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
Aim. There has been a significant reduction in unicompartmental knee arthroplasty (UKA) procedures recorded in Australia. This follows several national joint registry studies documenting high UKA revision rates when compared to total knee arthroplasty (TKA). With the recent introduction of
Aims. The aim of this study was to compare the clinical outcomes of
Aims. The aim of this study was to compare any differences in the primary outcome (biphasic flexion knee moment during gait) of
The aim was to assess whether robotic-assisted total knee arthroplasty (rTKA) had greater knee-specific outcomes, improved fulfilment of expectations, health-related quality of life (HRQoL), and patient satisfaction when compared with manual TKA (mTKA). A randomized controlled trial was undertaken (May 2019 to December 2021), and patients were allocated to either mTKA or rTKA. A total of 100 patients were randomized, 50 to each group, of whom 43 rTKA and 38 mTKA patients were available for review at 12 months following surgery. There were no statistically significant preoperative differences between the groups. The minimal clinically important difference in the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain score was defined as 7.5 points.Aims
Methods
The aim of this study was to analyze the true costs associated with preoperative CT scans performed for robotic-assisted total knee arthroplasty (RATKA) planning and to determine the value of a formal radiologist’s report of these studies. We reviewed 194 CT reports of 176 sequential patients who underwent primary RATKA by a single surgeon at a suburban teaching hospital. CT radiology reports were reviewed for the presence of incidental findings that might change the management of the patient. Payments for the scans, including the technical and professional components, for 330 patients at two hospitals were also recorded and compared.Aims
Methods
We performed a prospective, randomised controlled trial of unicompartmental knee arthroplasty comparing the performance of the Acrobot system with conventional surgery. A total of 27 patients (28 knees) awaiting unicompartmental knee arthroplasty were randomly allocated to have the operation performed conventionally or with the assistance of the Acrobot. The primary outcome measurement was the angle of tibiofemoral alignment in the coronal plane, measured by CT. Other secondary parameters were evaluated and are reported. All of the Acrobot group had tibiofemoral alignment in the coronal plane within 2° of the planned position, while only 40% of the conventional group achieved this level of accuracy. While the operations took longer, no adverse effects were noted, and there was a trend towards improvement in performance with increasing accuracy based on the Western Ontario and McMaster Universities Osteoarthritis Index and American Knee Society scores at six weeks and three months. The Acrobot device allows the surgeon to reproduce a pre-operative plan more reliably than is possible using conventional techniques which may have clinical advantages.
Aims. Robotic arm-assisted surgery offers accurate and reproducible guidance in component positioning and assessment of soft-tissue tensioning during knee arthroplasty, but the feasibility and early outcomes when using this technology for revision surgery remain unknown. The objective of this study was to compare the outcomes of
Aims. Unicompartmental knee arthroplasty (UKA) is a bone-preserving treatment option for osteoarthritis localized to a single compartment in the knee. The success of the procedure is sensitive to patient selection and alignment errors. Robotic arm-assisted UKA provides technological assistance to intraoperative bony resection accuracy, which is thought to improve ligament balancing. This paper presents the five-year outcomes of a comparison between manual and
Aims. The primary aim was to assess whether
Aims. The primary aim of this study was to compare the postoperative systemic inflammatory response in conventional jig-based total knee arthroplasty (conventional TKA) versus robotic-arm assisted total knee arthroplasty (robotic TKA). Secondary aims were to compare the macroscopic soft tissue injury, femoral and tibial bone trauma, localized thermal response, and the accuracy of component positioning between the two treatment groups. Methods. This prospective randomized controlled trial included 30 patients with osteoarthritis of the knee undergoing conventional TKA versus
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
Aims. The purpose of this multicentre observational study was to investigate the association between intraoperative component positioning and soft-tissue balancing on short-term clinical outcomes in patients undergoing robotic-arm assisted unicompartmental knee arthroplasty (UKA). Patients and Methods. Between 2013 and 2016, 363 patients (395 knees) underwent robotic-arm assisted UKAs at two centres. Pre- and postoperatively, patients were administered Knee Injury and Osteoarthritis Score (KOOS) and Forgotten Joint Score-12 (FJS-12). Results were stratified as “good” and “bad” if KOOS/FJS-12 were more than or equal to 80. Intraoperative, post-implantation
Aims. Ideal component sizing may be difficult to achieve in unicompartmental knee arthroplasty (UKA). Anatomical variants, incremental implant size, and a reduced surgical exposure may lead to over- or under-sizing of the components. The purpose of this study was to compare the accuracy of UKA sizing with robotic-assisted techniques versus a conventional surgical technique. Methods. Three groups of 93 medial UKAs were assessed. The first group was performed by a conventional technique, the second group with an image-free robotic-assisted system (Image-Free group), and the last group with an image-based
Aims. The aim of this study was to compare
Aims. The objective of this study is to assess the use of ultrasound (US) as a radiation-free imaging modality to reconstruct 3D anatomy of the knee for use in preoperative templating in knee arthroplasty. Methods. Using an US system, which is fitted with an electromagnetic (EM) tracker that is integrated into the US probe, allows 3D tracking of the probe, femur, and tibia. The raw US radiofrequency (RF) signals are acquired and, using real-time signal processing, bone boundaries are extracted. Bone boundaries and the tracking information are fused in a 3D point cloud for the femur and tibia. Using a statistical shaping model, the patient-specific surface is reconstructed by optimizing bone geometry to match the point clouds. An accuracy analysis was conducted for 17 cadavers by comparing the 3D US models with those created using CT. US scans from 15 users were compared in order to examine the effect of operator variability on the output. Results. The results revealed that the US bone models were accurate compared with the CT models (root mean squared error (RM)S: femur, 1.07 mm (SD 0.15); tibia, 1.02 mm (SD 0.13). Additionally, femoral landmarking proved to be accurate (transepicondylar axis: 1.07° (SD 0.65°); posterior condylar axis: 0.73° (SD 0.41°); distal condylar axis: 0.96° (SD 0.89°); medial anteroposterior (AP): 1.22 mm (SD 0.69); lateral AP: 1.21 mm (SD 1.02)). Tibial landmarking errors were slightly higher (posterior slope axis: 1.92° (SD 1.31°); and tubercle axis: 1.91° (SD 1.24°)). For implant sizing, 90% of the femora and 60% of the tibiae were sized correctly, while the remainder were only one size different from the required implant size. No difference was observed between moderate and skilled users. Conclusion. The 3D US bone models were proven to be closely matched compared with CT and suitable for preoperative planning. The 3D US is radiation-free and offers numerous clinical opportunities for bone visualization rapidly during clinic visits, to enable preoperative planning with implant sizing. There is potential to extend its application to 3D dynamic ligament balancing, and intraoperative registration for use with
Aims. It remains controversial whether patellofemoral joint pathology is a contraindication to lateral unicompartmental knee arthroplasty (UKA). This study aimed to evaluate the effect of preoperative radiological degenerative changes and alignment on patient-reported outcome scores (PROMs) after lateral UKA. Secondarily, the influence of lateral UKA on the alignment of the patellofemoral joint was studied. Methods. A consecutive series of patients who underwent
Aims. The objectives of this study were to compare postoperative pain, analgesia requirements, inpatient functional rehabilitation, time to hospital discharge, and complications in patients undergoing conventional jig-based unicompartmental knee arthroplasty (UKA) versus robotic-arm assisted UKA. Patients and Methods. This prospective cohort study included 146 patients with symptomatic medial compartment knee osteoarthritis undergoing primary UKA performed by a single surgeon. This included 73 consecutive patients undergoing conventional jig-based mobile bearing UKA, followed by 73 consecutive patients receiving robotic-arm assisted fixed bearing UKA. All surgical procedures were performed using the standard medial parapatellar approach for UKA, and all patients underwent the same postoperative rehabilitation programme. Postoperative pain scores on the numerical rating scale and opiate analgesia consumption were recorded until discharge. Time to attainment of predefined functional rehabilitation outcomes, hospital discharge, and postoperative complications were recorded by independent observers. Results. Robotic-arm assisted UKA was associated with reduced postoperative pain (p < 0.001), decreased opiate analgesia requirements (p < 0.001), shorter time to straight leg raise (p < 0.001), decreased number of physiotherapy sessions (p < 0.001), and increased maximum knee flexion at discharge (p < 0.001) compared with conventional jig-based UKA. Mean time to hospital discharge was reduced in
Aims. The primary aim of this study was to determine the surgical team’s
learning curve for introducing robotic-arm assisted unicompartmental
knee arthroplasty (UKA) into routine surgical practice. The secondary
objective was to compare accuracy of implant positioning in conventional
jig-based UKA versus robotic-arm assisted UKA. Patients and Methods. This prospective single-surgeon cohort study included 60 consecutive
conventional jig-based UKAs compared with 60 consecutive robotic-arm
assisted UKAs for medial compartment knee osteoarthritis. Patients
undergoing conventional UKA and robotic-arm assisted UKA were well-matched
for baseline characteristics including a mean age of 65.5 years
(. sd. 6.8) vs 64.1 years (. sd. 8.7), (p = 0.31); a
mean body mass index of 27.2 kg.m2 (. sd. 2.7) vs 28.1 kg.m2
(. sd. 4.5), (p = 0.25); and gender (27 males: 33 females
vs 26 males: 34 females, p = 0.85). Surrogate measures of the learning
curve were prospectively collected. These included operative times,
the Spielberger State-Trait Anxiety Inventory (STAI) questionnaire
to assess preoperative stress levels amongst the surgical team,
accuracy of implant positioning, limb alignment, and postoperative
complications. Results. Robotic-arm assisted UKA was associated with a learning curve
of six cases for operating time (p < 0.001) and surgical team
confidence levels (p < 0.001). Cumulative
The surgical target for optimal implant positioning in robotic-assisted total knee arthroplasty remains the subject of ongoing discussion. One of the proposed targets is to recreate the knee’s functional behaviour as per its pre-diseased state. The aim of this study was to optimize implant positioning, starting from mechanical alignment (MA), toward restoring the pre-diseased status, including ligament strain and kinematic patterns, in a patient population. We used an active appearance model-based approach to segment the preoperative CT of 21 osteoarthritic patients, which identified the osteophyte-free surfaces and estimated cartilage from the segmented bones; these geometries were used to construct patient-specific musculoskeletal models of the pre-diseased knee. Subsequently, implantations were simulated using the MA method, and a previously developed optimization technique was employed to find the optimal implant position that minimized the root mean square deviation between pre-diseased and postoperative ligament strains and kinematics.Aims
Methods