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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.

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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.

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Study design Systematic Review Objectives Vertebral Artery Injury (VAI) is a potentially serious complication of cervical spine fractures. As many patients can be asymptomatic at the time of injury, the identification and diagnosis of VAI can often prove difficult. Due to the high rates of morbidity and mortality associated with VAI, high clinical suspicion is paramount. The purpose of this review is to elucidate incidence, diagnosis, treatment and outcomes of VAI associated with cervical spine injuries. Methods A systematic search of electronic databases was performed using ‘PUBMED’, ‘EMBASE’,‘Medline (OVID)’, and ‘Web of Science, for articles pertaining to traumatic cervical fractures with associated VAI. Results 24 studies were included in this systematic review. Data was included from 48 744 patients. In regards to the demographics of the focus groups that highlighted information on VAI, the mean average age was 46.6 (32.1-62.6). 75.1% (169/225) were male and 24.9% (56/225) were female. Overall incidence of VAI was 596/11 479 (5.19%). 190/420 (45.2%) of patients with VAI had fractures involving the transverse foramina. The right vertebral artery was the most commonly injured 114/234 (48.7%). V3 was the most common section injured (16/36 (44.4%)). Grade I was the most common (103/218 (47.2%)) injury noted. Collective acute hospital mortality rate was 32/226 (14.2%), ranging from 0-26.2% across studies. Conclusion VAI secondary to cervical spine trauma has a notable incidence and high associated mortality rates. The current available literature is limited by a low quality of evidence. In order to optimise diagnostic protocols and treatment strategies, in addition to reducing mortality rates associated with VAI, robust quantitative and qualitative studies are needed.

Medical and surgical research has always had a longstanding relationship with industry-based funding from sources, such as drug and device companies. Concerns exist surrounding the association between funding sources, outcome from studies and publication bias. Studies demonstrating increased odds ratios associated with positive results in industry sponsored studies across medicine have stimulated Cochrane reviews, literature reviews and other articles to examine this relationship further. In spine surgery in particular, studies with positive results have an odds ratio of 3.3 of being published. This article discusses the biases associated with industry sponsorship, possible ways to reduce such biases and ways to improve transparency in research relationships. This article explores the types of bias that can be encountered at different stages of research including previous trials in spine surgery. The means of improving transparency including the Physician Payment Sunshine Act of 2010 and International Committee of Medical Journal Editors (ICJME) accreditation are discussed. We recognize that physicians undertaking industry sponsored research should be protected and not be liable to perverse incentives. We conclude that mitigating bias in industry sponsored research is a multistep process and needs a multifaceted approach. The main beneficiary of research should be patients and as such a collective effort from medical professionals, health care institutions, journals and industry should approach research, and publications with that in mind.

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