Changes in knee adduction moment, pain, and functionality with a variable‐stiffness walking shoe after 6 months
Bibliographic record
Abstract
This study tested the effects of variable-stiffness shoes on knee adduction moment, pain, and function in subjects with symptoms of medial compartment knee osteoarthritis over 6 months. Patients were randomly and blindly assigned to a variable-stiffness intervention or constant-stiffness control shoe. The Western Ontario and McMaster Universities (WOMAC) score served as the primary outcome measure. Joint loading, the secondary outcome measure, was assessed using the external knee adduction moment. Peak external knee adduction moment, total WOMAC, and WOMAC pain scores were assessed at baseline and after 6 months. The total WOMAC and WOMAC pain scores for the intervention group were reduced from baseline to 6 months (p = 0.017 and p = 0.002, respectively), with no significant reductions for the control group. There was no difference between groups in magnitude of the reduction in total WOMAC (p = 0.50) or WOMAC pain scores (p = 0.31). The proportion of patients achieving a clinically important improvement in pain was greater in the intervention group than in the control group (p = 0.012). The variable-stiffness shoes reduced the peak knee adduction moment (-6.6% vs. control, p < 0.001) in the 34 intervention subjects at 6 months. The adduction moment reduction significantly improved (p = 0.03) from the baseline reduction. The constant-stiffness control shoe increased the peak knee adduction moment (+6.3% vs. personal, p = 0.004) in the 26 control subjects at 6 months. The results of this study showed that wearing the variable-stiffness shoe lowered the adduction moment, reduced pain, and improved functionality after 6 months of wear. The lower adduction moment associated with wearing this shoe may slow the rate of progression of osteoarthritis after long-term use.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".