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.

Aims

While mechanical alignment (MA) is the traditional technique in total knee arthroplasty (TKA), its potential for altering constitutional alignment remains poorly understood. This study aimed to quantify unintentional changes to constitutional coronal alignment and joint line obliquity (JLO) resulting from MA.

Aims

Distal femoral resection in conventional total knee arthroplasty (TKA) utilizes an intramedullary guide to determine coronal alignment, commonly planned for 5° of valgus. However, a standard 5° resection angle may contribute to malalignment in patients with variability in the femoral anatomical and mechanical axis angle. The purpose of the study was to leverage deep learning (DL) to measure the femoral mechanical-anatomical axis angle (FMAA) in a heterogeneous cohort.

Total hip and knee arthroplasty (THA, TKA) are largely successful procedures; however, both have variable outcomes, resulting in some patients being dissatisfied with the outcome. Surgeons are turning to technologies such as robotic-assisted surgery in an attempt to improve outcomes. Robust studies are needed to find out if these innovations are really benefitting patients. The Robotic Arthroplasty Clinical and Cost Effectiveness Randomised Controlled Trials (RACER) trials are multicentre, patient-blinded randomized controlled trials. The patients have primary osteoarthritis of the hip or knee. The operation is Mako-assisted THA or TKA and the control groups have operations using conventional instruments. The primary clinical outcome is the Forgotten Joint Score at 12 months, and there is a built-in analysis of cost-effectiveness. Secondary outcomes include early pain, the alignment of the components, and medium- to long-term outcomes. This annotation outlines the need to assess these technologies and discusses the design and challenges when conducting such trials, including surgical workflows, isolating the effect of the operation, blinding, and assessing the learning curve. Finally, the future of robotic surgery is discussed, including the need to contemporaneously introduce and evaluate such technologies.

Cite this article: Bone Joint J 2024;106-B(2):114–120.

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 aims of this study were to determine if an increasing serum cobalt (Co) and/or chromium (Cr) concentration is correlated with a decreasing Harris Hip Score (HHS) and Hip disability and Osteoarthritis Outcome Score (HOOS) in patients who received the Articular Surface Replacement (ASR) hip resurfacing arthroplasty (HRA), and to evaluate the ten-year revision rate and show if sex, inclination angle, and Co level influenced the revision rate.

Orthopaedic surgeons are currently faced with an overwhelming number of choices surrounding total knee arthroplasty (TKA), not only with the latest technologies and prostheses, but also fundamental decisions on alignment philosophies. From ‘mechanical’ to ‘adjusted mechanical’ to ‘restricted kinematic’ to ‘unrestricted kinematic’ — and how constitutional alignment relates to these — there is potential for ambiguity when thinking about and discussing such concepts. This annotation summarizes the various alignment strategies currently employed in TKA. It provides a clear framework and consistent language that will assist surgeons to compare confidently and contrast the concepts, while also discussing the latest opinions about alignment in TKA. Finally, it provides suggestions for applying consistent nomenclature to future research, especially as we explore the implications of 3D alignment patterns on patient outcomes.

Cite this article: Bone Joint J 2023;105-B(2):102–108.

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.

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.

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?

Aims. Navigation devices are designed to improve a surgeon’s accuracy in positioning the acetabular and femoral components in total hip arthroplasty (THA). The purpose of this study was to both evaluate the accuracy of an optical computer-assisted surgery (CAS) navigation system and determine whether preoperative spinopelvic mobility (categorized as hypermobile, normal, or stiff) increased the risk of acetabular component placement error. Methods. A total of 356 patients undergoing primary THA were prospectively enrolled from November 2016 to March 2018. Clinically relevant error using the CAS system was defined as a difference of > 5° between CAS and 3D radiological reconstruction measurements for acetabular component inclination and anteversion. Univariate and multiple logistic regression analyses were conducted to determine whether hypermobile (. Δ. sacral slope(SS). stand-sit. > 30°), or stiff (. ∆. SS. stand-sit. < 10°) spinopelvic mobility contributed to increased error rates. Results. The paired absolute difference between CAS and postoperative imaging measurements was 2.3° (standard deviation (SD) 2.6°) for inclination and 3.1° (SD 4.2°) for anteversion. Using a target zone of 40° (± 10°) (inclination) and 20° (± 10°) (anteversion), postoperative standing radiographs measured 96% of acetabular components within the target zone for both inclination and anteversion. Multiple logistic regression analysis controlling for BMI and sex revealed that hypermobile spinopelvic mobility significantly increased error rates for anteversion (odds ratio (OR) 2.48, p = 0.009) and inclination (OR 2.44, p = 0.016), whereas stiff spinopelvic mobility increased error rates for anteversion (OR 1.97, p = 0.028). There were no dislocations at a minimum three-year follow-up. Conclusion. Despite high reliability in acetabular positioning for inclination in a large patient cohort using an optical CAS system, hypermobile and stiff spinopelvic mobility significantly increased the risk of clinically relevant errors. In patients with abnormal spinopelvic mobility, CAS systems should be adjusted for use to avoid acetabular component misalignment and subsequent risk for long-term dislocation. Cite this article: Bone Jt Open 2022;3(6):475–484

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.

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.