Lateral wedges alter mediolateral load distributions at the knee joint in obese individuals
Bibliographic record
Abstract
Obesity is the primary risk factor for knee osteoarthritis (OA). Greater external knee adduction moments, surrogate measures for medial compartment loading, are present in Obese individuals and may predispose them to knee OA. Laterally wedged insoles decrease the magnitude of the external adduction moment in Obese individuals but it is unknown how they alter the center of pressure on the tibial plateau. A gait analysis was performed on 14 Obese (avg. 29.3 years; BMI range: 30.3-51.6 kg/m(2) ) and 14 lean women (avg. 26.1 years; BMI range: 20.9-24.6 kg/m(2) ) with and without a full-length, wedged insole. Computed joint angles, joint moments, and knee extensor strength values were input into a musculoskeletal model to estimate center of pressure of the contact force on the tibial plateau. Statistical significance was assessed using a two-way ANOVA to compare the main effects of group and insole condition (α = 0.05). The insole resulted in a significant (p < 0.01) lateral shift in the center of pressure location in both the Obese and Control groups (mean: 2.9 ± 0.7 and 1.5 ± 0.7 mm, respectively). The insole also significantly reduced the peak external knee adduction moment 1.88 ± 1.82 N m in the Control group (p < 0.01) and 3.62 ± 3.90 N m in the Obese group (p < 0.01). The results of this study indicate the effects of a prophylactic wedged insole for reducing the magnitude of the load on the knee's medial compartment in Obese women who are at risk for knee OA development.
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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".