Aims

The objective of this study was to compare simulated range of motion (ROM) for reverse total shoulder arthroplasty (rTSA) with and without adjustment for scapulothoracic orientation in a global reference system. We hypothesized that values for simulated ROM in preoperative planning software with and without adjustment for scapulothoracic orientation would be significantly different.

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We aimed to compare reoperations following distal radial fractures (DRFs) managed with early fixation versus delayed fixation following initial closed reduction (CR).

Aims. The purpose of this study was to develop a convolutional neural network (CNN) for fracture detection, classification, and identification of greater tuberosity displacement ≥ 1 cm, neck-shaft angle (NSA) ≤ 100°, shaft translation, and articular fracture involvement, on plain radiographs. Methods. The CNN was trained and tested on radiographs sourced from 11 hospitals in Australia and externally validated on radiographs from the Netherlands. Each radiograph was paired with corresponding CT scans to serve as the reference standard based on dual independent evaluation by trained researchers and attending orthopaedic surgeons. Presence of a fracture, classification (non- to minimally displaced; two-part, multipart, and glenohumeral dislocation), and four characteristics were determined on 2D and 3D CT scans and subsequently allocated to each series of radiographs. Fracture characteristics included greater tuberosity displacement ≥ 1 cm, NSA ≤ 100°, shaft translation (0% to < 75%, 75% to 95%, > 95%), and the extent of articular involvement (0% to < 15%, 15% to 35%, or > 35%). Results. For detection and classification, the algorithm was trained on 1,709 radiographs (n = 803), tested on 567 radiographs (n = 244), and subsequently externally validated on 535 radiographs (n = 227). For characterization, healthy shoulders and glenohumeral dislocation were excluded. The overall accuracy for fracture detection was 94% (area under the receiver operating characteristic curve (AUC) = 0.98) and for classification 78% (AUC 0.68 to 0.93). Accuracy to detect greater tuberosity fracture displacement ≥ 1 cm was 35.0% (AUC 0.57). The CNN did not recognize NSAs ≤ 100° (AUC 0.42), nor fractures with ≥ 75% shaft translation (AUC 0.51 to 0.53), or with ≥ 15% articular involvement (AUC 0.48 to 0.49). For all objectives, the model’s performance on the external dataset showed similar accuracy levels. Conclusion. CNNs proficiently rule out proximal humerus fractures on plain radiographs. Despite rigorous training methodology based on CT imaging with multi-rater consensus to serve as the reference standard, artificial intelligence-driven classification is insufficient for clinical implementation. The CNN exhibited poor diagnostic ability to detect greater tuberosity displacement ≥ 1 cm and failed to identify NSAs ≤ 100°, shaft translations, or articular fractures. Cite this article: Bone Joint J 2024;106-B(11):1348–1360

Aims

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.

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Machine learning (ML), a branch of artificial intelligence that uses algorithms to learn from data and make predictions, offers a pathway towards more personalized and tailored surgical treatments. This approach is particularly relevant to prevalent joint diseases such as osteoarthritis (OA). In contrast to end-stage disease, where joint arthroplasty provides excellent results, early stages of OA currently lack effective therapies to halt or reverse progression. Accurate prediction of OA progression is crucial if timely interventions are to be developed, to enhance patient care and optimize the design of clinical trials.

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The risk factors for recurrent instability (RI) following a primary traumatic anterior shoulder dislocation (PTASD) remain unclear. In this study, we aimed to determine the rate of RI in a large cohort of patients managed nonoperatively after PTASD and to develop a clinical prediction model.

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To determine if patient ethnicity among patients with a hip fracture influences the type of fracture, surgical care, and outcome.

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This study aimed to gather insights from elbow experts using the Delphi method to evaluate the influence of patient characteristics and fracture morphology on the choice between operative and nonoperative treatment for coronoid fractures.

Aims. To propose a new method for evaluating paediatric radial neck fractures and improve the accuracy of fracture angulation measurement, particularly in younger children, and thereby facilitate planning treatment in this population. Methods. Clinical data of 117 children with radial neck fractures in our hospital from August 2014 to March 2023 were collected. A total of 50 children (26 males, 24 females, mean age 7.6 years (2 to 13)) met the inclusion criteria and were analyzed. Cases were excluded for the following reasons: Judet grade I and Judet grade IVb (> 85° angulation) classification; poor radiograph image quality; incomplete clinical information; sagittal plane angulation; severe displacement of the ulna fracture; and Monteggia fractures. For each patient, standard elbow anteroposterior (AP) view radiographs and corresponding CT images were acquired. On radiographs, Angle P (complementary to the angle between the long axis of the radial head and the line perpendicular to the physis), Angle S (complementary to the angle between the long axis of the radial head and the midline through the proximal radial shaft), and Angle U (between the long axis of the radial head and the straight line from the distal tip of the capitellum to the coronoid process) were identified as candidates approximating the true coronal plane angulation of radial neck fractures. On the coronal plane of the CT scan, the angulation of radial neck fractures (CTa) was measured and served as the reference standard for measurement. Inter- and intraobserver reliabilities were assessed by Kappa statistics and intraclass correlation coefficient (ICC). Results. Angle U showed the strongest correlation with CTa (p < 0.001). In the analysis of inter- and intraobserver reliability, Kappa values were significantly higher for Angles S and U compared with Angle P. ICC values were excellent among the three groups. Conclusion. Angle U on AP view was the best substitute for CTa when evaluating radial neck fractures in children. Further studies are required to validate this method. Cite this article: Bone Joint J 2024;106-B(9):964–969

Aims

The primary objective of this study was to develop a validated classification system for assessing iatrogenic bone trauma and soft-tissue injury during total hip arthroplasty (THA). The secondary objective was to compare macroscopic bone trauma and soft-tissues injury in conventional THA (CO THA) versus robotic arm-assisted THA (RO THA) using this classification system.

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: Bone Joint J 2024;106-B(9):892–897.

Aims. Conventional patient-reported surveys, used for patients undergoing total hip arthroplasty (THA), are limited by subjectivity and recall bias. Objective functional evaluation, such as gait analysis, to delineate a patient’s functional capacity and customize surgical interventions, may address these shortcomings. This systematic review endeavours to investigate the application of objective functional assessments in appraising individuals undergoing THA. Methods. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were applied. Eligible studies of THA patients that conducted at least one type of objective functional assessment both pre- and postoperatively were identified through Embase, Medline/PubMed, and Cochrane Central database-searching from inception to 15 September 2023. The assessments included were subgrouped for analysis: gait analysis, motion analysis, wearables, and strength tests. Results. A total of 130 studies using 15 distinct objective functional assessment methods (FAMs) were identified. The most frequently used method was instrumented gait/motion analysis, followed by the Timed-Up-and-Go test (TUG), 6 minute walk test, timed stair climbing test, and various strength tests. These assessments were characterized by their diagnostic precision and applicability to daily activities. Wearables were frequently used, offering cost-effectiveness and remote monitoring benefits. However, their accuracy and potential discomfort for patients must be considered. Conclusion. The integration of objective functional assessments in THA presents promise as a progress-tracking modality for improving patient outcomes. Gait analysis and the TUG, along with advancing wearable sensor technology, have the potential to enhance patient care, surgical planning, and rehabilitation. Cite this article: Bone Joint J 2024;106-B(8):764–774

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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 robotic arm-assisted revision of unicompartmental knee arthroplasty (UKA) to total knee arthroplasty (TKA) versus primary robotic arm-assisted TKA at short-term follow-up.

Aims. To examine whether natural language processing (NLP) using a clinically based large language model (LLM) could be used to predict patient selection for total hip or total knee arthroplasty (THA/TKA) from routinely available free-text radiology reports. Methods. Data pre-processing and analyses were conducted according to the Artificial intelligence to Revolutionize the patient Care pathway in Hip and knEe aRthroplastY (ARCHERY) project protocol. This included use of de-identified Scottish regional clinical data of patients referred for consideration of THA/TKA, held in a secure data environment designed for artificial intelligence (AI) inference. Only preoperative radiology reports were included. NLP algorithms were based on the freely available GatorTron model, a LLM trained on over 82 billion words of de-identified clinical text. Two inference tasks were performed: assessment after model-fine tuning (50 Epochs and three cycles of k-fold cross validation), and external validation. Results. For THA, there were 5,558 patient radiology reports included, of which 4,137 were used for model training and testing, and 1,421 for external validation. Following training, model performance demonstrated average (mean across three folds) accuracy, F1 score, and area under the receiver operating curve (AUROC) values of 0.850 (95% confidence interval (CI) 0.833 to 0.867), 0.813 (95% CI 0.785 to 0.841), and 0.847 (95% CI 0.822 to 0.872), respectively. For TKA, 7,457 patient radiology reports were included, with 3,478 used for model training and testing, and 3,152 for external validation. Performance metrics included accuracy, F1 score, and AUROC values of 0.757 (95% CI 0.702 to 0.811), 0.543 (95% CI 0.479 to 0.607), and 0.717 (95% CI 0.657 to 0.778) respectively. There was a notable deterioration in performance on external validation in both cohorts. Conclusion. The use of routinely available preoperative radiology reports provides promising potential to help screen suitable candidates for THA, but not for TKA. The external validation results demonstrate the importance of further model testing and training when confronted with new clinical cohorts. Cite this article: Bone Joint J 2024;106-B(7):688–695

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Intra-articular (IA) injection may be used when treating hip osteoarthritis (OA). Common injections include steroids, hyaluronic acid (HA), local anaesthetic, and platelet-rich plasma (PRP). Network meta-analysis allows for comparisons between two or more treatment groups and uses direct and indirect comparisons between interventions. This network meta-analysis aims to compare the efficacy of various IA injections used in the management of hip OA with a follow-up of up to six months.

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This study compares the re-revision rate and mortality following septic and aseptic revision hip arthroplasty (rTHA) in registry data, and compares the outcomes to previously reported data.

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This study aims to assess the relationship between history of pseudotumour formation secondary to metal-on-metal (MoM) implants and periprosthetic joint infection (PJI) rate, as well as establish ESR and CRP thresholds that are suggestive of infection in these patients. We hypothesized that patients with a pseudotumour were at increased risk of infection.

Aims. Accurate diagnosis of chronic periprosthetic joint infection (PJI) presents a significant challenge for hip surgeons. Preoperative diagnosis is not always easy to establish, making the intraoperative decision-making process crucial in deciding between one- and two-stage revision total hip arthroplasty (THA). Calprotectin is a promising point-of-care novel biomarker that has displayed high accuracy in detecting PJI. We aimed to evaluate the utility of intraoperative calprotectin lateral flow immunoassay (LFI) in THA patients with suspected chronic PJI. Methods. The study included 48 THAs in 48 patients with a clinical suspicion of PJI, but who did not meet European Bone and Joint Infection Society (EBJIS) PJI criteria preoperatively, out of 105 patients undergoing revision THA at our institution for possible PJI between November 2020 and December 2022. Intraoperatively, synovial fluid calprotectin was measured with LFI. Cases with calprotectin levels ≥ 50 mg/l were considered infected and treated with two-stage revision THA; in negative cases, one-stage revision was performed. At least five tissue cultures were obtained; the implants removed were sent for sonication. Results. Calprotectin was positive (≥ 50 mg/l) in 27 cases; out of these, 25 had positive tissue cultures and/or sonication. Calprotectin was negative in 21 cases. There was one false negative case, which had positive tissue cultures. Calprotectin showed an area under the curve of 0.917, sensitivity of 96.2%, specificity of 90.9%, positive predictive value of 92.6%, negative predictive value of 95.2%, positive likelihood ratio of 10.6, and negative likelihood ratio of 0.04. Overall, 45/48 patients were correctly diagnosed and treated by our algorithm, which included intraoperative calprotectin measurement. This yielded a 93.8% concordance with postoperatively assessed EBJIS criteria. Conclusion. Calprotectin can be a valuable tool in facilitating the intraoperative decision-making process for cases in which chronic PJI is suspected and diagnosis cannot be established preoperatively. Cite this article: Bone Joint J 2024;106-B(5 Supple B):118–124

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The purpose of this study was to assess the success rate and functional outcomes of bone grafting for periprosthetic bone cysts following total ankle arthroplasty (TAA). Additionally, we evaluated the rate of graft incorporation and identified associated predisposing factors using CT scan.

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The aims of this study were to determine the success of a reconstruction algorithm used in major acetabular bone loss, and to further define the indications for custom-made implants in major acetabular bone loss.