Deep gluteal syndrome is an increasingly recognized disease entity, caused by compression of the sciatic or pudendal nerve due to non-discogenic pelvic lesions. It includes the piriformis syndrome, the gemelli-obturator internus syndrome, the ischiofemoral impingement syndrome, and the proximal hamstring syndrome. The concept of the deep gluteal syndrome extends our understanding of posterior hip pain due to nerve entrapment beyond the traditional model of the piriformis syndrome. Nevertheless, there has been terminological confusion and the deep gluteal syndrome has often been undiagnosed or mistaken for other conditions. Careful history-taking, a physical examination including provocation tests, an electrodiagnostic study, and imaging are necessary for an accurate diagnosis. After excluding spinal lesions, MRI scans of the pelvis are helpful in diagnosing deep gluteal syndrome and identifying pathological conditions entrapping the nerves. It can be conservatively treated with multidisciplinary treatment including rest, the avoidance of provoking activities, medication, injections, and physiotherapy. Endoscopic or open surgical decompression is recommended in patients with persistent or recurrent symptoms after conservative treatment or in those who may have masses compressing the sciatic nerve. Many physicians remain unfamiliar with this syndrome and there is a lack of relevant literature. This comprehensive review aims to provide the latest information about the epidemiology, aetiology, pathology, clinical features, diagnosis, and treatment. Cite this article: Bone Joint J 2020;102-B(5):556–567

Literature surrounding artificial intelligence (AI)-related applications for hip and knee arthroplasty has proliferated. However, meaningful advances that fundamentally transform the practice and delivery of joint arthroplasty are yet to be realized, despite the broad range of applications as we continue to search for meaningful and appropriate use of AI. AI literature in hip and knee arthroplasty between 2018 and 2021 regarding image-based analyses, value-based care, remote patient monitoring, and augmented reality was reviewed. Concerns surrounding meaningful use and appropriate methodological approaches of AI in joint arthroplasty research are summarized. Of the 233 AI-related orthopaedics articles published, 178 (76%) constituted original research, while the rest consisted of editorials or reviews. A total of 52% of original AI-related research concerns hip and knee arthroplasty (n = 92), and a narrative review is described. Three studies were externally validated. Pitfalls surrounding present-day research include conflating vernacular (“AI/machine learning”), repackaging limited registry data, prematurely releasing internally validated prediction models, appraising model architecture instead of inputted data, withholding code, and evaluating studies using antiquated regression-based guidelines. While AI has been applied to a variety of hip and knee arthroplasty applications with limited clinical impact, the future remains promising if the question is meaningful, the methodology is rigorous and transparent, the data are rich, and the model is externally validated. Simple checkpoints for meaningful AI adoption include ensuring applications focus on: administrative support over clinical evaluation and management; necessity of the advanced model; and the novelty of the question being answered.

Cite this article: Bone Joint J 2022;104-B(12):1292–1303.

Aims

The principle strategies of fracture-related infection (FRI) treatment are debridement, antimicrobial therapy, and implant retention (DAIR) or debridement, antimicrobial therapy, and implant removal/exchange. Increasing the period between fracture fixation and FRI revision surgery is believed to be associated with higher failure rates after DAIR. However, a clear time-related cut-off has never been scientifically defined. This systematic review analyzed the influence of the interval between fracture fixation and FRI revision surgery on success rates after DAIR.

Aims

This study evaluates the quality of patient-reported outcome measures (PROMs) reported in childhood fracture trials and recommends outcome measures to assess and report physical function, functional capacity, and quality of life using the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) standards.

Aims

Computer-based applications are increasingly being used by orthopaedic surgeons in their clinical practice. With the integration of technology in surgery, augmented reality (AR) may become an important tool for surgeons in the future. By superimposing a digital image on a user’s view of the physical world, this technology shows great promise in orthopaedics. The aim of this review is to investigate the current and potential uses of AR in orthopaedics.

Aims

There is inconsistent evidence on whether prior spinal fusion surgery adversely impacts outcomes following total hip arthroplasty (THA). We conducted a systematic review and meta-analysis to assess the association between pre-existing spinal fusion surgery and the rate of complications following primary THA.