Whole body vibration and cerebral palsy: a systematic review.
Bibliographic record
Abstract
PURPOSE: The goal of this review is to evaluate the effects of whole body vibration on outcomes in patients with cerebral palsy. The findings in this review may help clinicians make evidence informed decisions on the use of whole body vibration for cerebral palsy. METHODS: A systematic search was conducted on April 29, 2014.The following search terms were used to search of several databases: (whole body vibration OR whole-body vibration OR whole body-vibration OR WBV) AND (cerebral palsy). Articles that met the inclusion criteria were assessed using the Scottish intercollegiate guidelines network (SIGN) rating system to assess the methodology and bias of the articles for randomized control trials. RESULTS: The search produced 25 articles, of which 12 duplicates were identified and removed. Another seven articles were not considered since they did not fit the inclusion criteria, leaving a total of five studies for review. Four of the articles analyzed the effects of WBV in children while the other study focused on adults with cerebral palsy. There was one low quality article, four acceptable quality articles and one high quality article when assessed using the SIGN criteria. CONCLUSIONS: It appears that whole body vibration has the potential to provide symptomatic relief for patients with cerebral palsy. Whole body vibration may improve spasticity, muscle strength and coordination. There is a lack of research to conclusively determine whether it does alter bone mineral density.
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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 | 0.006 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.005 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".