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. Patients and Methods. In a retrospective analysis with a standard postoperative follow-up, 95 patients with a PJI of the hip and knee who were treated with a two-stage exchange between 2013 and 2017 formed the study group. A historical cohort of 86 patients treated between 2009 and 2011 not according to the standardized protocol served as a control group. The success of treatment was defined according to the Delphi criteria in a two-year follow-up. Results. Patients in the study group had a significantly higher Charlson Comorbidity Index (3.9 vs 3.1; p = 0.009) and rate of previous revisions for infection (52.6% vs 36%; p = 0.025), and tended to be older (69.0 vs 66.2 years; p = 0.075) with a broader polymicrobial spectrum (47.3% vs 33.7%; p = 0.062). The rate of recurrent infection (3.1% vs 10.4%; p = 0.048) and the mean time interval between the two stages of the procedure (66.6 vs 80.7 days; p < 0.001) were reduced significantly in the study group compared with the control group. Conclusion. We were able to show that the outcome following the treatment of PJIs of the hip and knee is better when managed in a separate department with an interdisciplinary team using a standard algorithm

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

Despite being one of the most common injuries around the elbow, the optimal treatment of olecranon fractures is far from established and stimulates debate among both general orthopaedic trauma surgeons and upper limb specialists. It is almost universally accepted that stable non-displaced fractures can be safely treated nonoperatively with minimal specialist input. Internal fixation is recommended for the vast majority of displaced fractures, with a range of techniques and implants to choose from. However, there is concern regarding the complication rates, largely related to symptomatic metalwork resulting in high rates of implant removal. As the number of elderly patients sustaining these injuries increases, we are becoming more aware of the issues associated with fixation in osteoporotic bone and the often fragile soft-tissue envelope in this group. Given this, there is evidence to support an increasing role for nonoperative management in this high-risk demographic group, even in those presenting with displaced and/or multifragmentary fracture patterns. This review summarizes the available literature to date, focusing predominantly on the management techniques and available implants for stable fractures of the olecranon. It also offers some insights into the potential avenues for future research, in the hope of addressing some of the pertinent questions that remain unanswered.

Cite this article: Bone Joint J 2023;105-B(2):112–123.

Advanced 3D imaging and CT-based navigation have emerged as valuable tools to use in total knee arthroplasty (TKA), for both preoperative planning and the intraoperative execution of different philosophies of alignment. Preoperative planning using CT-based 3D imaging enables more accurate prediction of the size of components, enhancing surgical workflow and optimizing the precision of the positioning of components. Surgeons can assess alignment, osteophytes, and arthritic changes better. These scans provide improved insights into the patellofemoral joint and facilitate tibial sizing and the evaluation of implant-bone contact area in cementless TKA. Preoperative CT imaging is also required for the development of patient-specific instrumentation cutting guides, aiming to reduce intraoperative blood loss and improve the surgical technique in complex cases. Intraoperative CT-based navigation and haptic guidance facilitates precise execution of the preoperative plan, aiming for optimal positioning of the components and accurate alignment, as determined by the surgeon’s philosophy. It also helps reduce iatrogenic injury to the periarticular soft-tissue structures with subsequent reduction in the local and systemic inflammatory response, enhancing early outcomes. Despite the increased costs and radiation exposure associated with CT-based navigation, these many benefits have facilitated the adoption of imaged based robotic surgery into routine practice. Further research on ultra-low-dose CT scans and exploration of the possible translation of the use of 3D imaging into improved clinical outcomes are required to justify its broader implementation.

Cite this article: Bone Joint J 2024;106-B(9):892–897.

Abstract

Robotic-assisted total knee arthroplasty (TKA) has proven higher accuracy, fewer alignment outliers, and improved short-term clinical outcomes when compared to conventional TKA. However, evidence of cost-effectiveness and individual superiority of one system over another is the subject of further research. Despite its growing adoption rate, published results are still limited and comparative studies are scarce. This review compares characteristics and performance of five currently available systems, focusing on the information and feedback each system provides to the surgeon, what the systems allow the surgeon to modify during the operation, and how each system then aids execution of the surgical plan.

Cite this article: Bone Jt Open 2023;4(1):13–18.

Previous standards for assessing the reliability of a measurement tool have lacked consistency. We reviewed the most current American Society for Testing and Materials and International Organisation for Standardisation (ISO) recommendations, and propose an algorithm for orthopaedic surgeons. When assessing a measurement tool, conditions of the experimental set-up and clear formulae used to compile the results should be strictly reported. According to these recent guidelines, accuracy is a confusing word with an overly broad meaning and should therefore be abandoned. Depending on the experimental conditions, one should be referring to bias (when the study protocol involves accepted reference values), and repeatability (sr, r) or reproducibility (SR, R). In the absence of accepted reference values, only repeatability (sr, r) or reproducibility (SR, R) should be provided. Take home message: Assessing the reliability of a measurement tool involves reporting bias, repeatability and/or reproducibility depending on the defined conditions, instead of precision or accuracy. Cite this article: Bone Joint J 2016;98-B2:166–72

Evaluating musculoskeletal conditions of the lower limb and understanding the pathophysiology of complex bone kinematics is challenging. Static images do not take into account the dynamic component of relative bone motion and muscle activation. Fluoroscopy and dynamic MRI have important limitations. Dynamic CT (4D-CT) is an emerging alternative that combines high spatial and temporal resolution, with an increased availability in clinical practice. 4D-CT allows simultaneous visualization of bone morphology and joint kinematics. This unique combination makes it an ideal tool to evaluate functional disorders of the musculoskeletal system. In the lower limb, 4D-CT has been used to diagnose femoroacetabular impingement, patellofemoral, ankle and subtalar joint instability, or reduced range of motion. 4D-CT has also been used to demonstrate the effect of surgery, mainly on patellar instability. 4D-CT will need further research and validation before it can be widely used in clinical practice. We believe, however, it is here to stay, and will become a reference in the diagnosis of lower limb conditions and the evaluation of treatment options.

Cite this article: Bone Joint J 2021;103-B(5):822–827.

Upper limb amputations, ranging from transhumeral to partial hand, can be devastating for patients, their families, and society. Modern paradigm shifts have focused on reconstructive options after upper extremity limb loss, rather than considering the amputation an ablative procedure. Surgical advancements such as targeted muscle reinnervation and regenerative peripheral nerve interface, in combination with technological development of modern prosthetics, have expanded options for patients after amputation. In the near future, advances such as osseointegration, implantable myoelectric sensors, and implantable nerve cuffs may become more widely used and may expand the options for prosthetic integration, myoelectric signal detection, and restoration of sensation. This review summarizes the current advancements in surgical techniques and prosthetics for upper limb amputees.

Cite this article: Bone Joint J 2021;103-B(3):430–439.

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.

Modern healthcare contracting is shifting the responsibility for improving quality, enhancing community health and controlling the total cost of care for patient populations from payers to providers. Population-based contracting involves capitated risk taken across an entire population, such that any included services within the contract are paid for by the risk-bearing entity throughout the term of the agreement. Under such contracts, a risk-bearing entity, which may be a provider group, a hospital or another payer, administers the contract and assumes risk for contractually defined services. These contracts can be structured in various ways, from professional fee capitation to full global per member per month diagnosis-based risk. The entity contracting with the payer must have downstream network contracts to provide the care and facilities that it has agreed to provide. Population health is a very powerful model to reduce waste and costs. It requires a deep understanding of the nuances of such contracting and the appropriate infrastructure to manage both networks and risk.

Cite this article: Bone Joint J 2017;99-B:1431–4.

‘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.

Periprosthetic joint infection (PJI) is one of the most feared and challenging complications following total knee arthroplasty. We provide a detailed description of our current understanding regarding the management of PJI of the knee, including diagnostic aids, pre-operative planning, surgical treatment, and outcome.

Cite this article: Bone Joint J 2015;97-B(10 Suppl A):20–9.

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.