The addition of mirror therapy improved upper limb motor recovery and level of independence after stroke: a randomized controlled trial
Bibliographic record
Abstract
Abstract Introduction In stroke survivors, the prevalence of upper motor disability remains high. There has not been much report on the success of post-stroke mirror therapy, especially in developing countries. Objective The focus of this research is to see how mirror therapy, in addition to standard rehabilitation for hand paresis, affects upper limb motor recovery and level of independence in self-care after stroke at an Indonesian teaching hospital. Method This was a randomized controlled trial with no assessor blinding. The study included 18 subacute stroke patients who did not have cognitive or visual impairment. The mirror group received a 20-minute mirror therapy session in addition to conventional rehabilitation, while the control group received only the standard program for 5 weeks (2 times per week). The Brunnstrom score and self-care level of independence elements of the Functional Independence Measure (FIM) were used as outcome measures. Results Baseline comparisons of lesion type and Brunnstrom score showed significant between-group differences. The ANACOVA test showed the difference had no effect on the FIM change in scores (P > 0.05). One patient (mirror group) was dropped out from the study. After 5 weeks (n=17), the mirror group showed improvement in both the Brunnstrom and FIM scores (P < 0.05) compared to the control group. Conclusions Mirror treatment improves upper limb motor recovery and level of independence in self-care after stroke when combined with standard hand paresis rehabilitation 2 times a week for 5 weeks.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".