Investigating and Practicing Orthopedics at the Intersection of Sex and Gender: Understanding the Physiological Basis, Pathology, and Treatment Response of Orthopedic Conditions by Adopting a Gender Lens: A Narrative Overview
Bibliographic record
Abstract
In the biomedical field, the differentiation between sex and gender is crucial for enhancing the understanding of human health and personalizing medical treatments, particularly within the domain of orthopedics. This distinction, often overlooked or misunderstood, is vital for dissecting and treating musculoskeletal conditions effectively. This review delves into the sex- and gender-specific physiology of bones, cartilage, ligaments, and tendons, highlighting how hormonal differences impact the musculoskeletal system's structure and function, and exploring the physiopathology of orthopedic conditions from an epidemiological, molecular, and clinical perspective, shedding light on the discrepancies in disease manifestation across sexes. Examples such as the higher rates of deformities (adolescent idiopathic and adult degenerative scoliosis and hallux valgus) in females and osteoporosis in postmenopausal women illustrate the critical role of sex and gender in orthopedic health. Additionally, the review addresses the morbidity-mortality paradox, where women, despite appearing less healthy on frailty indexes, show lower mortality rates, highlighting the complex interplay between biological and social determinants of health. Injuries and chronic orthopedic conditions such osteoarthritis exhibit gender- and sex-specific prevalence and progression patterns, necessitating a nuanced approach to treatment that considers these differences to optimize outcomes. Moreover, the review underscores the importance of recognizing the unique needs of sexual minority and gender-diverse individuals in orthopedic care, emphasizing the impact of gender-affirming hormone therapy on aspects like bone health and perioperative risks. To foster advancements in sex- and gender-specific orthopedics, we advocate for the strategic disaggregation of data by sex and gender and the inclusion of "Sexual Orientation and Gender Identity" (SOGI) data in research and clinical practice. Such measures can enrich clinical insights, ensure tailored patient care, and promote inclusivity within orthopedic treatments, ultimately enhancing the precision and effectiveness of care for diverse patient populations. Integrating sex and gender considerations into orthopedic research and practice is paramount for addressing the complex and varied needs of patients. By embracing this comprehensive approach, orthopedic medicine can move towards more personalized, effective, and inclusive treatment strategies, thereby improving patient outcomes and advancing the field.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".