Sexual dimorphism in knee osteoarthritis: Biomechanical variances and biological influences
Bibliographic record
Abstract
Objective: Osteoarthritis (OA) is a degenerative joint disease that is more prevalent in women than men, especially later in life. This suggests that sexual dimorphism may be present in the pathogenesis of the disease. The purpose of this review is to discuss evidence of sexual dimorphism in knee OA development and presentation as it is framed by two contrasting paradigms: biomechanics and biology. Methods: A comprehensive search of databases was conducted including, but not limited to, MEDLINE via Ovid, PubMed, and Google Scholar. Keywords including osteoarthritis, sex differences, and/or sexual dimorphism were searched in combination with knee biomechanics, ACL, joint malalignment, estrogen, chondrocyte signal(l)ing, growth factor and integrin(s). Results: The biomechanical approach has identified sex differences in joint malalignment, bone shape, gait, and lower limb muscle strength leading to altered load transmission, as well as increased knee laxity in women predisposing them to joint injury. The biological approach has largely focused on the influence of estrogen receptor signaling on the maintenance of joint tissues. Preliminary work identifying sexual dimorphism in chondrocyte signaling pathways involving growth factors and collagen receptors has been reported in addition to more systemic levels of inflammatory cytokines and metabolites. Conclusion: Understanding the true etiology of OA is crucial for developing effective, individualized treatment in the age of personalised medicine. A shift from a 'one size fits all' mentality towards an individualized approach for therapeutic treatment must begin with the acknowledgment of sex differences in the biomechanical and biological factors underlying the onset and development of OA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".