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:
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:
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:
As residency training programmes around the globe
move towards competency-based medical education (CBME), there is
a need to review current teaching and assessment practices as they
relate to education in orthopaedic trauma. Assessment is the cornerstone
of CBME, as it not only helps to determine when a trainee is fit
to practice independently, but it also provides feedback on performance
and guides the development of competence. Although a standardised
core knowledge base for trauma care has been developed by the leading
national accreditation bodies and international agencies that teach
and perform research in orthopaedic trauma, educators have not yet established
optimal methods for assessing trainees’ performance in managing
orthopaedic trauma patients. This review describes the existing knowledge from the literature
on assessment in orthopaedic trauma and highlights initiatives that
have recently been undertaken towards CBME in the United Kingdom,
Canada and the United States. In order to support a CBME approach, programmes need to improve
the frequency and quality of assessments and improve on current
formative and summative feedback techniques in order to enhance
resident education in orthopaedic trauma. Cite this article:
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:
