Aims

Despite new technologies for total knee arthroplasty (TKA), approximately 20% of patients are dissatisfied. A major reason for dissatisfaction and revision surgery after TKA is persistent pain. The radiological grade of osteoarthritis (OA) preoperatively has been investigated as a predictor of the outcome after TKA, with conflicting results. The aim of this study was to determine if there is a difference in the intensity of pain 12 months after TKA in relation to the preoperative radiological grade of OA alone, and the combination of the intensity of preoperative pain and radiological grade of OA.

The August 2024 Knee Roundup³⁶⁰ looks at: Calcification’s role in knee osteoarthritis: implications for surgical decision-making; Lower complication rates and shorter lengths of hospital stay with technology-assisted total knee arthroplasty; Revision surgery: the hidden burden on surgeons; Are preoperative weight loss interventions worthwhile?; Total knee arthroplasty with or without prior bariatric surgery: a systematic review and meta-analysis; Aspirin triumphs in knee arthroplasty: a decade of evidence; Efficacy of DAIR in unicompartmental knee arthroplasty: a glimpse from Oxford.

The use of artificial intelligence (AI) is rapidly growing across many domains, of which the medical field is no exception. AI is an umbrella term defining the practical application of algorithms to generate useful output, without the need of human cognition. Owing to the expanding volume of patient information collected, known as ‘big data’, AI is showing promise as a useful tool in healthcare research and across all aspects of patient care pathways. Practical applications in orthopaedic surgery include: diagnostics, such as fracture recognition and tumour detection; predictive models of clinical and patient-reported outcome measures, such as calculating mortality rates and length of hospital stay; and real-time rehabilitation monitoring and surgical training. However, clinicians should remain cognizant of AI’s limitations, as the development of robust reporting and validation frameworks is of paramount importance to prevent avoidable errors and biases. The aim of this review article is to provide a comprehensive understanding of AI and its subfields, as well as to delineate its existing clinical applications in trauma and orthopaedic surgery. Furthermore, this narrative review expands upon the limitations of AI and future direction.

Cite this article: Bone Joint Res 2023;12(7):447–454.

Aims

The mid-term results of kinematic alignment (KA) for total knee arthroplasty (TKA) using image derived instrumentation (IDI) have not been reported in detail, and questions remain regarding ligamentous stability and revisions. This paper aims to address the following: 1) what is the distribution of alignment of KA TKAs using IDI; 2) is a TKA alignment category associated with increased risk of failure or poor patient outcomes; 3) does extending limb alignment lead to changes in soft-tissue laxity; and 4) what is the five-year survivorship and outcomes of KA TKA using IDI?

The kinematic alignment (KA) approach to total knee arthroplasty (TKA) has recently increased in popularity. Accordingly, a number of derivatives have arisen and have caused confusion. Clarification is therefore needed for a better understanding of KA-TKA. Calipered (or true, pure) KA is performed by cutting the bone parallel to the articular surface, compensating for cartilage wear. In soft-tissue respecting KA, the tibial cutting surface is decided parallel to the femoral cutting surface (or trial component) with in-line traction. These approaches are categorized as unrestricted KA because there is no consideration of leg alignment or component orientation. Restricted KA is an approach where the periarthritic joint surface is replicated within a safe range, due to concerns about extreme alignments that have been considered ‘alignment outliers’ in the neutral mechanical alignment approach. More recently, functional alignment and inverse kinematic alignment have been advocated, where bone cuts are made following intraoperative planning, using intraoperative measurements acquired with computer assistance to fulfill good coordination of soft-tissue balance and alignment. The KA-TKA approach aims to restore the patients’ own harmony of three knee elements (morphology, soft-tissue balance, and alignment) and eventually the patients’ own kinematics. The respective approaches start from different points corresponding to one of the elements, yet each aim for the same goal, although the existing implants and techniques have not yet perfectly fulfilled that goal.

This study compared the effect of a computer-assisted and a traditional surgical technique on the kinematics of the glenohumeral joint during passive abduction after hemiarthroplasty of the shoulder for the treatment of fractures. We used seven pairs of fresh-frozen cadaver shoulders to create simulated four-part fractures of the proximal humerus, which were then reconstructed with hemiarthroplasty and reattachment of the tuberosities. The specimens were randomised, so that one from each pair was repaired using the computer-assisted technique, whereas a traditional hemiarthroplasty without navigation was performed in the contralateral shoulder. Kinematic data were obtained using an electromagnetic tracking device. The traditional technique resulted in posterior and inferior translation of the humeral head. No statistical differences were observed before or after computer-assisted surgery. Although it requires further improvement, the computer-assisted approach appears to allow glenohumeral kinematics to more closely replicate those of the native joint, potentially improving the function of the shoulder and extending the longevity of the prosthesis

Restoration of neutral alignment of the leg is an important factor affecting the long-term results of total knee arthroplasty (TKA). Recent developments in computer-assisted surgery have focused on systems for improving TKA. In a prospective study two groups of 80 patients undergoing TKA had operations using either a computer-assisted navigation system or a conventional technique. Alignment of the leg and the orientation of components were determined on post-operative long-leg coronal and lateral films. The mechanical axis of the leg was significantly better in the computer-assisted group (96%, within ±3° varus/valgus) compared with the conventional group (78%, within ±3° varus/valgus). The coronal alignment of the femoral component was also more accurate in the computer-assisted group. Computer-assisted TKA gives a better correction of alignment of the leg and orientation of the components compared with the conventional technique. Potential benefits in the long-term outcome and functional improvement require further investigation

Aims

Neither a surgeon’s intraoperative impression nor the parameters of computer navigation have been shown to be predictive of the outcomes following total knee arthroplasty (TKA). The aim of this study was to determine whether a surgeon, with robotic assistance, can predict the outcome as assessed using the Knee Injury and Osteoarthritis Outcome Score (KOOS) for pain (KPS), one year postoperatively, and establish what factors correlate with poor KOOS scores in a well-aligned and balanced TKA.

Aims

Appropriate acetabular component placement has been proposed for prevention of postoperative dislocation in total hip arthroplasty (THA). Manual placements often cause outliers in spite of attempts to insert the component within the intended safe zone; therefore, some surgeons routinely evaluate intraoperative pelvic radiographs to exclude excessive acetabular component malposition. However, their evaluation is often ambiguous in case of the tilted or rotated pelvic position. The purpose of this study was to develop the computational analysis to digitalize the acetabular component orientation regardless of the pelvic tilt or rotation.

Aims

A significant percentage of patients remain dissatisfied after total knee arthroplasty (TKA). The aim of this study was to determine whether the sequential addition of accelerometer-based navigation for femoral component preparation and sensor-guided ligament balancing improved complication rates, radiological alignment, or patient-reported outcomes (PROMs) compared with a historical control group using conventional instrumentation.

The application of robotics in the operating theatre for knee arthroplasty remains controversial. As with all new technology, the introduction of new systems might be associated with a learning curve. However, guidelines on how to assess the introduction of robotics in the operating theatre are lacking. This systematic review aims to evaluate the current evidence on the learning curve of robot-assisted knee arthroplasty. An extensive literature search of PubMed, Medline, Embase, Web of Science, and Cochrane Library was conducted. Randomized controlled trials, comparative studies, and cohort studies were included. Outcomes assessed included: time required for surgery, stress levels of the surgical team, complications in regard to surgical experience level or time needed for surgery, size prediction of preoperative templating, and alignment according to the number of knee arthroplasties performed. A total of 11 studies met the inclusion criteria. Most were of medium to low quality. The operating time of robot-assisted total knee arthroplasty (TKA) and unicompartmental knee arthroplasty (UKA) is associated with a learning curve of between six to 20 cases and six to 36 cases respectively. Surgical team stress levels show a learning curve of seven cases in TKA and six cases for UKA. Experience with the robotic systems did not influence implant positioning, preoperative planning, and postoperative complications. Robot-assisted TKA and UKA is associated with a learning curve regarding operating time and surgical team stress levels. Future evaluation of robotics in the operating theatre should include detailed measurement of the various aspects of the total operating time, including total robotic time and time needed for preoperative planning. The prior experience of the surgical team should also be evaluated and reported.

Cite this article: Bone Joint J 2020;102-B(4):407–413.

Aims

Robotic-assisted unicompartmental knee arthroplasty (UKA) promises accurate implant placement with the potential of improved survival and functional outcomes. The aim of this study was to present the current evidence for robotic-assisted UKA and describe the outcome in terms of implant positioning, range of movement (ROM), function and survival, and the types of robot and implants that are currently used.

We performed a randomised controlled trial comparing computer-assisted surgery (CAS) with conventional surgery (CONV) in total knee replacement (TKR). Between 2009 and 2011 a total of 192 patients with a mean age of 68 years (55 to 85) with osteoarthritis or arthritic disease of the knee were recruited from four Norwegian hospitals. At three months follow-up, functional results were marginally better for the CAS group. Mean differences (MD) in favour of CAS were found for the Knee Society function score (MD: 5.9, 95% confidence interval (CI) 0.3 to 11.4, p = 0.039), the Knee Injury and Osteoarthritis Outcome Score (KOOS) subscales for ‘pain’ (MD: 7.7, 95% CI 1.7 to 13.6, p = 0.012), ‘sports’ (MD: 13.5, 95% CI 5.6 to 21.4, p = 0.001) and ‘quality of life’ (MD: 7.2, 95% CI 0.1 to 14.3, p = 0.046). At one-year follow-up, differences favouring CAS were found for KOOS ‘sports’ (MD: 11.0, 95% CI 3.0 to 19.0, p = 0.007) and KOOS ‘symptoms’ (MD: 6.7, 95% CI 0.5 to 13.0, p = 0.035). The use of CAS resulted in fewer outliers in frontal alignment (> 3° malalignment), both for the entire TKR (37.9% vs 17.9%, p = 0.042) and for the tibial component separately (28.4% vs 6.3%, p = 0.002). Tibial slope was better achieved with CAS (58.9% vs 26.3%, p < 0.001). Operation time was 20 minutes longer with CAS. In conclusion, functional results were, statistically, marginally in favour of CAS. Also, CAS was more predictable than CONV for mechanical alignment and positioning of the prosthesis. However, the long-term outcomes must be further investigated.

Cite this article: Bone Joint J 2014; 96-B:609–18.

We compared the orientation of the acetabular component obtained by a conventional manual technique with that using five different navigation systems.

Three surgeons carried out five implantations of an acetabular component with each navigation system, as well as manually, using an anatomical model. The orientation of the acetabular component, including inclination and anteversion, and its position was determined using a co-ordinate measuring machine.

The variation of the orientation of the acetabular component was higher in the conventional group compared with the navigated group. One experienced surgeon took significantly less time for the procedure. However, his placement of the component was no better than that of the less experienced surgeons. Significantly better inclination and anteversion (p < 0.001 for both) were obtained using navigation. These parameters were not significantly different between the surgeons when using the conventional technique (p = 0.966).

The use of computer navigation helps a surgeon to orientate the acetabular component with less variation regarding inclination and anteversion.