Effects of Augmented Exercise Therapy on Outcome of Gait and Gait-Related Activities in the First 6 Months After Stroke
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The purpose of this study was to determine the effects of augmented exercise therapy on gait, gait-related activities, and (basic and extended) activities of daily living within the first 6 months poststroke. METHODS: A systematic literature search in electronic databases from 1990 until October 2010 was performed. Randomized controlled trials were included in which the experimental group spent augmented time in lower-limb exercise therapy compared with the control group. Outcomes were gait, gait-related activities, and (extended) activities of daily living. Results from individual studies were pooled by calculating the summary effect sizes. Subgroup analyses were applied for a treatment contrast of ≥16 hours, timing poststroke, type of control intervention, and methodological quality. RESULTS: Fourteen (N=725) of 4966 identified studies were included. Pooling resulted in small to moderate significant summary effect sizes in favor of augmented exercise therapy for walking ability, comfortable and maximum walking speed, and extended activities of daily living. No significant effects were found for basic activities of daily living. Subgroup analysis did not show a significant effect modification. CONCLUSIONS: Dose-response trials in stroke rehabilitation are heterogeneous. The present meta-analysis suggests that increased time spent on exercise of gait and gait-related activities in the first 6 months poststroke results in significant small to moderate effects in terms of walking ability, walking speed, and extended activities of daily living. High-quality dose-response exercise therapy trials are needed with identical treatment goals but incremental levels of intensity.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.010 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".