Cognition affects gait adaptation after split-belt treadmill training in Parkinson's disease
Bibliographic record
Abstract
BACKGROUND: Split-belt treadmill (SBTM) training has been proposed to improve gait symmetry and overall gait performance of patients with Parkinson's disease (PD). OBJECTIVES: To determine whether patient's baseline features affect gait adaptation to SBTM in PD with freezing of gait (FOG). METHODS: Twenty participants with idiopathic PD and treatment-resistant FOG underwent several clinical assessments including the Toronto Cognitive Assessment (TorCA) prior to treadmill training. Velocity of the treadmill was adjusted to over-ground walking speed. During SBTM training, the belt velocity on the least-affected side was reduced by 25%. RESULTS: Participants who adapted to SBTM training demonstrated cognitively intact TorCA scores (p < 0.001), particularly intact working memory (p < 0.001). After-effects correlated with normal total TorCA (p = 0.02), working memory and visuospatial (p < 0.001) function. CONCLUSIONS: Cognitive impairment, particularly impaired working memory, reduces gait adaptation and after-effects in PD with FOG. This is informative for trials studying prolonged effects of SBTM training in FOG.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".