Resistance Training for Gait Speed and Total Distance Walked During the Chronic Stage of Stroke: A Meta-Analysis
Bibliographic record
Abstract
OBJECTIVE: To conduct a meta-analysis examining the effectiveness of resistance training on comfortable gait speed and total distance walked when initiated in the chronic stage of stroke. METHODS: MEDLINE, CINAHL, EMBASE, and Scopus databases were searched from 1980 to June 2012. Studies were selected if they met the following criteria: (1) they were randomized controlled trials; (2) individuals in the studies were entered into the studies at or over 6 months post stroke; (3) resistance training was initiated during the chronic stage of stroke; and (4) study participants were ≥18 years of age. A standardized mean difference (SMD ± SE and 95% confidence interval [CI]) was calculated for at least 1 of the following outcomes in each study: comfortable gait speed and/or 6-minute walk test (6MWT). Treatment effect sizes were interpreted as follows: small, ≯0.2; moderate, ≯0.5; or large, ≯0.8. Study quality was assessed using the Physiotherapy Evidence Database (PEDro) tool. RESULTS: Ten randomized controlled trials met inclusion criteria. Significant improvement was seen for gait speed with a small effect size (0.295 ± 0.118; 95% CI, 0.063-0.526; P < .013) and a pooled post mean speed of 0.79 m/s, and for the 6MWT (0.247 ± 0.111; 95% CI, 0.030-0.465; P = .026) with a pooled post mean total distance walked of 271.9 m. CONCLUSION: This meta-analysis demonstrated that providing lower limb resistance training to community-dwelling individuals who are 6 months post stroke has the capacity to improve comfortable gait speed and total distance walked.
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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 | 0.018 | 0.032 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.069 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".