In recent years, machine learning (ML) and artificial neural networks (ANNs), a particular subset of ML, have been adopted by various areas of healthcare. A number of diagnostic and prognostic algorithms have been designed and implemented across a range of orthopaedic sub-specialties to date, with many positive results. However, the methodology of many of these studies is flawed, and few compare the use of ML with the current approach in clinical practice. Spinal surgery has advanced rapidly over the past three decades, particularly in the areas of implant technology, advanced surgical techniques, biologics, and enhanced recovery protocols. It is therefore regarded an innovative field. Inevitably, spinal surgeons will wish to incorporate ML into their practice should models prove effective in diagnostic or prognostic terms. The purpose of this article is to review published studies that describe the application of neural networks to spinal surgery and which actively compare ANN models to contemporary clinical standards allowing evaluation of their efficacy, accuracy, and relatability. It also explores some of the limitations of the technology, which act to constrain the widespread adoption of neural networks for diagnostic and prognostic use in spinal care. Finally, it describes the necessary considerations should institutions wish to incorporate ANNs into their practices. In doing so, the aim of this review is to provide a practical approach for spinal surgeons to understand the relevant aspects of neural networks. Cite this article: Bone Joint J 2021;103-B(9):1442–1448

Continuous technical improvement in spinal surgical procedures, with the aim of enhancing patient outcomes, can be assisted by the deployment of advanced technologies including navigation, intraoperative CT imaging, and surgical robots. The latest generation of robotic surgical systems allows the simultaneous application of a range of digital features that provide the surgeon with an improved view of the surgical field, often through a narrow portal. There is emerging evidence that procedure-related complications and intraoperative blood loss can be reduced if the new technologies are used by appropriately trained surgeons. Acceptance of the role of surgical robots has increased in recent years among a number of surgical specialities including general surgery, neurosurgery, and orthopaedic surgeons performing major joint arthroplasty. However, ethical challenges have emerged with the rollout of these innovations, such as ensuring surgeon competence in the use of surgical robotics and avoiding financial conflicts of interest. Therefore, it is essential that trainees aspiring to become spinal surgeons as well as established spinal specialists should develop the necessary skills to use robotic technology safely and effectively and understand the ethical framework within which the technology is introduced. Traditional and more recently developed platforms exist to aid skill acquisition and surgical training which are described. The aim of this narrative review is to describe the role of surgical robotics in spinal surgery, describe measures of proficiency, and present the range of training platforms that institutions can use to ensure they employ confident spine surgeons adequately prepared for the era of robotic spinal surgery. Cite this article: Bone Joint J 2020;102-B(5):568–572

The recently published Prophylactic Antibiotic Regimens In Tumor Surgery (PARITY) trial found no benefit in extending antibiotic prophylaxis from 24 hours to five days after endoprosthetic reconstruction for lower limb bone tumours. PARITY is the first randomized controlled trial in orthopaedic oncology and is a huge step forward in understanding antibiotic prophylaxis. However, significant gaps remain, including questions around antibiotic choice, particularly in the UK, where cephalosporins are avoided due to concerns of Clostridioides difficile infection. We present a review of the evidence for antibiotic choice, dosing, and timing, and a brief description of PARITY, its implication for practice, and the remaining gaps in our understanding.

Cite this article: Bone Joint J 2023;105-B(8):850–856.

The mucopolysaccharidoses (MPS) are a group of inherited lysosomal storage disorders with clinical manifestations relevant to the orthopaedic surgeon. Our aim was to review the recent advances in their management and the implications for surgical practice.

The current literature about MPSs is summarised, emphasising orthopaedic complications and their management.

Recent advances in the diagnosis and management of MPSs include the recognition of slowly progressive, late presenting subtypes, developments in life-prolonging systemic treatment and potentially new indications for surgical treatment. The outcomes of surgery in these patients are not yet validated and some procedures have a high rate of complications which differ from those in patients who do not have a MPS.

The diagnosis of a MPS should be considered in adolescents or young adults with a previously unrecognised dysplasia of the hip. Surgeons treating patients with a MPS should report their experience and studies should include the assessment of function and quality of life to guide treatment.

Cite this article: Bone Joint J 2017;99-B:1132–9