Varied Overground Walking Training Versus Body-Weight-Supported Treadmill Training in Adults Within 1 Year of Stroke
Bibliographic record
Abstract
BACKGROUND: Although task-related walking training has been recommended after stroke, the theoretical basis, content, and impact of interventions vary across the literature. There is a need for a comparison of different approaches to task-related walking training after stroke. OBJECTIVE: To compare the impact of a motor-learning-science-based overground walking training program with body-weight-supported treadmill training (BWSTT) in ambulatory, community-dwelling adults within 1 year of stroke onset. METHODS: In this rater-blinded, 1:1 parallel, randomized controlled trial, participants were stratified by baseline gait speed. Participants assigned to the Motor Learning Walking Program (MLWP) practiced various overground walking tasks under the supervision of 1 physiotherapist. Cognitive effort was encouraged through random practice and limited provision of feedback and guidance. The BWSTT program emphasized repetition of the normal gait cycle while supported on a treadmill and assisted by 1 to 3 therapy staff. The primary outcome was comfortable gait speed at postintervention assessment (T2). RESULTS: In total, 71 individuals (mean age = 67.3; standard deviation = 11.6 years) with stroke (mean onset = 20.9 [14.1] weeks) were randomized (MLWP, n = 35; BWSTT, n = 36). There was no significant between-group difference in gait speed at T2 (0.002 m/s; 95% confidence interval [CI] = -0.11, 0.12; P > .05). The MLWP group improved by 0.14 m/s (95% CI = 0.09, 0.19), and the BWSTT group improved by 0.14 m/s (95% CI = 0.08, 0.20). CONCLUSIONS: In this sample of community-dwelling adults within 1 year of stroke, a 15-session program of varied overground walking-focused training was not superior to a BWSTT program of equal frequency, duration, and in-session step activity.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".