectional study was to extensively investigate the relationships between cognitive performance and motor dysfunction involving balance and gait ability in patients with Parkinson's disease. Twenty subjects with Parkinson's disease underwent a cognitive (outcomes: Frontal Assessment Battery-Italian version, Montreal overall Cognitive Assessment, Trail Making Test, Semantic Verbal Fluency Test, and Memory with Interference Test) and motor (outcomes: Berg Balance Scale, 10-Meter Walking Test, 6-Minute Walking Test, Timed Up and Go Test performed also under dual task condition, and Unified Parkinson's Disease Rating Scale) assessment. Our correlation analyses showed that balance skills are significantly correlated with executive functions, cognitive impairment, and ability to switch attention between two tasks. Furthermore, functional mobility showed a significant correlation with cognitive impairment, verbal fluency, and ability to switch attention between two tasks. In addition, the functional mobility evaluated under the dual task condition showed a significant correlation with cognitive impairment and ability to switch attention between two tasks. These findings might help early identification of cognitive deficits or motor dysfunctions in patients with Parkinson's disease who may benefit from rehabilitative strategies. Future prospective larger-scale studies are needed to strengthen our results.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".