There is a disparity in sport-related injuries between sexes, with females sustaining non-contact musculoskeletal injuries at a higher rate. Anterior cruciate ligament ruptures are between two and eight times more common than in males, and females also have a higher incidence of ankle sprains, patellofemoral pain, and bone stress injuries. The sequelae of such injuries can be devastating to an athlete, resulting in time out of sport, surgery, and the early onset of osteoarthritis. It is important to identify the causes of this disparity and introduce prevention programmes to reduce the incidence of these injuries. A natural difference reflects the effect of reproductive hormones in females, which have receptors in certain musculoskeletal tissues. Relaxin increases ligamentous laxity. Oestrogen decreases the synthesis of collagen and progesterone does the opposite. Insufficient diet and intensive training can lead to menstrual irregularities, which are common in female athletes and result in injury, whereas oral contraception may have a protective effect against certain injuries. It is important for coaches, physiotherapists, nutritionists, doctors, and athletes to be aware of these issues and to implement preventive measures. This annotation explores the relationship between the menstrual cycle and orthopaedic sports injuries in pre-menopausal females, and proposes recommendations to mitigate the risk of sustaining these injuries. Cite this article: Bone Joint J 2023;105-B(7):723–728

The anterior cruciate ligament (ACL) is frequently injured in elite athletes, with females up to eight times more likely to suffer an ACL tear than males. Biomechanical and hormonal factors have been thoroughly investigated; however, there remain unknown factors that need investigation. The mechanism of injury differs between males and females, and anatomical differences contribute significantly to the increased risk in females. Hormonal factors, both endogenous and exogenous, play a role in ACL laxity and may modify the risk of injury. However, data are still limited, and research involving oral contraceptives is potentially associated with methodological and ethical problems. Such characteristics can also influence the outcome after ACL reconstruction, with higher failure rates in females linked to a smaller diameter of the graft, especially in athletes aged < 21 years. The addition of a lateral extra-articular tenodesis can improve the outcomes after ACL reconstruction and reduce the risk of failure, and it should be routinely considered in young elite athletes. Sex-specific environmental differences can also contribute to the increased risk of injury, with more limited access to and availablility of advanced training facilities for female athletes. In addition, football kits are designed for male players, and increased attention should be focused on improving the quality of pitches, as female leagues usually play the day after male leagues. The kit, including boots, the length of studs, and the footballs themselves, should be tailored to the needs and body shapes of female athletes. Specific physiotherapy programmes and training protocols have yielded remarkable results in reducing the risk of injury, and these should be extended to school-age athletes. Finally, psychological factors should not be overlooked, with females’ greater fear of re-injury and lack of confidence in their knee compromising their return to sport after ACL injury. Both intrinsic and extrinsic factors should be recognized and addressed to optimize the training programmes which are designed to prevent injury, and improve our understanding of these injuries. Cite this article: Bone Joint J 2023;105-B(10):1033–1037

Artificial intelligence and machine-learning analytics have gained extensive popularity in recent years due to their clinically relevant applications. A wide range of proof-of-concept studies have demonstrated the ability of these analyses to personalize risk prediction, detect implant specifics from imaging, and monitor and assess patient movement and recovery. Though these applications are exciting and could potentially influence practice, it is imperative to understand when these analyses are indicated and where the data are derived from, prior to investing resources and confidence into the results and conclusions. In this article, we review the current benefits and potential limitations of machine-learning for the orthopaedic surgeon with a specific emphasis on data quality.