Aims. Machine learning (ML), a branch of artificial intelligence that uses algorithms to learn from data and make predictions, offers a pathway towards more personalized and tailored surgical treatments. This approach is particularly relevant to prevalent joint diseases such as osteoarthritis (OA). In contrast to end-stage disease, where joint arthroplasty provides excellent results, early stages of OA currently lack effective therapies to halt or reverse progression. Accurate prediction of OA progression is crucial if timely interventions are to be developed, to enhance patient care and optimize the design of clinical trials. Methods. A systematic review was conducted in accordance with PRISMA guidelines. We searched MEDLINE and Embase on 5 May 2024 for studies utilizing ML to predict OA progression. Titles and abstracts were independently screened, followed by full-text reviews for studies that met the eligibility criteria. Key information was extracted and synthesized for analysis, including types of data (such as clinical, radiological, or biochemical), definitions of OA progression, ML algorithms, validation methods, and outcome measures. Results. Out of 1,160 studies initially identified, 39 were included. Most studies (85%) were published between 2020 and 2024, with 82% using publicly available datasets, primarily the Osteoarthritis Initiative. ML methods were predominantly supervised, with significant variability in the definitions of OA progression: most studies focused on structural changes (59%), while fewer addressed pain progression or both. Deep learning was used in 44% of studies, while automated ML was used in 5%. There was a lack of standardization in evaluation metrics and limited external validation. Interpretability was explored in 54% of studies, primarily using SHapley Additive exPlanations. Conclusion. Our systematic review demonstrates the feasibility of ML models in predicting OA progression, but also uncovers critical limitations that currently restrict their clinical applicability. Future priorities should include diversifying data sources, standardizing outcome measures, enforcing rigorous validation, and integrating more sophisticated algorithms. This paradigm shift from predictive modelling to actionable clinical tools has the potential to transform patient care and disease management in orthopaedic practice. Cite this article: Bone Joint J 2024;106-B(11):1216–1222

Aims. Current guidelines recommend surgery within 48 hours among patients presenting with hip fractures; however, optimal surgical timing for patients on oral anticoagulants (OACs) remains unclear. Individual studies are limited by small sample sizes and heterogeneous outcomes. The aim of this study was to conduct a systematic review and meta-analysis to summarize the effect of pre-injury OACs on time-to-surgery (TTS) and all-cause mortality among older adults with hip fracture treated surgically. Methods. We searched MEDLINE, EMBASE, and the Cochrane Central Register of Controlled Trials (CENTRAL) from inception to 14 October 2019 to identify studies directly comparing outcomes among hip fracture patients receiving direct oral anticoagulants (DOACs) or vitamin K antagonists (VKAs) prior to hospital admission to hip fracture patients not on OACs. Random effects meta-analyses were used to pool all outcomes (TTS, in-hospital mortality, and 30-day mortality). Results. A total of 34 studies (involving 39,446 patients) were included in our systematic review. TTS was 13.7 hours longer (95% confidence interval (CI) 9.8 to 17.5; p < 0.001) among hip fracture patients on OACs compared to those not on OACs. This translated to a three-fold higher odds of having surgery beyond the recommended 48 hours from admission (odds ratio (OR) 3.0 (95% CI 2.1 to 4.3); p = 0.001). In-hospital mortality was higher (OR 1.4 (95% CI 1.0 to 1.8); p < 0.03) among anticoagulated patients. Among studies comparing anticoagulants, there was no statistically significant difference in time-to-surgery between patients taking a DOAC compared to a VKA. Conclusion. Patients presenting with a hip fracture who were taking OACs prior to injury experience a delay in time-to-surgery and higher mortality than non-anticoagulated patients. Patients on DOACs may be at risk of further delays. Evaluating expedited surgical protocols in hip fracture patients on OACs is an urgent priority, with the potential to decrease morbidity and mortality in this group of high-risk patients. Cite this article: Bone Joint J 2021;103-B(2):222–233

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The early diagnosis of cauda equina syndrome (CES) is crucial for a favourable outcome. Several studies have reported the use of an ultrasound scan of the bladder as an adjunct to assess the minimum post-void residual volume of urine (mPVR). However, variable mPVR values have been proposed as a threshold without consensus on a value for predicting CES among patients with relevant symptoms and signs. The aim of this study was to perform a meta-analysis and systematic review of the published evidence to identify a threshold mPVR value which would provide the highest diagnostic accuracy in patients in whom the diagnosis of CES is suspected.

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The aim of this meta-analysis was to assess the prognosis after early functional rehabilitation or traditional immobilization in patients who underwent operative or nonoperative treatment for rupture of the Achilles tendon.