Association of medial longitudinal arch height and stiffness with lower extremity alignment, pain, and disease severity in knee osteoarthritis: A cross-sectional study
Bibliographic record
Abstract
Objectives: This study aimed to investigate the association of medial longitudinal arch (MLA) height and stiffness with lower extremity alignment, pain, and disease severity in patients with knee osteoarthritis (OA). Patients and methods: This cross-sectional study included 90 patients (75 females, 15 males; mean age: 63.6±9.4 years; range, 50 to 90 years) diagnosed with knee OA according to the American College of Rheumatology criteria between December 2022 and June 2024. Medial longitudinal arch height and stiffness were assessed using the arch height index (AHI) method in both sitting and standing positions. The arch stiffness index (ASI) was calculated. The OA-related clinical outcomes included pain severity (numeric rating scale), Western Ontario and McMaster Universities Osteoarthritis Index scores, Kellgren-Lawrence grade, and tibiofemoral angles. Associations between MLA characteristics and OA parameters were examined. Results: Low and high arch rates were 10% and 16%, respectively. No significant differences in OA clinical and radiological parameters were observed across different MLA types. Within-patient comparisons showed higher MLA height in the extremity with greater knee pain and more advanced OA. Correlation analyses indicated that increased ASI was associated with higher arch height and knee varus angles, suggesting a biomechanical interplay between MLA structure and knee joint alignment in advanced OA patients. In the early OA group, ASI was negatively correlated with knee pain severity. Conclusion: A higher medial arch and increased midfoot stiffness were associated with knee pain, radiological severity, and knee varus in patients with OA. These findings support the complex relationship between the foot arch structure and knee OA through the perspective of the lower extremity kinematic chain.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".