The development of spinal deformity in children with underlying neurodisability can affect their ability to function and impact on their quality of life, as well as compromise provision of nursing care. Patients with neuromuscular spinal deformity are among the most challenging due to the number and complexity of medical comorbidities that increase the risk for severe intraoperative or postoperative complications. A multidisciplinary approach is mandatory at every stage to ensure that all nonoperative measures have been applied, and that the treatment goals have been clearly defined and agreed with the family. This will involve input from multiple specialities, including allied healthcare professionals, such as physiotherapists and wheelchair services. Surgery should be considered when there is significant impact on the patients’ quality of life, which is usually due to poor sitting balance, back or costo-pelvic pain, respiratory complications, or problems with self-care and feeding. Meticulous preoperative assessment is required, along with careful consideration of the nature of the deformity and the problems that it is causing. Surgery can achieve good curve correction and results in high levels of satisfaction from the patients and their caregivers. Modern modular posterior instrumentation systems allow an effective deformity correction. However, the risks of surgery remain high, and involvement of the family at all stages of decision-making is required in order to balance the risks and anticipated gains of the procedure, and to select those patients who can mostly benefit from spinal correction.

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.

The coronavirus disease 2019 (COVID-19) pandemic has led to unprecedented challenges to healthcare systems worldwide. Orthopaedic departments have adopted business continuity models and guidelines for essential and non-essential surgeries to preserve hospital resources as well as protect patients and staff. These guidelines broadly encompass reduction of ambulatory care with a move towards telemedicine, redeployment of orthopaedic surgeons/residents to the frontline battle against COVID-19, continuation of education and research through web-based means, and cancellation of non-essential elective procedures. However, if containment of COVID-19 community spread is achieved, resumption of elective orthopaedic procedures and transition plans to return to normalcy must be considered for orthopaedic departments. The COVID-19 pandemic also presents a moral dilemma to the orthopaedic surgeon considering elective procedures. What is the best treatment for our patients and how does the fear of COVID-19 influence the risk-benefit discussion during a pandemic? Surgeons must deliberate the fine balance between elective surgery for a patient’s wellbeing versus risks to the operating team and utilization of precious hospital resources. Attrition of healthcare workers or Orthopaedic surgeons from restarting elective procedures prematurely or in an unsafe manner may render us ill-equipped to handle the second wave of infections. This highlights the need to develop effective screening protocols or preoperative COVID-19 testing before elective procedures in high-risk, elderly individuals with comorbidities. Alternatively, high-risk individuals should be postponed until the risk of nosocomial COVID-19 infection is minimal. In addition, given the higher mortality and perioperative morbidity of patients with COVID-19 undergoing surgery, the decision to operate must be carefully deliberated. As we ramp-up elective services and get “back to business” as orthopaedic surgeons, we have to be constantly mindful to proceed in a cautious and calibrated fashion, delivering the best care, while maintaining utmost vigilance to prevent the resurgence of COVID-19 during this critical transition period.

Cite this article: Bone Joint Open 2020;1-6:222–228.

Aims

In 2013, we introduced a specialized, centralized, and interdisciplinary team in our institution that applied a standardized diagnostic and treatment algorithm for the management of prosthetic joint infections (PJIs). The hypothesis for this study was that the outcome of treatment would be improved using this approach.

‘Big data’ is a term for data sets that are so large or complex that traditional data processing applications are inadequate. Billions of dollars have been spent on attempts to build predictive tools from large sets of poorly controlled healthcare metadata. Companies often sell reports at a physician or facility level based on various flawed data sources, and comparative websites of ‘publicly reported data’ purport to educate the public. Physicians should be aware of concerns and pitfalls seen in such data definitions, data clarity, data relevance, data sources and data cleaning when evaluating analytic reports from metadata in health care.

Cite this article: Bone Joint J 2017;99-B:1571–6.

The United States and Canada are in the midst of an epidemic of the use, misuse and overdose of opioids, and deaths related to overdose. This is the direct result of overstatement of the benefits and understatement of the risks of using opioids by advocates and pharmaceutical companies. Massive amounts of prescription opioids entered the community and were often diverted and misused. Most other parts of the world achieve comparable pain relief using fewer opioids.

The misconceptions about opioids that created this epidemic are finding their way around the world. There is particular evidence of the increased prescription of strong opioids in Europe.

Opioids are addictive and dangerous. Evidence is mounting that the best pain relief is obtained through resilience. Opioids are often prescribed when treatments to increase resilience would be more effective.

Cite this article: Bone Joint J 2017;99-B:856–64.

Aims

The importance of accurate identification and reporting of surgical site infection (SSI) is well recognised but poorly defined. Public Health England (PHE) mandated collection of orthopaedic SSI data in 2004. Data submission is required in one of four categories (hip prosthesis, knee prosthesis, repair of neck of femur, reduction of long bone fracture) for one quarter per year. Trusts are encouraged to carry out post-discharge surveillance but this is not mandatory. Recent papers in the orthopaedic literature have highlighted the importance of SSI surveillance and the heterogeneity of surveillance methods. However, details of current orthopaedic SSI surveillance practice has not been described or quantified.

Primary total knee arthroplasty (TKA) is a reliable procedure with reproducible long-term results. Nevertheless, there are conditions related to the type of patient or local conditions of the knee that can make it a difficult procedure. The most common scenarios that make it difficult are discussed in this review. These include patients with many previous operations and incisions, and those with severe coronal deformities, genu recurvatum, a stiff knee, extra-articular deformities and those who have previously undergone osteotomy around the knee and those with chronic dislocation of the patella.

Each condition is analysed according to the characteristics of the patient, the pre-operative planning and the reported outcomes.

When approaching the difficult primary TKA surgeons should use a systematic approach, which begins with the review of the existing literature for each specific clinical situation.

Cite this article: Bone Joint J 2015;97-B(10 Suppl A):30–9.

The patient with a painful arthritic knee awaiting total knee arthroplasty (TKA) requires a multidisciplinary approach. Optimal control of acute post-operative pain and the prevention of chronic persistent pain remains a challenge. The aim of this paper is to evaluate whether stratification of patients can help identify those who are at particular risk for severe acute or chronic pain. . Intense acute post-operative pain, which is itself a risk factor for chronic pain, is more common in younger, obese female patients and those suffering from central pain sensitisation. Pre-operative pain, in the knee or elsewhere in the body, predisposes to central sensitisation. Pain due to osteoarthritis of the knee may also trigger neuropathic pain and may be associated with chronic medication like opioids, leading to a state of nociceptive sensitisation called ‘opioid-induced hyperalgesia’. Finally, genetic and personality related risk factors may also put patients at a higher risk for the development of chronic pain. . Those identified as at risk for chronic pain would benefit from specific peri-operative management including reduction in opioid intake pre-operatively, the peri-operative use of antihyperalgesic drugs such as ketamine and gabapentinoids, and a close post-operative follow-up in a dedicated chronic pain clinic. Cite this article: Bone Joint J 2015;97-B(10 Suppl A):45–8