Aims. Conventional patient-reported surveys, used for patients undergoing total hip arthroplasty (THA), are limited by subjectivity and recall bias. Objective functional evaluation, such as gait analysis, to delineate a patient’s functional capacity and customize surgical interventions, may address these shortcomings. This systematic review endeavours to investigate the application of objective functional assessments in appraising individuals undergoing THA. Methods. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were applied. Eligible studies of THA patients that conducted at least one type of objective functional assessment both pre- and postoperatively were identified through Embase, Medline/PubMed, and Cochrane Central database-searching from inception to 15 September 2023. The assessments included were subgrouped for analysis: gait analysis, motion analysis, wearables, and strength tests. Results. A total of 130 studies using 15 distinct objective functional assessment methods (FAMs) were identified. The most frequently used method was instrumented gait/motion analysis, followed by the Timed-Up-and-Go test (TUG), 6 minute walk test, timed stair climbing test, and various strength tests. These assessments were characterized by their diagnostic precision and applicability to daily activities. Wearables were frequently used, offering cost-effectiveness and remote monitoring benefits. However, their accuracy and potential discomfort for patients must be considered. Conclusion. The integration of objective functional assessments in THA presents promise as a progress-tracking modality for improving patient outcomes. Gait analysis and the TUG, along with advancing wearable sensor technology, have the potential to enhance patient care, surgical planning, and rehabilitation. Cite this article: Bone Joint J 2024;106-B(8):764–774

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.

Aims

The success of anterior cruciate ligament reconstruction (ACLR) depends on osseointegration at the graft-tunnel interface and intra-articular ligamentization. Our aim was to conduct a systematic review of clinical and preclinical studies that evaluated biological augmentation of graft healing in ACLR.