Effects of 24 wk of Treadmill Training on Gait Performance in Parkinson’s Disease
Bibliographic record
Abstract
PURPOSE: Recent studies suggest that walking on a treadmill improves gait, mobility, and quality of life of patients with Parkinson's disease (PD). Still, there is a need for larger-scale randomized controlled studies that demonstrate the advantages of treadmill training (TT) with control groups that receive similar amounts of attention. Moreover, to date, no study has combined speed and incline as parameters of progression. The aim of the study was to evaluate the effects of 24 wk of TT, with and without the use of incline, on gait, mobility and quality of life in patients with PD. METHODS: The sample comprised 34 patients with PD, at the Hoehn and Yahr stage 1.5 or 2. Participants were randomized to speed TT, mixed TT, and control groups. The intervention consisted of 72 one-hour exercise sessions for 24 wk. The main outcome measures are the Movement Disorder Society-Unified Parkinson's Disease Rating Scale, the 39-item Parkinson's Disease Questionnaire, spatiotemporal parameters of gait and 6-min walking distance. The measures were taken at baseline, mid-term and after 6 months. RESULTS: Both TT groups improved in terms of speed, cadence, and stride length during self-selected walking conditions at the study end point. Both groups also showed improvements in distance traveled. Only the Mixed TT group improved their quality of life. The Control group showed no progress. CONCLUSIONS: Participants in this study showed significant improvements in walking speed and walking endurance after 6 months of TT. Improvements were observed after 3 months of intensive TT and persisted at 6 months. It appears that individuals with poorer baseline performance may benefit most from TT.
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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) | 0.001 | 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) | 0.001 | 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".