Upper limb tendon/muscle vibration in persons with subacute and chronic stroke: a systematic review and meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Results of several recent studies suggest that tendon/muscle vibration treatment may improve motor performance and reduce spasticity in individuals with stroke. We performed a systematic review and meta-analysis to assess the efficacy of tendon/muscle vibration treatment for upper limb functional movements in persons with subacute and chronic stroke. EVIDENCE ACQUISITION: We searched MEDLINE (Ovid), EMBASE (Ovid), and the Cochrane Central Register of Controlled Trials (Wiley) from inception to September 2017. We included randomized controlled trials comparing upper limb tendon/muscle vibration to sham treatment/rest or conventional interventions in persons with subacute and chronic stroke. Our primary outcome was upper limb functional movement at the end of the treatment period. EVIDENCE SYNTHESIS: We included eight trials, enrolling a total of 211 participants. We found insufficient evidence to support a benefit for upper limb functional movement (standard mean difference -0.32, 95% confidence interval (CI) -0.74 to 0.10, I2 25%, 6 trials, 135 participants). Movement time for reaching tasks significantly decreased after using tendon/muscle vibration (standard mean difference -1.20, 95% CI -2.05 to -0.35, I2 65%, 2 trials, 74 participants). We also found that tendon/muscle vibration was not associated with a significant reduction in spasticity (4 trials). CONCLUSIONS: Besides shorter movement time for reaching tasks, we did not identify evidence to support clinical improvement in upper limb functional movements after tendon/muscle vibration treatment in persons with subacute and chronic stroke. A small number of trials were identified; therefore, there is a need for larger, higher quality studies and to consider the clinical relevance of performance-based outcome measures that focus on time to complete a functional movement such as a reach.
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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 | 0.014 | 0.033 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.023 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".