Objectives. Accurate characterisation of fractures is essential in fracture management trials. However, this is often hampered by poor inter-observer agreement. This article describes the practicalities of defining the fracture population, based on the Neer classification, within a pragmatic
To assess the variation in pre-fracture quality of life (QoL) within the UK hip fracture population, and quantify the nature and strength of associations between QoL and other routinely collected patient characteristics and treatment choices. The World Hip Trauma Evaluation (WHiTE) study, an observational cohort study of UK hip fracture patients, collects a range of routine data and a health-related QoL score (EuroQol five-dimension questionnaire (EQ-5D)). Pre-fracture QoL data are summarized and statistical models fitted to understand associations between QoL, patient characteristics, fracture types, and operations.Aims
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Research into COVID-19 has been rapid in response to the dynamic global situation, which has resulted in heterogeneity of methodology and the communication of information. Adherence to reporting standards would improve the quality of evidence presented in future studies, and may ensure that findings could be interpreted in the context of the wider literature. The COVID-19 pandemic remains a dynamic situation, requiring continued assessment of the disease incidence and monitoring for the emergence of viral variants and their transmissibility, virulence, and susceptibility to vaccine-induced immunity. More work is needed to assess the long-term impact of COVID-19 infection on patients who sustain a hip fracture. The International
Objectives. As tumours of bone and soft tissue are rare,
Aims. This feasibility study investigates the utilization and cost of health resources related to formal and informal care, home adaptations, and physiotherapy among patients aged 60 years and above after hip fracture from a
Objectives. Pulsed electromagnetic field (PEMF) stimulation was evaluated after anterior cervical discectomy and fusion (ACDF) procedures in a randomized, controlled clinical study performed for United States Food and Drug Administration (FDA) approval. PEMF significantly increased fusion rates at six months, but 12-month fusion outcomes for subjects at elevated risk for pseudoarthrosis were not thoroughly reported. The objective of the current study was to evaluate the effect of PEMF treatment on subjects at increased risk for pseudoarthrosis after ACDF procedures. Methods. Two evaluations were performed that compared fusion rates between PEMF stimulation and a historical control (160 subjects) from the FDA investigational device exemption (IDE) study: a post hoc (PH) analysis of high-risk subjects from the FDA study (PH PEMF); and a
This study aimed to develop and validate a fully automated system that quantifies proximal femoral bone mineral density (BMD) from CT images. The study analyzed 978 pairs of hip CT and dual-energy X-ray absorptiometry (DXA) measurements of the proximal femur (DXA-BMD) collected from three institutions. From the CT images, the femur and a calibration phantom were automatically segmented using previously trained deep-learning models. The Hounsfield units of each voxel were converted into density (mg/cm3). Then, a deep-learning model trained by manual landmark selection of 315 cases was developed to select the landmarks at the proximal femur to rotate the CT volume to the neutral position. Finally, the CT volume of the femur was projected onto the coronal plane, and the areal BMD of the proximal femur (CT-aBMD) was quantified. CT-aBMD correlated to DXA-BMD, and a receiver operating characteristic (ROC) analysis quantified the accuracy in diagnosing osteoporosis.Aims
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This study aimed to explore the diagnostic value of synovial fluid neutrophil extracellular traps (SF-NETs) in periprosthetic joint infection (PJI) diagnosis, and compare it with that of microbial culture, serum ESR and CRP, synovial white blood cell (WBC) count, and polymorphonuclear neutrophil percentage (PMN%). In a single health centre, patients with suspected PJI were enrolled from January 2013 to December 2021. The inclusion criteria were: 1) patients who were suspected to have PJI; 2) patients with complete medical records; and 3) patients from whom sufficient synovial fluid was obtained for microbial culture and NET test. Patients who received revision surgeries due to aseptic failure (AF) were selected as controls. Synovial fluid was collected for microbial culture and SF-WBC, SF-PNM%, and SF-NET detection. The receiver operating characteristic curve (ROC) of synovial NET, WBC, PMN%, and area under the curve (AUC) were obtained; the diagnostic efficacies of these diagnostic indexes were calculated and compared.Aims
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This aim of this study was to analyze the detection rate of rare pathogens in bone and joint infections (BJIs) using metagenomic next-generation sequencing (mNGS), and the impact of mNGS on clinical diagnosis and treatment. A retrospective analysis was conducted on 235 patients with BJIs who were treated at our hospital between January 2015 and December 2021. Patients were divided into the no-mNGS group (microbial culture only) and the mNGS group (mNGS testing and microbial culture) based on whether mNGS testing was used or not.Aims
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Orthopaedic surgery requires grafts with sufficient mechanical strength. For this purpose, decellularized tissue is an available option that lacks the complications of autologous tissue. However, it is not widely used in orthopaedic surgeries. This study investigated clinical trials of the use of decellularized tissue grafts in orthopaedic surgery. Using the ClinicalTrials.gov (CTG) and the International Clinical Trials Registry Platform (ICTRP) databases, we comprehensively surveyed clinical trials of decellularized tissue use in orthopaedic surgeries registered before 1 September 2022. We evaluated the clinical results, tissue processing methods, and commercial availability of the identified products using academic literature databases and manufacturers’ websites.Aims
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To investigate the optimal thresholds and diagnostic efficacy of commonly used serological and synovial fluid detection indexes for diagnosing periprosthetic joint infection (PJI) in patients who have rheumatoid arthritis (RA). The data from 348 patients who had RA or osteoarthritis (OA) and had previously undergone a total knee (TKA) and/or a total hip arthroplasty (THA) (including RA-PJI: 60 cases, RA-non-PJI: 80 cases; OA-PJI: 104 cases, OA-non-PJI: 104 cases) were retrospectively analyzed. A receiver operating characteristic curve was used to determine the optimal thresholds of the CRP, ESR, synovial fluid white blood cell count (WBC), and polymorphonuclear neutrophil percentage (PMN%) for diagnosing RA-PJI and OA-PJI. The diagnostic efficacy was evaluated by comparing the area under the curve (AUC) of each index and applying the results of the combined index diagnostic test.Aims
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This study was designed to develop a model for predicting bone mineral density (BMD) loss of the femur after total hip arthroplasty (THA) using artificial intelligence (AI), and to identify factors that influence the prediction. Additionally, we virtually examined the efficacy of administration of bisphosphonate for cases with severe BMD loss based on the predictive model. The study included 538 joints that underwent primary THA. The patients were divided into groups using unsupervised time series clustering for five-year BMD loss of Gruen zone 7 postoperatively, and a machine-learning model to predict the BMD loss was developed. Additionally, the predictor for BMD loss was extracted using SHapley Additive exPlanations (SHAP). The patient-specific efficacy of bisphosphonate, which is the most important categorical predictor for BMD loss, was examined by calculating the change in predictive probability when hypothetically switching between the inclusion and exclusion of bisphosphonate.Aims
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The use of artificial intelligence (AI) is rapidly growing across many domains, of which the medical field is no exception. AI is an umbrella term defining the practical application of algorithms to generate useful output, without the need of human cognition. Owing to the expanding volume of patient information collected, known as ‘big data’, AI is showing promise as a useful tool in healthcare research and across all aspects of patient care pathways. Practical applications in orthopaedic surgery include: diagnostics, such as fracture recognition and tumour detection; predictive models of clinical and patient-reported outcome measures, such as calculating mortality rates and length of hospital stay; and real-time rehabilitation monitoring and surgical training. However, clinicians should remain cognizant of AI’s limitations, as the development of robust reporting and validation frameworks is of paramount importance to prevent avoidable errors and biases. The aim of this review article is to provide a comprehensive understanding of AI and its subfields, as well as to delineate its existing clinical applications in trauma and orthopaedic surgery. Furthermore, this narrative review expands upon the limitations of AI and future direction. Cite this article:
To explore the clinical efficacy of using two different types of articulating spacers in two-stage revision for chronic knee periprosthetic joint infection (kPJI). A retrospective cohort study of 50 chronic kPJI patients treated with two types of articulating spacers between January 2014 and March 2022 was conducted. The clinical outcomes and functional status of the different articulating spacers were compared. Overall, 17 patients were treated with prosthetic spacers (prosthetic group (PG)), and 33 patients were treated with cement spacers (cement group (CG)). The CG had a longer mean follow-up period (46.67 months (SD 26.61)) than the PG (24.82 months (SD 16.46); p = 0.001).Aims
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Fracture-related infection (FRI) is commonly classified based on the time of onset of symptoms. Early infections (< two weeks) are treated with debridement, antibiotics, and implant retention (DAIR). For late infections (> ten weeks), guidelines recommend implant removal due to tolerant biofilms. For delayed infections (two to ten weeks), recommendations are unclear. In this study we compared infection clearance and bone healing in early and delayed FRI treated with DAIR in a rabbit model.
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A substantial fraction of patients undergoing knee arthroplasty (KA) or hip arthroplasty (HA) do not achieve an improvement as high as the minimal clinically important difference (MCID), i.e. do not achieve a meaningful improvement. Using three patient-reported outcome measures (PROMs), our aim was: 1) to assess machine learning (ML), the simple pre-surgery PROM score, and logistic-regression (LR)-derived performance in their prediction of whether patients undergoing HA or KA achieve an improvement as high or higher than a calculated MCID; and 2) to test whether ML is able to outperform LR or pre-surgery PROM scores in predictive performance. MCIDs were derived using the change difference method in a sample of 1,843 HA and 1,546 KA patients. An artificial neural network, a gradient boosting machine, least absolute shrinkage and selection operator (LASSO) regression, ridge regression, elastic net, random forest, LR, and pre-surgery PROM scores were applied to predict MCID for the following PROMs: EuroQol five-dimension, five-level questionnaire (EQ-5D-5L), EQ visual analogue scale (EQ-VAS), Hip disability and Osteoarthritis Outcome Score-Physical Function Short-form (HOOS-PS), and Knee injury and Osteoarthritis Outcome Score-Physical Function Short-form (KOOS-PS).Aims
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We compared the risks of re-revision and mortality between two-stage and single-stage revision surgeries among patients with infected primary hip arthroplasty. Patients with a periprosthetic joint infection (PJI) of their primary arthroplasty revised with single-stage or two-stage procedure in England and Wales between 2003 and 2014 were identified from the National Joint Registry. We used Poisson regression with restricted cubic splines to compute hazard ratios (HRs) at different postoperative periods. The total number of revisions and re-revisions undergone by patients was compared between the two strategies.Aims
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In this study, we aimed to visualize the spatial distribution characteristics of femoral head necrosis using a novel measurement method. We retrospectively collected CT imaging data of 108 hips with non-traumatic osteonecrosis of the femoral head from 76 consecutive patients (mean age 34.3 years (SD 8.1), 56.58% male (n = 43)) in two clinical centres. The femoral head was divided into 288 standard units (based on the orientation of units within the femoral head, designated as N[Superior], S[Inferior], E[Anterior], and W[Posterior]) using a new measurement system called the longitude and latitude division system (LLDS). A computer-aided design (CAD) measurement tool was also developed to visualize the measurement of the spatial location of necrotic lesions in CT images. Two orthopaedic surgeons independently performed measurements, and the results were used to draw 2D and 3D heat maps of spatial distribution of necrotic lesions in the femoral head, and for statistical analysis.Aims
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