A single-blind, cross-over trial of hip abductor strength training to improve Timed Up & Go performance in patients with unilateral, transfemoral amputation
Bibliographic record
Abstract
OBJECTIVE: To evaluate hip abductor strength-training for patients with unilateral transfemoral amputation. DESIGN: Single-blind, cross-over (AB/BA) trial with randomization. SUBJECTS: Seventeen patients with transfemoral amputation. METHODS: Subjects completed 8-week programs of twice weekly hip abductor strength training or arm ergometry. Subjects were randomly assigned to receive either the experimental or active control intervention first. A physiotherapist blinded to group assignment conducted baseline and post-intervention assessments. The Timed Up & Go (TUG) test was selected as the primary outcome measure; secondary measures included the 2 Minute Walk (2MW), hip abductor strength, Activities Specific Balance Confidence Scale (ABC) and prosthetic use. A two-way cross-over ANOVA was used for baseline and post-intervention treatment comparisons. RESULTS: There were no baseline differences between treatments for TUG, 2MW, ABC, Houghton scale, sitting or side-lying abductor strength (p > 0.05 for all), though supine strength was greater for the experimental treatment (p < 0.05). After 8-weeks of hip abductor strength training, there were significant treatment effects for TUG, ABC (p < 0.01 for both), 2MW (p < 0.05), sitting and side-lying abductor strength (p = 0.05 for both), but not for supine strength, prosthetic use, nor thigh girth measures (p > 0.05 for all). CONCLUSIONS: This study suggests that patients with unilateral transfemoral amputation can improve functional performance and balance confidence following intense hip abductor strength training.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".