Aims. The purpose of this study was to compare the radiological outcomes of manual versus robotic-assisted medial unicompartmental knee arthroplasty (UKA). Methods. 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. Results. When assessing the accuracy of RAUKAs, 91.6% of all alignment measurements and 99.2% of all overhang measurements were within the target range. All alignment and overhang targets were simultaneously met in 68.6% of RAUKAs. When comparing radiological outcomes between the RAUKA and MUKA groups, statistically significant differences were identified for combined outliers in FCA (2.3% vs 12.6%; p = 0.006), FSA (17.4% vs 50.2%; p < 0.001), TCA (5.8% vs 41.5%; p < 0.001), and TSA (8.1% vs 18.6%; p = 0.023), as well as anterior (0.0% vs 4.7%; p = 0.042), posterior (1.2% vs 13.4%; p = 0.001), and medial (1.2% vs 14.2%; p < 0.001) overhang outliers. Conclusion. Robotic system navigation decreases alignment and overhang outliers compared to manual UKA. Given the association between component placement errors and revision in UKA, this strong significant improvement in accuracy may improve implant survival. Level of Evidence: III. Cite this article: Bone Jt Open 2021;2-3:191–197

Aims. Natural Language Processing (NLP) offers an automated method to extract data from unstructured free text fields for arthroplasty registry participation. Our objective was to investigate how accurately NLP can be used to extract structured clinical data from unstructured clinical notes when compared with manual data extraction. Methods. A group of 1,000 randomly selected clinical and hospital notes from eight different surgeons were collected for patients undergoing primary arthroplasty between 2012 and 2018. In all, 19 preoperative, 17 operative, and two postoperative variables of interest were manually extracted from these notes. A NLP algorithm was created to automatically extract these variables from a training sample of these notes, and the algorithm was tested on a random test sample of notes. Performance of the NLP algorithm was measured in Statistical Analysis System (SAS) by calculating the accuracy of the variables collected, the ability of the algorithm to collect the correct information when it was indeed in the note (sensitivity), and the ability of the algorithm to not collect a certain data element when it was not in the note (specificity). Results. The NLP algorithm performed well at extracting variables from unstructured data in our random test dataset (accuracy = 96.3%, sensitivity = 95.2%, and specificity = 97.4%). It performed better at extracting data that were in a structured, templated format such as range of movement (ROM) (accuracy = 98%) and implant brand (accuracy = 98%) than data that were entered with variation depending on the author of the note such as the presence of deep-vein thrombosis (DVT) (accuracy = 90%). Conclusion. The NLP algorithm used in this study was able to identify a subset of variables from randomly selected unstructured notes in arthroplasty with an accuracy above 90%. For some variables, such as objective exam data, the accuracy was very high. Our findings suggest that automated algorithms using NLP can help orthopaedic practices retrospectively collect information for registries and quality improvement (QI) efforts. Cite this article: Bone Joint J 2020;102-B(7 Supple B):99–104

Aims. The preoperative diagnosis of periprosthetic joint infection (PJI) remains a challenge due to a lack of biomarkers that are both sensitive and specific. We investigated the performance characteristics of polymerase chain reaction (PCR), interleukin-6 (IL6), and calprotectin of synovial fluid in the diagnosis of PJI. Methods. We performed systematic search of PubMed, Embase, The Cochrane Library, Web of Science, and Science Direct from the date of inception of each database through to 31 May 2021. Studies which described the diagnostic accuracy of synovial fluid PCR, IL6, and calprotectin using the Musculoskeletal Infection Society criteria as the reference standard were identified. Results. Overall, 31 studies were identified: 20 described PCR, six described IL6, and five calprotectin. The sensitivity and specificity were 0.78 (95% confidence interval (CI) 0.67 to 0.86) and 0.97 (95% CI 0.94 to 0.99), respectively, for synovial PCR;, 0.86 (95% CI 0.74 to 0.92), and 0.94 (95% CI 0.90 to 0.96), respectively, for synovial IL6; and 0.94 (95% CI 0.82 to 0.98) and 0.93 (95% CI 0.85 to 0.97), respectively, for synovial calprotectin. Likelihood ratio scattergram analyses recommended clinical utility of synovial fluid PCR and IL6 as a confirmatory test only. Synovial calprotectin had utility in the exclusion and confirmation of PJI. Conclusion. Synovial fluid PCR and IL6 had low sensitivity and high specificity in the diagnosis of PJI, and is recommended to be used as confirmatory test. In contrast, synovial fluid calprotectin had both high sensitivity and specificity with utility in both the exclusion and confirmation of PJI. We recommend use of synovial fluid calprotectin studies in the preoperative workup of PJI. Cite this article: Bone Joint J 2022;104-B(3):311–320

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

Aims. Synovial fluid white blood cell (WBC) count and percentage of polymorphonuclear cells (%PMN) are elevated at periprosthetic joint infection (PJI). Leucocytes produce different interleukins (IL), including IL-6, so we hypothesized that synovial fluid IL-6 could be a more accurate predictor of PJI than synovial fluid WBC count and %PMN. The main aim of our study was to compare the predictive performance of all three diagnostic tests in the detection of PJI. Methods. Patients undergoing total hip or knee revision surgery were included. In the perioperative assessment phase, synovial fluid WBC count, %PMN, and IL-6 concentration were measured. Patients were labeled as positive or negative according to the predefined cut-off values for IL-6 and WBC count with %PMN. Intraoperative samples for microbiological and histopathological analysis were obtained. PJI was defined as the presence of sinus tract, inflammation in histopathological samples, and growth of the same microorganism in a minimum of two or more samples out of at least four taken. Results. In total, 49 joints in 48 patients (mean age 68 years (SD 10; 26 females (54%), 25 knees (51%)) were included. Of these 11 joints (22%) were infected. The synovial fluid WBC count and %PMN predicted PJI with sensitivity, specificity, accuracy, PPV, and NPV of 82%, 97%, 94%, 90%, and 95%, respectively. Synovial fluid IL-6 predicted PJI with sensitivity, specificity, accuracy, PPV, and NPV of 73%, 95%, 90%, 80%, and 92%, respectively. A comparison of predictive performance indicated a strong agreement between tests. Conclusions. Synovial fluid IL-6 is not superior to synovial fluid WBC count and %PMN in detecting PJI. Level of Evidence: Therapeutic Level II. Cite this article: Bone Jt Open 2020;1-12:737–742

Aims. 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). Methods. 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. Results. The mean values of absolute differences (postoperative CT-preoperative plan) were 1.7° (standard deviation (SD) 2.0) (inclination) and 2.5° (SD 2.1°) (anteversion) in DDH patients, and no significant differences were found between non-DDH and DDH patients. The mean absolute differences for 3D cup position were 1.1 mm (SD 1.0) (coronal plane) and 1.2 mm (SD 2.1) (axial plane) in DDH patients, and no significant differences were found between two groups. No significant difference was found either in cup alignment between postoperative CT and navigation record after cup screws or in the severity of DDH. Excellent restoration of leg length and combined offset were achieved in both groups. Conclusion. We demonstrated that robotic-assisted THA may achieve precise cup positioning in DDH patients, and may be useful in those with severe DDH. Cite this article: Bone Joint Res 2021;10(10):629–638

Aims. Intraoperative 3D navigation (ION) allows high accuracy to be achieved in spinal surgery, but poor workflow has prevented its widespread uptake. The technical demands on ION when used in patients with adolescent idiopathic scoliosis (AIS) are higher than for other more established indications. Lean principles have been applied to industry and to health care with good effects. While ensuring optimal accuracy of instrumentation and safety, the implementation of ION and its associated productivity was evaluated in this study for AIS surgery in order to enhance the workflow of this technique. The aim was to optimize the use of ION by the application of lean principles in AIS surgery. Methods. A total of 20 consecutive patients with AIS were treated with ION corrective spinal surgery. Both qualitative and quantitative analysis was performed with real-time modifications. Operating time, scan time, dose length product (measure of CT radiation exposure), use of fluoroscopy, the influence of the reference frame, blood loss, and neuromonitoring were assessed. Results. The greatest gains in productivity were in avoiding repeat intraoperative scans (a mean of 248 minutes for patients who had two scans, and a mean 180 minutes for those who had a single scan). Optimizing accuracy was the biggest factor influencing this, which was reliant on incremental changes to the operating setup and technique. Conclusion. The application of lean principles to the introduction of ION for AIS surgery helps assimilate this method into the environment of the operating theatre. Data and stakeholder analysis identified a reproducible technique for using ION for AIS surgery, reducing operating time, and radiation exposure. Cite this article: Bone Joint J. 2020;102-B(1):5–10

Aims. The aim of this study was to establish a reliable method for producing 3D reconstruction of sonographic callus. Methods. A cohort of ten closed tibial shaft fractures managed with intramedullary nailing underwent ultrasound scanning at two, six, and 12 weeks post-surgery. Ultrasound capture was performed using infrared tracking technology to map each image to a 3D lattice. Using echo intensity, semi-automated mapping was performed to produce an anatomical 3D representation of the fracture site. Two reviewers independently performed 3D reconstructions and kappa coefficient was used to determine agreement. A further validation study was undertaken with ten reviewers to estimate the clinical application of this imaging technique using the intraclass correlation coefficient (ICC). Results. Nine of the ten patients achieved union at six months. At six weeks, seven patients had bridging callus of ≥ one cortex on the 3D reconstruction and when present all achieved union. Compared to six-week radiographs, no bridging callus was present in any patient. Of the three patients lacking sonographic bridging callus, one went onto a nonunion (77.8% sensitive and 100% specific to predict union). At 12 weeks, nine patients had bridging callus at ≥ one cortex on 3D reconstruction (100%-sensitive and 100%-specific to predict union). Presence of sonographic bridging callus on 3D reconstruction demonstrated excellent reviewer agreement on ICC at 0.87 (95% confidence interval 0.74 to 0.96). Conclusion. 3D fracture reconstruction can be created using multiple ultrasound images in order to evaluate the presence of bridging callus. This imaging modality has the potential to enhance the usability and accuracy of identification of early fracture healing. Cite this article: Bone Joint Res 2021;10(12):759–766

Aims. This study aimed to explore whether serum combined with synovial interleukin-6 (IL-6) measurement can improve the accuracy of prosthetic joint infection (PJI) diagnosis, and to establish the cut-off values of IL-6 in serum and synovial fluid in detecting chronic PJI. Methods. Patients scheduled to have a revision surgery for indications of chronic infection of knee and hip arthroplasties or aseptic loosening of an implant were prospectively screened before being enrolled into this study. The Musculoskeletal Infection Society (MSIS) definition of PJI was used for the classification of cases as aseptic or infected. Serum CRP, ESR, IL-6, and percentage of polymorphonuclear neutrophils (PMN%) and IL-6 in synovial fluid were analyzed. Statistical tests were performed to compare these biomarkers in the two groups, and receiver operating characteristic (ROC) curves and area under the curve (AUC) were analyzed for each biomarker. Results. A total of 93 patients were enrolled. There was no difference in demographic data between both groups. Synovial fluid IL-6, with a threshold of 1,855.36 pg/ml, demonstrated a mean sensitivity of 94.59% (95% confidence interval (CI) 81.8% to 99.3%) and a mean specificity of 92.86% (95% CI 82.7 to 98.0) for detecting chronic PJI. Then 6.7 pg/ml was determined to be the optimal threshold value of serum IL-6 for the diagnosis of chronic PJI, with a mean sensitivity of 97.30% (95% CI 85.8% to 99.9%) and a mean specificity of 76.79% (95% CI 63.6% to 87.0%). The combination of synovial IL-6 and serum IL-6 led to improved accuracy of 96.77% in diagnosing chronic PJI. Conclusion. The present study identified that a combination of IL-6 in serum and synovial IL-6 has the potential for further improvement of the diagnosis of PJI. Cite this article: Bone Joint Res 2020;9(9):587–592

Aims. The aim of this study was to further evaluate the accuracy of ten promising synovial biomarkers (bactericidal/permeability-increasing protein (BPI), lactoferrin (LTF), neutrophil gelatinase-associated lipocalin (NGAL), neutrophil elastase 2 (ELA-2), α-defensin, cathelicidin LL-37 (LL-37), human β-defensin (HBD-2), human β-defensin 3 (HBD-3), D-dimer, and procalcitonin (PCT)) for the diagnosis of periprosthetic joint infection (PJI), and to investigate whether inflammatory joint disease (IJD) activity affects their concentration in synovial fluid. Methods. We included 50 synovial fluid samples from patients with (n = 25) and without (n = 25) confirmed PJI from an institutional tissue bank collected between May 2015 and December 2016. We also included 22 synovial fluid samples aspirated from patients with active IJD presenting to Department of Rheumatology, the first Medical Centre, Chinese PLA General Hospital. Concentrations of the ten candidate biomarkers were measured in the synovial fluid samples using standard enzyme-linked immunosorbent assays (ELISA). The diagnostic accuracy was evaluated by receiver operating characteristic (ROC) curves. Results. BPI, LTF, NGAL, ELA-2, and α-defensin were well-performing biomarkers for detecting PJI, with areas under the curve (AUCs) of 1.000 (95% confidence interval, 1.000 to 1.000), 1.000 (1.000 to 1.000), 1.000 (1.000 to 1.000), 1.000 (1.000 to 1.000), and 0.998 (0.994 to 1.000), respectively. The other markers (LL-37, HBD-2, D-dimer, PCT, and HBD-3) had limited diagnostic value. For the five well-performing biomarkers, elevated concentrations were observed in patients with active IJD. The original best thresholds determined by the Youden index, which discriminated PJI cases from non-PJI cases could not discriminate PJI cases from active IJD cases, while elevated thresholds resulted in good performance. Conclusion. BPI, LTF, NGAL, ELA-2, and α-defensin demonstrated excellent performance for diagnosing PJI. However, all five markers showed elevated concentrations in patients with IJD activity. For patients with IJD, elevated thresholds should be considered to accurately diagnose PJI. Cite this article: Bone Joint J 2021;103-B(1):32–38

In recent years, machine learning (ML) and artificial neural networks (ANNs), a particular subset of ML, have been adopted by various areas of healthcare. A number of diagnostic and prognostic algorithms have been designed and implemented across a range of orthopaedic sub-specialties to date, with many positive results. However, the methodology of many of these studies is flawed, and few compare the use of ML with the current approach in clinical practice. Spinal surgery has advanced rapidly over the past three decades, particularly in the areas of implant technology, advanced surgical techniques, biologics, and enhanced recovery protocols. It is therefore regarded an innovative field. Inevitably, spinal surgeons will wish to incorporate ML into their practice should models prove effective in diagnostic or prognostic terms. The purpose of this article is to review published studies that describe the application of neural networks to spinal surgery and which actively compare ANN models to contemporary clinical standards allowing evaluation of their efficacy, accuracy, and relatability. It also explores some of the limitations of the technology, which act to constrain the widespread adoption of neural networks for diagnostic and prognostic use in spinal care. Finally, it describes the necessary considerations should institutions wish to incorporate ANNs into their practices. In doing so, the aim of this review is to provide a practical approach for spinal surgeons to understand the relevant aspects of neural networks. Cite this article: Bone Joint J 2021;103-B(9):1442–1448

Aims. An algorithm to determine the constitutional alignment of the lower limb once arthritic deformity has occurred would be of value when undertaking kinematically aligned total knee arthroplasty (TKA). The purpose of this study was to determine if the arithmetic hip-knee-ankle angle (aHKA) algorithm could estimate the constitutional alignment of the lower limb following development of significant arthritis. Methods. A matched-pairs radiological study was undertaken comparing the aHKA of an osteoarthritic knee (aHKA-OA) with the mechanical HKA of the contralateral normal knee (mHKA-N). Patients with Grade 3 or 4 Kellgren-Lawrence tibiofemoral osteoarthritis in an arthritic knee undergoing TKA and Grade 0 or 1 osteoarthritis in the contralateral normal knee were included. The aHKA algorithm subtracts the lateral distal femoral angle (LDFA) from the medial proximal tibial angle (MPTA) measured on standing long leg radiographs. The primary outcome was the mean of the paired differences in the aHKA-OA and mHKA-N. Secondary outcomes included comparison of sex-based differences and capacity of the aHKA to determine the constitutional alignment based on degree of deformity. Results. A total of 51 radiographs met the inclusion criteria. There was no significant difference between aHKA-OA and mHKA-N, with a mean angular difference of −0.4° (95% SE −0.8° to 0.1°; p = 0.16). There was no significant sex-based difference when comparing aHKA-OA and mHKA-N (mean difference 0.8°; p = 0.11). Knees with deformities of more than 8° had a greater mean difference between aHKA-OA and mHKA-N (1.3°) than those with lesser deformities (-0.1°; p = 0.009). Conclusion. This study supports the arithmetic HKA algorithm for prediction of the constitutional alignment once arthritis has developed. The algorithm has similar accuracy between sexes and greater accuracy with lesser degrees of deformity. Cite this article: Bone Joint Open 2020;1-7:339–345

Aims. The aim of this study was to investigate whether intraoperative 3D fluoroscopic imaging outperforms dorsal tangential views in the detection of dorsal cortex screw penetration after volar plating of an intra-articular distal radial fracture, as identified on postoperative CT imaging. Methods. A total of 165 prospectively enrolled patients who underwent volar plating for an intra-articular distal radial fracture were retrospectively evaluated to study three intraoperative imaging protocols: 1) standard 2D fluoroscopic imaging with anteroposterior (AP) and elevated lateral images (n = 55); 2) 2D fluoroscopic imaging with AP, lateral, and dorsal tangential views images (n = 50); and 3) 3D fluoroscopy (n = 60). Multiplanar reconstructions of postoperative CT scans served as the reference standard. Results. In order to detect dorsal screw penetration, the sensitivity of dorsal tangential views was 39% with a negative predictive value (NPV) of 91% and an accuracy of 91%; compared with a sensitivity of 25% for 3D fluoroscopy with a NPV of 93% and an accuracy of 93%. On the postoperative CT scans, we found penetrating screws in: 1) 40% of patients in the 2D fluoroscopy group; 2) in 32% of those in the 2D fluoroscopy group with AP, lateral, and dorsal tangential views; and 3) in 25% of patients in the 3D fluoroscopy group. In all three groups, the second compartment was prone to penetration, while the postoperative incidence decreased when more advanced imaging was used. There were no penetrating screws in the third compartment (extensor pollicis longus groove) in the 3D fluoroscopy groups, and one in the dorsal tangential views group. Conclusion. Advanced intraoperative imaging helps to identify screws which have penetrated the dorsal compartments of the wrist. However, based on diagnostic performance characteristics, one cannot conclude that 3D fluoroscopy outperforms dorsal tangential views when used for this purpose. Dorsal tangential views are sufficiently accurate to detect dorsal screw penetration, and arguably more efficacious than 3D fluoroscopy. Cite this article: Bone Joint J 2020;102-B(7):874–880

Objectives. The primary objective of this study was to compare accuracy in restoring the native centre of hip rotation in patients undergoing conventional manual total hip arthroplasty (THA) versus robotic-arm assisted THA. Secondary objectives were to determine differences between these treatment techniques for THA in achieving the planned combined offset, component inclination, component version, and leg-length correction. Materials and Methods. This prospective cohort study included 50 patients undergoing conventional manual THA and 25 patients receiving robotic-arm assisted THA. Patients undergoing conventional manual THA and robotic-arm assisted THA were well matched for age (mean age, 69.4 years (. sd. 5.2) vs 67.5 years (. sd. 5.8) (p = 0.25); body mass index (27.4 kg/m. 2. (. sd. 2.1) vs 26.9 kg/m. 2. (. sd. 2.2); p = 0.39); and laterality of surgery (right = 28, left = 22 vs right = 12, left = 13; p = 0.78). All operative procedures were undertaken by a single surgeon using the posterior approach. Two independent blinded observers recorded all radiological outcomes of interest using plain radiographs. Results. The correlation coefficient was 0.92 (95% confidence interval (CI) 0.88 to 0.95) for intraobserver agreement and 0.88 (95% CI 0.82 to 0.94) for interobserver agreement in all study outcomes. Robotic THA was associated with improved accuracy in restoring the native horizontal (p < 0.001) and vertical (p < 0.001) centres of rotation, and improved preservation of the patient’s native combined offset (p < 0.001) compared with conventional THA. Robotic THA improved accuracy in positioning of the acetabular component within the combined safe zones of inclination and anteversion described by Lewinnek et al (p = 0.02) and Callanan et al (p = 0.01) compared with conventional THA. There was no difference between the two treatment groups in achieving the planned leg-length correction (p = 0.10). Conclusion. Robotic-arm assisted THA was associated with improved accuracy in restoring the native centre of rotation, better preservation of the combined offset, and more precise acetabular component positioning within the safe zones of inclination and anteversion compared with conventional manual THA

Aims. The purpose of this investigation was to determine the relationship between height, weight, and sex with implant size in total knee arthroplasty (TKA) using a multivariate linear regression model and a Bayesian model. Methods. A retrospective review of an institutional registry was performed of primary TKAs performed between January 2005 and December 2016. Patient demographics including patient age, sex, height, weight, and body mass index (BMI) were obtained from registry and medical record review. In total, 8,100 primary TKAs were included. The mean age was 67.3 years (SD 9.5) with a mean BMI of 30.4 kg/m. 2. (SD 6.3). The TKAs were randomly split into a training cohort (n = 4,022) and a testing cohort (n = 4,078). A multivariate linear regression model was created on the training cohort and then applied to the testing cohort . A Bayesian model was created based on the frequencies of implant sizes in the training cohort. The model was then applied to the testing cohort to determine the accuracy of the model at 1%, 5%, and 10% tolerance of inaccuracy. Results. Height had a relatively strong correlation with implant size (femoral component anteroposterior (AP) Pearson correlation coefficient (ρ) = 0.73, p < 0.001; tibial component mediolateral (ML) ρ = 0.77, p < 0.001). Weight had a moderately strong correlation with implant size, (femoral component AP ρ = 0.46, p < 0.001; tibial ML ρ = 0.48, p < 0.001). There was a significant linear correlation with height, weight, and sex with implant size (femoral component R. 2. = 0.607, p < 0.001; tibial R. 2. = 0.695, p < 0.001). The Bayesian model showed high accuracy in predicting the range of required implant sizes (94.4% for the femur and 96.6% for the tibia) accepting a 5% risk of inaccuracy. Conclusion. Implant size was correlated with basic demographic variables including height, weight, and sex. The linear regression and Bayesian models accurately predicted required implant sizes across multiple manufacturers based on height, weight, and sex alone. These types of predictive models may help improve operating room and implant supply chain efficiency. Level of Evidence: Level IV. Cite this article: Bone Joint J 2020;102-B(6 Supple A):85–90

Aims. The aim of the Scaphoid Magnetic Resonance Imaging in Trauma (SMaRT) trial was to evaluate the clinical and cost implications of using immediate MRI in the acute management of patients with a suspected fracture of the scaphoid with negative radiographs. Patients and Methods. Patients who presented to the emergency department (ED) with a suspected fracture of the scaphoid and negative radiographs were randomized to a control group, who did not undergo further imaging in the ED, or an intervention group, who had an MRI of the wrist as an additional test during the initial ED attendance. Most participants were male (52% control, 61% intervention), with a mean age of 36.2 years (18 to 73) in the control group and 38.2 years (20 to 71) in the intervention group. The primary outcome was total cost impact at three months post-recruitment. Secondary outcomes included total costs at six months, the assessment of clinical findings, diagnostic accuracy, and the participants’ self-reported level of satisfaction. Differences in cost were estimated using generalized linear models with gamma errors. Results. The mean cost up to three months post-recruitment per participant was £542.40 (. sd. £855.20, n = 65) for the control group and £368.40 (. sd. £338.60, n = 67) for the intervention group, leading to an estimated cost difference of £174 (95% confidence interval (CI) -£30 to £378; p = 0.094). The cost difference per participant increased to £266 (95% CI £3.30 to £528; p = 0.047) at six months. Overall, 6.2% of participants (4/65, control group) and 10.4% of participants (7/67, intervention group) had sustained a fracture of the scaphoid (p = 0.37). In addition, 7.7% of participants (5/65, control group) and 22.4% of participants (15/67, intervention group) had other fractures diagnosed (p = 0.019). The use of MRI was associated with higher diagnostic accuracy both in the diagnosis of a fracture of the scaphoid (100.0% vs 93.8%) and of any other fracture (98.5% vs 84.6%). Conclusion. The use of immediate MRI in the management of participants with a suspected fracture of the scaphoid and negative radiographs led to cost savings while improving the pathway’s diagnostic accuracy and patient satisfaction. Cite this article: Bone Joint J 2019;101-B:984–994

Aims. This pilot study tested the performance of a rapid assay for diagnosing prosthetic joint infection (PJI), which measures synovial fluid calprotectin from total hip and knee revision patients. Methods. A convenience series of 69 synovial fluid samples from revision patients at the Norfolk and Norwich University Hospital were collected intraoperatively (52 hips, 17 knees) and frozen. Synovial fluid calprotectin was measured retrospectively using a new commercially available lateral flow assay for PJI diagnosis (Lyfstone AS) and compared to International Consensus Meeting (ICM) 2018 criteria and clinical case review (ICM-CR) gold standards. Results. According to ICM, 24 patients were defined as PJI positive and the remaining 45 were negative. The overall accuracy of the lateral flow test compared to ICM was 75.36% (52/69, 95% CI 63.51% to 84.95%), sensitivity and specificity were 75.00% (18/24, 95% CI 53.29% to 90.23%) and 75.56% (34/45, 95% CI 60.46% to 87.12%), respectively, positive predictive value (PPV) was 62.07% (18/29, 95% CI 48.23% to 74.19%) and negative predictive value (NPV) was 85.00% (34/40, 95% CI 73.54% to 92.04%), and area under the receiver operating characteristic (ROC) curve (AUC) was 0.78 (95% CI 0.66 to 0.87). Patient data from discordant cases were reviewed by the clinical team to develop the ICM-CR gold standard. The lateral flow test performance improved significantly when compared to ICM-CR, with accuracy increasing to 82.61% (57/69, 95% CI 71.59% to 90.68%), sensitivity increasing to 94.74% (18/19, 95% CI 73.97% to 99.87%), NPV increasing to 97.50% (39/40, 95% CI 85.20% to 99.62%), and AUC increasing to 0.91 (95% CI 0.81 to 0.96). Test performance was better in knees (100.00% accurate (17/17, 95% CI 80.49% to 100.00%)) compared to hips (76.92% accurate (40/52, 95% CI 63.16% to 87.47%)). Conclusion. This study demonstrates that the calprotectin lateral flow assay could be an effective diagnostic test for PJI, however additional prospective studies testing fresh samples are required. Cite this article:Bone Joint Res. 2020;9(5):202–210

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 robotic experience did not affect accuracy of implant positioning (p = 0.52), posterior condylar offset ratio (p = 0.71), posterior tibial slope (p = 0.68), native joint line preservation (p = 0.55), and postoperative limb alignment (p = 0.65). Robotic-arm assisted UKA improved accuracy of femoral (p < 0.001) and tibial (p < 0.001) implant positioning with no additional risk of postoperative complications compared to conventional jig-based UKA. Conclusion. Robotic-arm assisted UKA was associated with a learning curve of six cases for operating time and surgical team confidence levels but no learning curve for accuracy of implant positioning. Cite this article: Bone Joint J 2018;100-B:1033–42

Aims. Traditionally, acetabular component insertion during total hip arthroplasty (THA) is visually assisted in the posterior approach and fluoroscopically assisted in the anterior approach. The present study examined the accuracy of a new surgeon during anterior (NSA) and posterior (NSP) THA using robotic arm-assisted technology compared to two experienced surgeons using traditional methods. Methods. Prospectively collected data was reviewed for 120 patients at two institutions. Data were collected on the first 30 anterior approach and the first 30 posterior approach surgeries performed by a newly graduated arthroplasty surgeon (all using robotic arm-assisted technology) and was compared to standard THA by an experienced anterior (SSA) and posterior surgeon (SSP). Acetabular component inclination, version, and leg length were calculated postoperatively and differences calculated based on postoperative film measurement. Results. Demographic data were similar between groups with the exception of BMI being lower in the NSA group (27.98 vs 25.2; p = 0.005). Operating time and total time in operating room (TTOR) was lower in the SSA (p < 0.001) and TTOR was higher in the NSP group (p = 0.014). Planned versus postoperative leg length discrepancy were similar among both anterior and posterior surgeries (p > 0.104). Planned versus postoperative abduction and anteversion were similar among the NSA and SSA (p > 0.425), whereas planned versus postoperative abduction and anteversion were lower in the NSP (p < 0.001). Outliers > 10 mm from planned leg length were present in one case of the SSP and NSP, with none in the anterior groups. There were no outliers > 10° in anterior or posterior for abduction in all surgeons. The SSP had six outliers > 10° in anteversion while the NSP had none (p = 0.004); the SSA had no outliers for anteversion while the NSA had one (p = 0.500). Conclusion. Robotic arm-assisted technology allowed a newly trained surgeon to produce similarly accurate results and outcomes as experienced surgeons in anterior and posterior hip arthroplasty. Cite this article: Bone Jt Open 2021;2(6):365–370

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 robots and navigation systems. Cite this article: Bone Joint J 2021;103-B(6 Supple A):81–86