This study investigates the use of the metabolic equivalent of task (MET) score in a young hip arthroplasty population, and its ability to capture additional benefit beyond the ceiling effect of conventional patient-reported outcome measures. From our electronic database of 751 hip arthroplasty procedures, 221 patients were included. Patients were excluded if they had revision surgery, an alternative hip procedure, or incomplete data either preoperatively or at one-year follow-up. Included patients had a mean age of 59.4 years (SD 11.3) and 54.3% were male, incorporating 117 primary total hip and 104 hip resurfacing arthroplasty operations. Oxford Hip Score (OHS), EuroQol five-dimension questionnaire (EQ-5D), and the MET were recorded preoperatively and at one-year follow-up. The distribution was examined reporting the presence of ceiling and floor effects. Validity was assessed correlating the MET with the other scores using Spearman’s rank correlation coefficient and determining responsiveness. A subgroup of 93 patients scoring 48/48 on the OHS were analyzed by age, sex, BMI, and preoperative MET using the other metrics to determine if differences could be established despite scoring identically on the OHS.Aims
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No predictive model has been published to forecast operating time for total knee arthroplasty (TKA). The aims of this study were to design and validate a predictive model to estimate operating time for robotic-assisted TKA based on demographic data, and evaluate the added predictive power of CT scan-based predictors and their impact on the accuracy of the predictive model. A retrospective study was conducted on 1,061 TKAs performed from January 2016 to December 2019 with an image-based robotic-assisted system. Demographic data included age, sex, height, and weight. The femoral and tibial mechanical axis and the osteophyte volume were calculated from CT scans. These inputs were used to develop a predictive model aimed to predict operating time based on demographic data only, and demographic and 3D patient anatomy data.Aims
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Artificial intelligence (AI) is, in essence, the concept of ‘computer thinking’, encompassing methods that train computers to perform and learn from executing certain tasks, called machine learning, and methods to build intricate computer models that both learn and adapt, called complex neural networks. Computer vision is a function of AI by which machine learning and complex neural networks can be applied to enable computers to capture, analyze, and interpret information from clinical images and visual inputs. This annotation summarizes key considerations and future perspectives concerning computer vision, questioning the need for this technology (the ‘why’), the current applications (the ‘what’), and the approach to unlocking its full potential (the ‘how’). Cite this article:
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? A prospective, multicentre, trial enrolled 100 patients undergoing KA TKA using IDI, with follow-up to five years. Alignment measures were conducted pre- and postoperatively to assess constitutional alignment and final implant position. Patient-reported outcome measures (PROMs) of pain and function were also included. The Australian Orthopaedic Association National Joint Arthroplasty Registry was used to assess survivorship.Aims
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The aim of this study was to estimate the clinical and economic burden of dislocation following primary total hip arthroplasty (THA) in England. This retrospective evaluation used data from the UK Clinical Practice Research Datalink database. Patients were eligible if they underwent a primary THA (index date) and had medical records available 90 days pre-index and 180 days post-index. Bilateral THAs were excluded. Healthcare costs and resource use were evaluated over two years. Changes (pre- vs post-THA) in generic quality of life (QoL) and joint-specific disability were evaluated. Propensity score matching controlled for baseline differences between patients with and without THA dislocation.Aims
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The aims of this study were to assess mapping models to predict the three-level version of EuroQoL five-dimension utility index (EQ-5D-3L) from the Oxford Knee Score (OKS) and validate these before and after total knee arthroplasty (TKA). A retrospective cohort of 5,857 patients was used to create the prediction models, and a second cohort of 721 patients from a different centre was used to validate the models, all of whom underwent TKA. Patient characteristics, BMI, OKS, and EQ-5D-3L were collected preoperatively and one year postoperatively. Generalized linear regression was used to formulate the prediction models.Aims
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Unicompartmental knee arthroplasty (UKA) has a higher risk of revision than total knee arthroplasty (TKA), particularly for younger patients. The outcome of knee arthroplasty is typically defined as implant survival or revision incidence after a defined number of years. This can be difficult for patients to conceptualize. We aimed to calculate the ‘lifetime risk’ of revision for UKA as a more meaningful estimate of risk projection over a patient’s remaining lifetime, and to compare this to TKA. Incidence of revision and mortality for all primary UKAs performed from 1999 to 2019 (n = 13,481) was obtained from the New Zealand Joint Registry (NZJR). Lifetime risk of revision was calculated for patients and stratified by age, sex, and American Society of Anesthesiologists (ASA) grade.Aims
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This study aimed to evaluate the accuracy of implant placement with robotic-arm assisted total hip arthroplasty (THA) in patients with developmental dysplasia of the hip (DDH). The study analyzed a consecutive series of 69 patients who underwent robotic-arm assisted THA between September 2018 and December 2019. Of these, 30 patients had DDH and were classified according to the Crowe type. Acetabular component alignment and 3D positions were measured using pre- and postoperative CT data. The absolute differences of cup alignment and 3D position were compared between DDH and non-DDH patients. Moreover, these differences were analyzed in relation to the severity of DDH. The discrepancy of leg length and combined offset compared with contralateral hip were measured.Aims
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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
Robotic-assisted total knee arthroplasty (RA-TKA) is theoretically more accurate for component positioning than TKA performed with mechanical instruments (M-TKA). Furthermore, the ability to incorporate soft-tissue laxity data into the plan prior to bone resection should reduce variability between the planned polyethylene thickness and the final implanted polyethylene. The purpose of this study was to compare accuracy to plan for component positioning and precision, as demonstrated by deviation from plan for polyethylene insert thickness in measured-resection RA-TKA versus M-TKA. A total of 220 consecutive primary TKAs between May 2016 and November 2018, performed by a single surgeon, were reviewed. Planned coronal plane component alignment and overall limb alignment were all 0° to the mechanical axis; tibial posterior slope was 2°; and polyethylene thickness was 9 mm. For RA-TKA, individual component position was adjusted to assist gap-balancing but planned coronal plane alignment for the femoral and tibial components and overall limb alignment remained 0 ± 3°; planned tibial posterior slope was 1.5°. Mean deviations from plan for each parameter were compared between groups for positioning and size and outliers were assessed.Aims
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Intraoperative pressure sensors allow surgeons to quantify soft-tissue balance during total knee arthroplasty (TKA). The aim of this study was to determine whether using sensors to achieve soft-tissue balance was more effective than manual balancing in improving outcomes in TKA. A multicentre randomized trial compared the outcomes of sensor balancing (SB) with manual balancing (MB) in 250 patients (285 TKAs). The primary outcome measure was the mean difference in the four Knee injury and Osteoarthritis Outcome Score subscales (ΔKOOS4) in the two groups, comparing the preoperative and two-year scores. Secondary outcomes included intraoperative balance data, additional patient-reported outcome measures (PROMs), and functional measures.Aims
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The purpose of this study was to compare the radiological outcomes of manual versus robotic-assisted medial unicompartmental knee arthroplasty (UKA). Postoperative radiological outcomes from 86 consecutive robotic-assisted UKAs (RAUKA group) from a single academic centre were retrospectively reviewed and compared to 253 manual UKAs (MUKA group) drawn from a prior study at our institution. Femoral coronal and sagittal angles (FCA, FSA), tibial coronal and sagittal angles (TCA, TSA), and implant overhang were radiologically measured to identify outliers.Aims
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Orthopaedic surgeons use a variety of instruments to help correct, treat, and heal bone disease. The development of these instruments mirrors the history of orthopaedic surgery. The history of bonesetting, the treatment and replacement of joints, and of those who performed these techniques, appears to originate deep in antiquity. Changing ideas within medicine and surgery over the last 200 years have shaped the discovery and evolution of orthopaedic instruments and of the bonesetters themselves. Advances have led to the use of computers as instruments in the navigational guidance of arthroplasty surgery, the use of
The goal of the current systematic review was to assess the impact of implant placement accuracy on outcomes following total knee arthroplasty (TKA). A systematic review was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines using the Ovid Medline, Embase, Cochrane Central, and Web of Science databases in order to assess the impact of the patient-reported outcomes measures (PROMs) and implant placement accuracy on outcomes following TKA. Studies assessing the impact of implant alignment, rotation, size, overhang, or condylar offset were included. Study quality was assessed, evidence was graded (one-star: no evidence, two-star: limited evidence, three-star: moderate evidence, four-star: strong evidence), and recommendations were made based on the available evidence.Aims
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