Impacto de la terapia resistida sobre los parámetros de la marcha en niños con parálisis cerebral: revisión sistemática y metaanálisis
Bibliographic record
Abstract
INTRODUCTION: Cerebral palsy is one of the main causes of disability in childhood. Resistive therapy has proved to be beneficial in increasing strength and motor function in these patients, but its impact on gait is not yet clear. AIM: To analyse the impact of resistive therapy on improving gait through a systematic review and meta-analysis. PATIENTS AND METHODS: A search was conducted in Medline, ISI Web of Knowledge and PEDro for clinical trials in which resistive therapy was used and at least one gait parameter was assessed. RESULTS: Nine controlled studies and one single-arm study were identified. In terms of pre-post difference, the overall intragroup effect was in favour of the intervention, with null heterogeneity (standardised mean difference: 0.32; 95% CI: 0.19-0.44). The standardised mean differences were also positive as they restricted each of the gait parameters analysed: 0.36, 0.35 and 0.22 for step cadence, gait speed and step length, respectively. As regards the difference between groups, the results showed high heterogeneity, and the mean difference was also favourable, especially for speed (7.3 cm/s; 95% CI: 2.67-11.92), cadence (5.66 steps; 95% CI: 1.86-9.46) and, to a lesser extent, step length (3.25 cm; 95% CI: -1.69 to 8.19). CONCLUSION: The results support the impact of resistive therapy on gait improvement, especially in terms of the gait speed and step cadence parameters.
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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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.027 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".