Changes in knee adduction moment wearing a variable‐stiffness shoe correlate with changes in pain and mechanically stimulated cartilage oligomeric matrix levels
Bibliographic record
Abstract
This study aimed to determine if changes in knee adduction moment (KAM) after 6 months of variable-stiffness shoe wear are associated with changes in symptoms or serum levels of cartilage oligomeric matrix protein (COMP) following a mechanical stimulus in subjects with medial knee osteoarthritis (OA). Twenty-five subjects were enrolled in the study and assigned a variable-stiffness shoe, and 19 subjects completed the 6-month follow-up. At baseline and follow-up subjects underwent gait analysis in control and variable-stiffness shoes, completed Western Ontario and McMaster Universities (WOMAC) questionnaires, and serum COMP concentrations were measured immediately before, 3.5 and 5.5 hours after a 30-minute walking activity. Relationships between changes in KAM (first peak and impulse) and changes in (a) COMP levels in response to the 30-minute walking activity and (b) WOMAC scores from baseline to 6-month follow-up were assessed by Pearson correlation coefficients. Changes in first peak KAM were associated with changes in COMP levels 5.5 hours postactivity from baseline to follow-up (R = .564, P = .045). Subjects with greater reductions in KAM had larger decreases in COMP (expressed as a percent of preactivity levels) at follow-up. Subjects with greater reductions in KAM impulse had significantly greater improvements in WOMAC Pain (R = -.56, P = .015) and Function (R = -.52, P = .028) scores at follow-up. The study results demonstrated the magnitude of reduction in the KAM wearing a variable-stiffness shoe is associated with decreases in mechanically stimulated COMP levels and pain/function. This work suggests that interactions between COMP and joint loading during walking should be further investigated in future studies of treatment outcomes in OA.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".