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The Peri-Implant and PeriProsthetic Survival AnalysiS (PIPPAS) study aimed to investigate the risk factors for one-year mortality of femoral peri-implant fractures (FPIFs).

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Around the world, the emergence of robotic technology has improved surgical precision and accuracy in total knee arthroplasty (TKA). This territory-wide study compares the results of various robotic TKA (R-TKA) systems with those of conventional TKA (C-TKA) and computer-navigated TKA (N-TKA).

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The aims of this study were to develop an automatic system capable of calculating four radiological measurements used in the diagnosis and monitoring of cerebral palsy (CP)-related hip disease, and to demonstrate that these measurements are sufficiently accurate to be used in clinical practice.

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Prolonged waits for hip and knee arthroplasty have raised questions about the equity of current approaches to waiting list prioritization for those awaiting surgery. We therefore set out to understand key stakeholder (patient and surgeon) preferences for the prioritization of patients awaiting such surgery, in order to guide future waiting list redesign.

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The Clavien-Dindo (CD) classification and Comprehensive Complication Index (CCI) have been validated primarily among general surgical procedures. To date, the validity of these measures has not been assessed in patients undergoing arthroplasty.

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There is compelling evidence for the use of cemented hip hemiarthroplasty for displaced intracapsular hip fractures; however, the risks of cement are well reported and in rare cases may be associated with haemodynamic collapse. It is therefore important to improve our understanding of haemodynamic instability, intraoperative monitoring, and strategies to reduce the risk to patients.

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Excellent outcomes have been reported following CT-based robotic arm-assisted total hip arthroplasty (rTHA) compared with manual THA; however, its superiority over CT-based navigation THA (nTHA) remains unclear. This study aimed to determine whether a CT-based robotic arm-assisted system helps surgeons perform accurate cup placement, minimizes leg length, and offsets discrepancies more than a CT-based navigation system.

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We evaluated the national and regional trends from 2013 to 2022, in the prevalence of Perthes’ disease among adolescent males in South Korea.

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Limb salvage surgery (LSS) is the primary treatment option for primary bone malignancy. It involves the removal of bone and tissue, followed by reconstruction with endoprosthetic replacements (EPRs) to prevent amputation. Trabecular metal (TM) collars have been developed to encourage bone ingrowth (osseointegration (OI)) into EPRs. The primary aim of this study was to assess whether OI occurs when TM collars are used in EPRs for tumour.

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Better prediction of outcome after total hip arthroplasty (THA) is warranted. Systemic inflammation and central neuroinflammation are possibly involved in progression of osteoarthritis and pain. We explored whether inflammatory biomarkers in blood and cerebrospinal fluid (CSF) were associated with clinical outcome, and baseline pain or disability, 12 months after THA.

Aims. The transepicondylar axis is a well-established reference for the determination of femoral component rotation in total knee arthroplasty (TKA). However, when severe bone loss is present in the femoral condyles, rotational alignment can be more complicated. There is a lack of validated landmarks in the supracondylar region of the distal femur. Therefore, the aim of this study was to analyze the correlation between the surgical transepicondylar axis (sTEA) and the suggested dorsal cortex line (DCL) in the coronal plane and the inter- and intraobserver reliability of its CT scan measurement. Methods. A total of 75 randomly selected CT scans were measured by three experienced surgeons independently. The DCL was defined in the coronal plane as a tangent to the dorsal femoral cortex located 75 mm above the joint line in the frontal plane. The difference between sTEA and DCL was calculated. Descriptive statistics and angulation correlations were generated for the sTEA and DCL, as well as for the distribution of measurement error for intra- and inter-rater reliability. Results. The external rotation of the DCL to the sTEA was a mean of 9.47° (SD 3.06°), and a median of 9.2° (IQR 7.45° to 11.60°), with a minimum value of 1.7° and maximum of 16.3°. The measurements of the DCL demonstrated very good to excellent test-retest and inter-rater reliability coefficients (intraclass correlation coefficient 0.80 to 0.99). Conclusion. This study reveals a correlation between the sTEA and the DCL. Overall, 10° of external rotation of the dorsal femoral cortical bone to the sTEA may serve as a reliable landmark for initial position of the femoral component. Surgeons should be aware that there are outliers in this study in up to 17% of the measurements, which potentially could result in deviations of femoral component rotation. Cite this article: Bone Jt Open 2024;5(12):1067–1071

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The aim of the LightFix Trial was to evaluate the clinical outcomes for one year after the treatment of impending and completed pathological fractures of the humerus using the IlluminOss System (IS), and to analyze the performance of this device.

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Surgeon and patient reluctance to participate are potential significant barriers to conducting placebo-controlled trials of orthopaedic surgery. Understanding the preferences of orthopaedic surgeons and patients regarding the design of randomized placebo-controlled trials (RCT-Ps) of knee procedures can help to identify what RCT-P features will lead to the greatest participation. This information could inform future trial designs and feasibility assessments.

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For displaced femoral neck fractures (FNFs) in geriatric patients, there remains uncertainty regarding the effect of total hip arthroplasty (THA) compared with hemiarthroplasty (HA) in the guidelines. We aimed to compare 90-day surgical readmission, in-hospital complications, and charges between THA and HA in these patients.

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Highly cross-linked polyethylene (HXLPE) greatly reduces wear in total hip arthroplasty, compared to conventional polyethylene (CPE). Cross-linking is commonly achieved by irradiation. This study aimed to compare the degree of cross-linking and in vitro wear rates across a cohort of retrieved and unused polyethylene cups/liners from various brands.

Introduction. The current methods for measuring femoral torsion have limitations, including variability and inaccuracies. Existing 3D methods are not reliable for abnormal femoral anteversion measurement. A new 3D method is needed for accurate measurement and planning of proximal femoral osteotomies. Currently available software for viewing and modelling CT data lacks measurement capabilities. The MSK Hip planner aims to address these limitations by combining measurement, planning, and analysis functionalities into one tool. We aim to answer 5 key questions: Is there a difference between 2D measurement methods? Is there a difference between 3D measurement methods? Is there a difference between 2D and 3D measurement methods? Are any of the measurement methods affected by the presence of osteoarthritis or a CAM deformity?. Method. After segmentation was carried out on 42 femoral CT scans using Osirix, 3D bone models were landmarked in the MSK lab hip planning software. Murphy's, Reikeras’, McBryde, and the novel MSK lab method were used to measure femoral anteversion. Result. Murphy's method had the lowest mean femoral neck anteversion (FNA) at 24.98°, while the MSK method had the highest at 28.55°. Bland-Altman plots showed systematic errors between 2D (1.201°) and 3D (1.074°) methods. All methods demonstrated good intra- and inter-user reliability. Significant differences were found between measurement methods and between patient groups. Conclusion. The MSK Hip Planner software proved useful and convenient to measure FNA. Statistically significant differences in FNA were observed between the measurement methods, as well as between patient groups when split by presence of osteoarthritis and cam deformity. Complex joint pathology and altered femoral morphology should be considered by clinicians when deciding which method to use when measuring FNA

Introduction. This study aimed to evaluate the effectiveness of a novel intraoperative navigation platform for total knee arthroplasty (TKA) in restoring native knee joint kinematics and strains in the medial collateral ligament (MCL) and lateral collateral ligament (LCL) during squatting motions. Method. Six cadaver lower limbs underwent computed tomography scans to design patient-specific guides. Using these scans, bony landmarks and virtual single-line collateral ligaments were identified to provide intraoperative real-time feedback, aided in bone resection, implant alignment, tibiofemoral kinematics, and collateral ligament elongations, using the navigation platform. The specimens were subjected to squatting (35°-100°) motions on a physiological ex vivo knee simulator, maintaining a constant 110N vertical ankle load regulated by active quadriceps and bilateral hamstring actuators. Subsequently, each knee underwent a medially-stabilized TKA using the mechanical alignment technique, followed by a retest under the same conditions used preoperatively. Using a dedicated wand, MCL and LCL insertions—anterior, middle, and posterior bundles—were identified in relation to bone-pin markers. The knee kinematics and collateral ligament strains were analyzed from 3D marker trajectories captured by a six-camera optical system. Result. Both native and TKA conditions demonstrated similar patterns in tibial valgus orientation (Root Mean Square Error (RMSE=1.7°), patellar flexion (RMSE=1.2°), abduction (RMSE=0.5°), and rotation (RMSE=0.4°) during squatting (p>0.13). However, a significant difference was found in tibial internal rotation between 35° and 61° (p<0.045, RMSE=3.3°). MCL strains in anterior (RMSE=1.5%), middle (RMSE=0.8%), and posterior (RMSE=0.8%) bundles closely matched in both conditions, showing no statistical differences (p>0.05). Conversely, LCL strain across all bundles (RMSE<4.6%) exhibited significant differences from mid to deep flexion (p<0.048). Conclusion. The novel intraoperative navigation platform not only aims to achieve planned knee alignment but also assists in restoring native knee kinematics and collateral ligament behavior through real-time feedback. Acknowledgment. This study was funded by Medacta International (Castel San Pietro, Switzerland)

Introduction. Accurate assessment of alignment in pre-operative and post-operative knee radiographs is important for planning and evaluating knee replacement surgery. Existing methods predominantly rely on manual measurements using long-leg radiographs, which are time-consuming to perform and are prone to reliability errors. In this study, we propose a machine-learning-based approach to automatically measure anatomical varus/valgus alignment in pre-operative and post-operative standard AP knee radiographs. Method. We collected a training dataset of 816 pre-operative and 457 one-year post-operative AP knee radiographs of patients who underwent knee replacement surgery. Further, we have collected a separate distinct test dataset with both pre-operative and one-year post-operative radiographs for 376 patients. We manually outlined the distal femur and the proximal tibia/fibula with points to capture the knee joint (including implants in the post-operative images). This included point positions used to permit calculation of the anatomical tibiofemoral angle. We defined varus/valgus as negative/positive deviations from zero. Ground truth measurements were obtained from the manually placed points. We used the training dataset to develop a machine-learning-based automatic system to locate the point positions and derive the automatic measurements. Agreement between the automatic and manual measurements for the test dataset was assessed by intra-class correlation coefficient (ICC), mean absolute difference (MAD) and Bland-Altman analysis. Result. Analysing the agreement between the manual and automated measurements, ICC values were excellent pre-/post-operatively (0.96, CI: 0.94-0.96) / (0.95, CI: 0.95-0.96). Pre-/post-operative MAD values were 1.3°±1.4°SD / 0.7°±0.6°SD. The Bland-Altman analysis showed a pre-/post-operative mean difference (bias) of 0.3°±1.9°SD/-0.02°±0.9°SD, with pre-/post-operative 95% limits of agreement of ±3.7°/±1.8°, respectively. Conclusion. The developed machine-learning-based system demonstrates high accuracy and reliability in automatically measuring anatomical varus/valgus alignment in pre-operative and post-operative knee radiographs. It provides a promising approach for automating the measurement of anatomical alignment without the need for long-leg radiographs. Acknowledgements. This research was funded by the Wellcome Trust [223267/Z/21/Z]

Introduction. Three-dimensional (3D) morphological understanding of the hip joint, specifically the joint space and surrounding anatomy, including the proximal femur and the pelvis bone, is crucial for a range of orthopedic diagnoses and surgical planning. While deep learning algorithms can provide higher accuracy for segmenting bony structures, delineating hip joint space formed by cartilage layers is often left for subjective manual evaluation. This study compared the performance of two state-of-the-art 3D deep learning architectures (3D UNET and 3D UNETR) for automated segmentation of proximal femur bone, pelvis bone, and hip joint space with single and multi-class label segmentation strategies. Method. A dataset of 56 3D CT images covering the hip joint was used for the study. Two bones and hip joint space were manually segmented for training and evaluation. Deep learning models were trained and evaluated for a single-class approach for each label (proximal femur, pelvis, and the joint space) separately, and for a multi-class approach to segment all three labels simultaneously. A consistent training configuration of hyperparameters was used across all models by implementing the AdamW optimizer and Dice Loss as the primary loss function. Dice score, Root Mean Squared Error, and Mean Absolute Error were utilized as evaluation metrics. Results. Both the models performed at excellent levels for single-label segmentations in bones (dice > 0.95), but single-label joint space performance remained considerably lower (dice < 0.87). Multi-class segmentations remained at lower performance (dice < 0.88) for both models. Combining bone and joint space labels may have introduced a class imbalance problem in multi-class models, leading to lower performance. Conclusion. It is not clear if 3D UNETR provides better performance as the selection of hyperparameters was the same across the models and was not optimized. Further evaluations will be needed with baseline UNET and nnUNET modeling architectures