Walking biomechanics in women with patellofemoral osteoarthritis differ compared to men with and women without patellofemoral osteoarthritis
Bibliographic record
Abstract
BACKGROUND: Differences in walking biomechanics between women and men with patellofemoral joint (PF) osteoarthritis (OA) may contribute to the development or progression of persistent symptoms in people with PF OA. OBJECTIVE: Evaluate how walking biomechanics of women with PF OA differ from: (i) men with PFJ OA; and (ii) women without PF OA. Second, explore the relationship between knee-related symptoms/function and walking biomechanics in individuals with PF OA, and whether these are modified by sex. METHODS: Sixty-seven individuals with PF OA (43 women) and 14 women without PF OA were included. Biomechanics data were recorded during walking. Patient-reported symptoms and function were obtained using the Knee injury and Osteoarthritis Outcome Score. Differences in continuous biomechanical data were assessed using statistical parametric mapping, with discrete data and relationships evaluated using linear models. RESULTS: ] Nms/kg, respectively) compared to men with PF OA. Compared to their asymptomatic peers, women with PF OA displayed a 5° offset towards greater hip flexion. Higher knee adduction moment impulse correlated with worse KOOS-ADL scores in men, not women. CONCLUSION: Observed biomechanical differences were small in nature with moderate to weak relationship observed with the KOOS. Findings were not limited to the knee, indicating that women with PF OA display unique biomechanical features across the kinetic-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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.004 | 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".