Introduction. Vertebral compression fractures are the most common type of osteoporotic fracture. Though 89% of clinical fractures occur anteriorly, it is challenging to replicate these ex vivo with the underlying intervertebral discs (IVDs) present. Furthermore, the role of disc degeneration in this mechanism is poorly understood. Understanding how disc morphology alters vertebral strain distributions may lead to the utilisation of IVD metrics in fracture prediction, or inform surgical decision-making regarding instrumentation type and placement. Aim. To determine the effect of disc degeneration on the vertebral trabecular bone strain distributions in axial compression and flexion loading. Methods. Eight cadaveric thoracolumbar segments (T11-L3) were prepared (N=4 axial compression, N=4 flexion). µCT-based digital volume correlation was used to quantify trabecular strains. A bespoke loading device fixed specimens at the resultant displacement when loaded to 50N and 800N. Flexion was achieved by adding 6° wedges. Disc degeneration was quantified with Pfirrmann grading and T2 relaxation times. Results. Anterior axial strains were 80.9±39% higher than the posterior region in flexion (p<0.01), the ratio of which was correlated with T2 relaxation time (R. 2. =0.80, p<0.05). In flexion, the central-to-peripheral axial strain ratio in the endplate region was significantly higher when the underlying IVDs were non-degenerated relative to degenerated (+38.1±12%, p<0.05). No significant differences were observed in axial compression. Conclusion. Disc degeneration is a stronger determinant of the trabecular strain distribution when flexion is applied. Load transfer through non-degenerate IVDs under flexion appears to be more centralised, suggesting that disc degeneration predisposes flexion-type compression fractures by shifting high strains anteriorly. Conflicts of interest. The authors declare none. Sources of funding. This work was funded by the Engineering & Physical Sciences Research Council (EP/V029452/1), and Back-to-Back

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The COVID-19 pandemic has disrupted the provision of arthroplasty services in England, Wales, and Northern Ireland. This study aimed to quantify the backlog, analyze national trends, and predict time to recovery.

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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.

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The metabolic variations between the cartilage of osteoarthritis (OA) and Kashin-Beck disease (KBD) remain largely unknown. Our study aimed to address this by conducting a comparative analysis of the metabolic profiles present in the cartilage of KBD and OA.

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Cemented hemiarthroplasty is an effective form of treatment for most patients with an intracapsular fracture of the hip. However, it remains unclear whether there are subgroups of patients who may benefit from the alternative operation of a modern uncemented hemiarthroplasty – the aim of this study was to investigate this issue. Knowledge about the heterogeneity of treatment effects is important for surgeons in order to target operations towards specific subgroups who would benefit the most.

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There is a lack of high-quality research investigating outcomes of Ponseti-treated idiopathic clubfeet and correlation with relapse. This study assessed clinical and quality of life (QoL) outcomes using a standardized core outcome set (COS), comparing children with and without relapse.

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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.

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In this study, we aimed to visualize the spatial distribution characteristics of femoral head necrosis using a novel measurement method.

The June 2024 Wrist & Hand Roundup³⁶⁰ looks at: One-year outcomes of the anatomical front and back reconstruction for scapholunate dissociation; Limited intercarpal fusion versus proximal row carpectomy in the treatment of SLAC or SNAC wrist: results after 3.5 years; Prognostic factors for clinical outcomes after arthroscopic treatment of traumatic central tears of the triangular fibrocartilage complex; The rate of nonunion in the MRI-detected occult scaphoid fracture: a multicentre cohort study; Does correction of carpal malalignment influence the union rate of scaphoid nonunion surgery?; Provision of a home-based video-assisted therapy programme in thumb carpometacarpal arthroplasty; Is replantation associated with better hand function after traumatic hand amputation than after revision amputation?; Diagnostic performance of artificial intelligence for detection of scaphoid and distal radius fractures: a systematic review.

The June 2024 Hip & Pelvis Roundup³⁶⁰ looks at: Machine learning did not outperform conventional competing risk modelling to predict revision arthroplasty; Unravelling the risks: incidence and reoperation rates for femoral fractures post-total hip arthroplasty; Spinal versus general anaesthesia for hip arthroscopy: a COVID-19 pandemic- and opioid epidemic-driven study; Development and validation of a deep-learning model to predict total hip arthroplasty on radiographs; Ambulatory centres lead in same-day hip and knee arthroplasty success; Exploring the impact of smokeless tobacco on total hip arthroplasty outcomes: a deeper dive into postoperative complications.

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To investigate the impact of consecutive perioperative care transitions on in-hospital recovery of patients who had primary total knee arthroplasty (TKA) over an 11-year period.

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The Birmingham Hip Resurfacing (BHR) was introduced in 1997 to address the needs of young active patients using a historically proven large-diameter metal-on-metal (MoM) bearing. A single designer surgeon’s consecutive series of 130 patients (144 hips) was previously reported at five and ten years, reporting three and ten failures, respectively. The aim of this study was to extend the follow-up of this original cohort at 25 years.

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To assess the alterations in cell-specific DNA methylation associated with chondroitin sulphate response using peripheral blood collected from Kashin-Beck disease (KBD) patients before initiation of chondroitin sulphate treatment.

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The localization of necrotic areas has been reported to impact the prognosis and treatment strategy for osteonecrosis of the femoral head (ONFH). Anteroposterior localization of the necrotic area after a femoral neck fracture (FNF) has not been properly investigated. We hypothesize that the change of the weight loading direction on the femoral head due to residual posterior tilt caused by malunited FNF may affect the location of ONFH. We investigate the relationship between the posterior tilt angle (PTA) and anteroposterior localization of osteonecrosis using lateral hip radiographs.

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Micromotion of the polyethylene (PE) inlay may contribute to backside PE wear in addition to articulate wear of total knee arthroplasty (TKA). Using radiostereometric analysis (RSA) with tantalum beads in the PE inlay, we evaluated PE micromotion and its relationship to PE wear.

Ideally the hip arthroplasty should not be subject to bony or prosthetic impingement, in order to minimise complications and optimise outcomes. Modern 3d planning permits pre-operative simulation of the movements of the planned hip arthroplasty to check for such impingement. For this to be meaningful, however, it is necessary to know the range of movement (ROM) that should be simulated. Arbitrary “normal” values for hip ROM are of limited value in such simulations: it is well known that hip ROM is individualised for each patient. We have therefore developed a method to determine this individualised ROM using CT scans. CT scans were performed on 14 cadaveric hips, and the images were segmented to create 3d virtual models. Using Matlab software, each virtual hip was moved in all potential directions to the point of bony impingement, thus defining an individualised impingement-free 3d ROM envelope. This was then compared with the actual ROM as directly measured from each cadaver using a high-resolution motion capture system. For each hip, the ROM envelope free of bony impingement could be described from the CT and represented as a 3d shape. As expected, the directly measured ROM from the cadaver study for each hip was smaller than the CT-based prediction, owing to the presence of constraining soft tissues. However, for movements associated with hip dislocation (such as flexion with internal rotation), the cadaver measurements matched the CT prediction, to within 10°. It is possible to determine an individual's range of clinically important hip movements from a CT scan. This method could therefore be used to create truly personalised movement simulation as part of pre-operative 3d surgical planning

Arthroplasties are widely performed to improve mobility and quality of life for symptomatic knee/hip osteoarthritis patients. With increasing rates of Total Joint Replacements in the United Kingdom, predicting length of stay is vital for hospitals to control costs, manage resources, and prevent postoperative complications. A longer Length of stay has been shown to negatively affect the quality of care, outcomes and patient satisfaction. Thus, predicting LOS enables us to make full use of medical resources. Clinical characteristics were retrospectively collected from 1,303 patients who received TKA and THR. A total of 21 variables were included, to develop predictive models for LOS by multiple machine learning (ML) algorithms, including Random Forest Classifier (RFC), K-Nearest Neighbour (KNN), Extreme Gradient Boost (XgBoost), and Na¯ve Bayes (NB). These models were evaluated by the receiver operating characteristic (ROC) curve for predictive performance. A feature selection approach was used to identify optimal predictive factors. Based on the ROC of Training result, XgBoost algorithm was selected to be applied to the Test set. The areas under the ROC curve (AUCs) of the 4 models ranged from 0.730 to 0.966, where higher AUC values generally indicate better predictive performance. All the ML-based models performed better than conventional statistical methods in ROC curves. The XgBoost algorithm with 21 variables was identified as the best predictive model. The feature selection indicated the top six predictors: Age, Operation Duration, Primary Procedure, BMI, creatinine and Month of Surgery. By analysing clinical characteristics, it is feasible to develop ML-based models for the preoperative prediction of LOS for patients who received TKA and THR, and the XgBoost algorithm performed the best, in terms of accuracy of predictive performance. As this model was originally crafted at Ashford and St. Peters Hospital, we have naturally named it as THE ASHFORD OUTCOME

OpenPredictor, a machine learning-enabled clinical decision aid, has been developed to manage backlogs in elective surgeries. It aims to optimise the use of high volume, low complexity surgical pathways by accurately stratifying patient risk, thereby facilitating the allocation of patients to the most suitable surgical sites. The tool augments elective surgical pathways by providing automated secondary opinions for perioperative risk assessments, enhancing decision-making. Its primary application is in elective sites utilising lighter pre-assessment methods, identifying patients with minimal complication risks and those high-risk individuals who may benefit from early pre-assessment. The Phase 1 clinical evaluation of OpenPredictor entailed a prospective analysis of 156 patient records from elective hip and knee joint replacement surgeries. Using a polynomial logistic regression model, patients were categorised into high, moderate, and low-risk groups. This categorisation incorporated data from various sources, including patient demographics, co-morbidities, blood tests, and overall health status. In identifying patients at risk of postoperative complications, OpenPredictor demonstrated parity with consultant-led preoperative assessments. It accurately flagged 70% of patients who later experienced complications as moderate or high risk. The tool's efficiency in risk prediction was evidenced by its balanced accuracy (75.6%), sensitivity (70% with a 95% confidence interval of 62.05% to 76.91%), and a high negative predictive value (96.7%). OpenPredictor presents a scalable and consistent solution for managing elective surgery pathways, comparable in performance to secondary consultant opinions. Its integration into pre-assessment workflows assists in efficient patient categorisation, reduces late surgery cancellations, and optimises resource allocation. The Phase 1 evaluation of OpenPredictor underscores its potential for broader clinical application and highlights the need for ongoing data refinement and system integration to enhance its performance

Lag screw cut-out is a serious complication of dynamic hip screw fixation in trochanteric hip fractures. Lag screw position is recognised as a crucial factor influencing the occurrence of lag screw cut-out. We propose a modification of the Tip Apex Distance (TAD) and hypothesize that it could enhance the reliability of predicting lag screw cut-out in these injuries.

A retrospective study of hip fracture cases was conducted from January 2018 to July 2022. A total of 109 patients were eligible for the final analysis. The modified TAD was measured in millimetres, based on the sum of the traditional TAD in the lateral view and the net value of two distances in the anteroposterior (AP) view. The first distance is from the lag screw tip to the opposite point on the femoral head along the lag screw axis, while the second distance is from that point to the femoral head apex. The first distance is a positive value, whereas the second distance is positive if the lag screw is superior and negative if it is inferior. Receiver operating characteristic (ROC) curve analysis was used to assess the reliability of various parameters for evaluating the lag screw position within the femoral head.

Factors such as reduction quality, fracture pattern according to the AO/OTA classification, TAD, Calcar-Referenced TAD, Axis Blade Angle, Parker’s ratio in the AP view, Cleveland Zone 1, and modified TAD were statistically associated with lag screw cut-out. Among the tested parameters, the novel parameter exhibited 90.1% sensitivity and 90.9% specificity for predicting lag screw cut-out at a cut-off value of 25 mm, with a p-value < 0.001.

The modified TAD demonstrated the highest reliability in predicting lag screw cut-out. A value of 25 mm may potentially reduce the risk of lag screw cut-out in trochanteric hip fractures.

Aims. Surgical site infection (SSI) after soft-tissue sarcoma (STS) resection is a serious complication. The purpose of this retrospective study was to investigate the risk factors for SSI after STS resection, and to develop a nomogram that allows patient-specific risk assessment. Methods. A total of 547 patients with STS who underwent tumour resection between 2005 and 2021 were divided into a development cohort and a validation cohort. In the development cohort of 402 patients, the least absolute shrinkage and selection operator (LASSO) regression model was used to screen possible risk factors of SSI. To select risk factors and construct the prediction nomogram, multivariate logistic regression was used. The predictive power of the nomogram was evaluated by receiver operating curve (ROC) analysis in the validation cohort of 145 patients. Results. LASSO regression analysis selected possible risk factors for SSI, including age, diabetes, operating time, skin graft or flap, resected tumour size, smoking, and radiation therapy. Multivariate analysis revealed that age, diabetes, smoking during the previous year, operating time, and radiation therapy were independent risk factors for SSI. A nomogram was developed based on the results of multivariate logistic regression analysis. In the development cohort, the incidence of SSI was 4.5% in the low-risk group (risk score < 6.89) and 26.6% in the high-risk group (risk score ≥ 6.89; p < 0.001). In the validation cohort, the incidence of SSI was 2.0% in the low-risk group and 15.9% in the high-risk group (p = 0.004). Conclusion. Our nomogram will enable surgeons to assess the risk of SSI in patients with STS. In patients with high risk of SSI, frequent monitoring and aggressive interventions should be considered to prevent this. Cite this article: Bone Joint J 2024;106-B(5):492–500