Aims. This feasibility study investigates the utilization and
Objectives. “Virtual fracture clinics” have been reported as a safe and effective alternative to the traditional fracture clinic. Robust protocols are used to identify cases that do not require further review, with the remainder triaged to the most appropriate subspecialist at the optimum time for review. The objective of this study was to perform a “top-down” analysis of the
Implant-related infection is one of the leading reasons for failure in orthopaedics and trauma, and results in high social and economic costs. Various antibacterial coating technologies have proven to be safe and effective both in preclinical and clinical studies, with post-surgical implant-related infections reduced by 90% in some cases, depending on the type of coating and experimental setup used. Economic assessment may enable the cost-to-benefit profile of any given antibacterial coating to be defined, based on the expected infection rate with and without the coating, the
Objectives. To assess the clinical and cost-effectiveness of a virtual fracture clinic (VFC) model, and supplement the literature regarding this service as recommended by The National Institute for Health and Care Excellence (NICE) and the British Orthopaedic Association (BOA). Methods. This was a retrospective study including all patients (17 116) referred to fracture clinics in a London District General Hospital from May 2013 to April 2016, using hospital-level data. We used interrupted time series analysis with segmented regression, and direct before-and-after comparison, to study the impact of VFCs introduced in December 2014 on six clinical parameters and on local Clinical Commissioning Group (CCG) spend. Student’s t-tests were used for direct comparison, whilst segmented regression was employed for projection analysis. Results. There were statistically significant reductions in numbers of new patients seen face-to-face (140.4, . sd. 39.6 versus 461.6, . sd. 61.63, p < 0.0001), days to first orthopaedic review (5.2, . sd. 0.66 versus 10.9, . sd. 1.5, p < 0.0001), discharges (33.5, . sd. 3.66 versus 129.2, . sd. 7.36, p < 0.0001) and non-attendees (14.82, . sd. 1.48 versus 60.47, . sd. 2.68, p < 0.0001), in addition to a statistically significant increase in number of patients seen within 72-hours (46.4% 3873 of 8345 versus 5.1% 447 of 8771, p < 0.0001). There was a non-significant increase in consultation time of 1 minute 9 seconds (14 minutes 53 seconds . sd. 106 seconds versus 13 minutes 44 seconds . sd. 128 seconds, p = 0.0878). VFC saved the local CCG £67 385.67 in the first year and is set to save £129 885.67 annually thereafter. Conclusions. We have shown VFCs are clinically and cost-effective, with improvement across several clinical performance parameters and substantial financial savings for CCGs. To our knowledge this is the largest study addressing clinical practice implications of VFCs in England, using robust methodology to adjust for pre-existing trends. Further studies are required to appreciate whether our results are reproducible with local variations in the VFC model and payment tariffs. Cite this article: A. McKirdy, A. M. Imbuldeniya. The clinical and
Aims. The present study aimed to investigate whether patients with inflammatory bowel disease (IBD) undergoing joint arthroplasty have a higher incidence of adverse outcomes than those without IBD. Methods. A comprehensive literature search was conducted to identify eligible studies reporting postoperative outcomes in IBD patients undergoing joint arthroplasty. The primary outcomes included postoperative complications, while the secondary outcomes included unplanned readmission, length of stay (LOS), joint reoperation/implant revision, and
The high prevalence of osteoarthritis (OA), as well as the current lack of disease-modifying drugs for OA, has provided a rationale for regenerative medicine as a possible treatment modality for OA treatment. In this editorial, the current status of regenerative medicine in OA including stem cells, exosomes, and genes is summarized along with the author’s perspectives. Despite a tremendous interest, so far there is very little evidence proving the efficacy of this modality for clinical application. As symptomatic relief is not sufficient to justify the high
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Despite the vast quantities of published artificial intelligence (AI) algorithms that target trauma and orthopaedic applications, very few progress to inform clinical practice. One key reason for this is the lack of a clear pathway from development to deployment. In order to assist with this process, we have developed the Clinical Practice Integration of Artificial Intelligence (CPI-AI) framework – a five-stage approach to the clinical practice adoption of AI in the setting of trauma and orthopaedics, based on the IDEAL principles ( Cite this article:
The aim of this investigation was to compare risk of infection in both cemented and uncemented hemiarthroplasty (HA) as well as in total hip arthroplasty (THA) following femoral neck fracture. Data collection was performed using the German Arthroplasty Registry (EPRD). In HA and THA following femoral neck fracture, fixation method was divided into cemented and uncemented prostheses and paired according to age, sex, BMI, and the Elixhauser Comorbidity Index using Mahalanobis distance matching.Aims
Methods
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
Methods
The aim of this study was to create artificial intelligence (AI) software with the purpose of providing a second opinion to physicians to support distal radius fracture (DRF) detection, and to compare the accuracy of fracture detection of physicians with and without software support. The dataset consisted of 26,121 anonymized anterior-posterior (AP) and lateral standard view radiographs of the wrist, with and without DRF. The convolutional neural network (CNN) model was trained to detect the presence of a DRF by comparing the radiographs containing a fracture to the inconspicuous ones. A total of 11 physicians (six surgeons in training and five hand surgeons) assessed 200 pairs of randomly selected digital radiographs of the wrist (AP and lateral) for the presence of a DRF. The same images were first evaluated without, and then with, the support of the CNN model, and the diagnostic accuracy of the two methods was compared.Aims
Methods
Glucose-insulin-potassium (GIK) is protective following cardiac myocyte ischaemia-reperfusion (IR) injury, however the role of GIK in protecting skeletal muscle from IR injury has not been evaluated. Given the similar mechanisms by which cardiac and skeletal muscle sustain an IR injury, we hypothesized that GIK would similarly protect skeletal muscle viability. A total of 20 C57BL/6 male mice (10 control, 10 GIK) sustained a hindlimb IR injury using a 2.5-hour rubber band tourniquet. Immediately prior to tourniquet placement, a subcutaneous osmotic pump was placed which infused control mice with saline (0.9% sodium chloride) and treated mice with GIK (40% glucose, 50 U/l insulin, 80 mEq/L KCl, pH 4.5) at a rate of 16 µl/hr for 26.5 hours. At 24 hours following tourniquet removal, bilateral (tourniqueted and non-tourniqueted) gastrocnemius muscles were triphenyltetrazolium chloride (TTC)-stained to quantify percentage muscle viability. Bilateral peroneal muscles were used for gene expression analysis, serum creatinine and creatine kinase activity were measured, and a validated murine ethogram was used to quantify pain before euthanasia.Aims
Methods
The Oxford Shoulder Score (OSS) is a 12-item measure commonly used for the assessment of shoulder surgeries. This study explores whether computerized adaptive testing (CAT) provides a shortened, individually tailored questionnaire while maintaining test accuracy. A total of 16,238 preoperative OSS were available in the National Joint Registry (NJR) for England, Wales, Northern Ireland, the Isle of Man, and the States of Guernsey dataset (April 2012 to April 2022). Prior to CAT, the foundational item response theory (IRT) assumptions of unidimensionality, monotonicity, and local independence were established. CAT compared sequential item selection with stopping criteria set at standard error (SE) < 0.32 and SE < 0.45 (equivalent to reliability coefficients of 0.90 and 0.80) to full-length patient-reported outcome measure (PROM) precision.Aims
Methods
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:
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
Methods
Degenerative cervical spondylosis (DCS) is a common musculoskeletal disease that encompasses a wide range of progressive degenerative changes and affects all components of the cervical spine. DCS imposes very large social and economic burdens. However, its genetic basis remains elusive. Predicted whole-blood and skeletal muscle gene expression and genome-wide association study (GWAS) data from a DCS database were integrated, and functional summary-based imputation (FUSION) software was used on the integrated data. A transcriptome-wide association study (TWAS) was conducted using FUSION software to assess the association between predicted gene expression and DCS risk. The TWAS-identified genes were verified via comparison with differentially expressed genes (DEGs) in DCS RNA expression profiles in the Gene Expression Omnibus (GEO) (Accession Number: GSE153761). The Functional Mapping and Annotation (FUMA) tool for genome-wide association studies and Meta tools were used for gene functional enrichment and annotation analysis.Aims
Methods
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
Methods
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
Methods
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
Methods
This study was designed to characterize the recurrence incidence and risk factors of antibiotic-loaded cement spacer (ALCS) for definitive bone defect treatment in limb osteomyelitis. We included adult patients with limb osteomyelitis who received debridement and ALCS insertion into the bone defect as definitive management between 2013 and 2020 in our clinical centre. The follow-up time was at least two years. Data on patients’ demographics, clinical characteristics, and infection recurrence were retrospectively collected and analyzed.Aims
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