Effects of foot orthoses with medial arch support and lateral wedge on knee adduction moment in patients with medial knee osteoarthritis
Bibliographic record
Abstract
BACKGROUND: There is contradictory evidence regarding whether the addition of medial arch supports to laterally wedged insoles reduces knee adduction moment, improves comfort, and reduces knee pain during the late stance phase of gait. OBJECTIVES: To verify if such effects occur in participants with medial knee osteoarthritis. STUDY DESIGN: Randomized single-blinded study. METHODS: Gait analysis was performed on 18 patients affected by medial knee osteoarthritis. Pain and comfort scores, frontal plane kinematics and kinetics of ankle, knee, and hip were compared in four conditions: without foot orthosis, with foot orthoses, with medial arch support, and with foot orthoses with medial arch support and lateral wedge insoles with 6° and 10° inclination. RESULTS: Lower-extremity gait kinetics were characterized by a significant decrease, greater than 6%, in second peak knee adduction moment in laterally wedged insole conditions compared to the other conditions ( p < 0.001; effect size = 0.6). No significant difference in knee adduction moment was observed between laterally wedged insole conditions. In contrast, a significant increase of 7% in knee adduction moment during the loading response was observed in the customized foot orthoses without lateral inclination condition ( p < 0.001; effect size = 0.3). No difference was found in comfort or pain ratings between conditions. CONCLUSION: Our study suggests that customized foot orthoses with a medial arch support may only be suitable for the management of medial knee osteoarthritis when a lateral wedge is included. Clinical relevance Our data suggest that customized foot orthoses with medial arch support and a lateral wedge reduce knee loading in patients with medial knee osteoarthritis (KOA). We also found evidence that medial arch support may increase knee loading, which could potentially be detrimental in KOA patients.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".