Bacterial infection activates neutrophils to release neutrophil extracellular traps (NETs) in bacterial biofilms of periprosthetic joint infections (PJIs). The aim of this study was to evaluate the increase in NET activation and release (NETosis) and haemostasis markers in the plasma of patients with PJI, to evaluate whether such plasma induces the activation of neutrophils, to ascertain whether increased NETosis is also mediated by reduced DNaseI activity, to explore novel therapeutic interventions for NETosis in PJI in vitro, and to evaluate the potential diagnostic use of these markers. We prospectively recruited 107 patients in the preoperative period of prosthetic surgery, 71 with a suspicion of PJI and 36 who underwent arthroplasty for non-septic indications as controls, and obtained citrated plasma. PJI was confirmed in 50 patients. We measured NET markers, inflammation markers, DNaseI activity, haemostatic markers, and the thrombin generation test (TGT). We analyzed the ability of plasma from confirmed PJI and controls to induce NETosis and to degrade in vitro-generated NETs, and explored the therapeutic restoration of the impairment to degrade NETs of PJI plasma with recombinant human DNaseI. Finally, we assessed the contribution of these markers to the diagnosis of PJI.Aims
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Children with spinal dysraphism can develop various musculoskeletal deformities, necessitating a range of orthopaedic interventions, causing significant morbidity, and making considerable demands on resources. This systematic review aimed to identify what outcome measures have been reported in the literature for children with spinal dysraphism who undergo orthopaedic interventions involving the lower limbs. A PROSPERO-registered systematic literature review was performed following PRISMA guidelines. All relevant studies published until January 2023 were identified. Individual outcomes and outcome measurement tools were extracted verbatim. The measurement tools were assessed for reliability and validity, and all outcomes were grouped according to the Outcome Measures Recommended for use in Randomized Clinical Trials (OMERACT) filters.Aims
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Hip fractures are some of the most common fractures encountered in orthopaedic practice. We aimed to identify whether perioperative hypotension is a predictor of 30-day mortality, and to stratify patient groups that would benefit from closer monitoring and early intervention. While there is literature on intraoperative blood pressure, there are limited studies examining pre- and postoperative blood pressure. We conducted a prospective observational cohort study over a one-year period from December 2021 to December 2022. Patient demographic details, biochemical results, and haemodynamic observations were taken from electronic medical records. Statistical analysis was conducted with the Cox proportional hazards model, and the effects of independent variables estimated with the Wald statistic. Kaplan-Meier survival curves were estimated with the log-rank test.Aims
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This study aimed to compare the performance of survival prediction models for bone metastases of the extremities (BM-E) with pathological fractures in an Asian cohort, and investigate patient characteristics associated with survival. This retrospective cohort study included 469 patients, who underwent surgery for BM-E between January 2009 and March 2022 at a tertiary hospital in South Korea. Postoperative survival was calculated using the PATHFx3.0, SPRING13, OPTIModel, SORG, and IOR models. Model performance was assessed with area under the curve (AUC), calibration curve, Brier score, and decision curve analysis. Cox regression analyses were performed to evaluate the factors contributing to survival.Aims
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Literature surrounding artificial intelligence (AI)-related applications for hip and knee arthroplasty has proliferated. However, meaningful advances that fundamentally transform the practice and delivery of joint arthroplasty are yet to be realized, despite the broad range of applications as we continue to search for meaningful and appropriate use of AI. AI literature in hip and knee arthroplasty between 2018 and 2021 regarding image-based analyses, value-based care, remote patient monitoring, and augmented reality was reviewed. Concerns surrounding meaningful use and appropriate methodological approaches of AI in joint arthroplasty research are summarized. Of the 233 AI-related orthopaedics articles published, 178 (76%) constituted original research, while the rest consisted of editorials or reviews. A total of 52% of original AI-related research concerns hip and knee arthroplasty (n = 92), and a narrative review is described. Three studies were externally validated. Pitfalls surrounding present-day research include conflating vernacular (“AI/machine learning”), repackaging limited registry data, prematurely releasing internally validated prediction models, appraising model architecture instead of inputted data, withholding code, and evaluating studies using antiquated regression-based guidelines. While AI has been applied to a variety of hip and knee arthroplasty applications with limited clinical impact, the future remains promising if the question is meaningful, the methodology is rigorous and transparent, the data are rich, and the model is externally validated. Simple checkpoints for meaningful AI adoption include ensuring applications focus on: administrative support over clinical evaluation and management; necessity of the advanced model; and the novelty of the question being answered. Cite this article:
Prediction tools are instruments which are commonly used to estimate the prognosis in oncology and facilitate clinical decision-making in a more personalized manner. Their popularity is shown by the increasing numbers of prediction tools, which have been described in the medical literature. Many of these tools have been shown to be useful in the field of soft-tissue sarcoma of the extremities (eSTS). In this annotation, we aim to provide an overview of the available prediction tools for eSTS, provide an approach for clinicians to evaluate the performance and usefulness of the available tools for their own patients, and discuss their possible applications in the management of patients with an eSTS. Cite this article:
Total hip arthroplasty (THA) and total knee arthroplasty (TKA) are common orthopaedic procedures requiring postoperative radiographs to confirm implant positioning and identify complications. Artificial intelligence (AI)-based image analysis has the potential to automate this postoperative surveillance. The aim of this study was to prepare a scoping review to investigate how AI is being used in the analysis of radiographs following THA and TKA, and how accurate these tools are. The Embase, MEDLINE, and PubMed libraries were systematically searched to identify relevant articles. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews and Arksey and O’Malley framework were followed. Study quality was assessed using a modified Methodological Index for Non-Randomized Studies tool. AI performance was reported using either the area under the curve (AUC) or accuracy.Aims
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Heterotopic ossification (HO) is a common complication after elbow trauma and can cause severe upper limb disability. Although multiple prognostic factors have been reported to be associated with the development of post-traumatic HO, no model has yet been able to combine these predictors more succinctly to convey prognostic information and medical measures to patients. Therefore, this study aimed to identify prognostic factors leading to the formation of HO after surgery for elbow trauma, and to establish and validate a nomogram to predict the probability of HO formation in such particular injuries. This multicentre case-control study comprised 200 patients with post-traumatic elbow HO and 229 patients who had elbow trauma but without HO formation between July 2019 and December 2020. Features possibly associated with HO formation were obtained. The least absolute shrinkage and selection operator regression model was used to optimize feature selection. Multivariable logistic regression analysis was applied to build the new nomogram: the Shanghai post-Traumatic Elbow Heterotopic Ossification Prediction model (STEHOP). STEHOP was validated by concordance index (C-index) and calibration plot. Internal validation was conducted using bootstrapping validation.Aims
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Artificial intelligence (AI) is, in essence, the concept of ‘computer thinking’, encompassing methods that train computers to perform and learn from executing certain tasks, called machine learning, and methods to build intricate computer models that both learn and adapt, called complex neural networks. Computer vision is a function of AI by which machine learning and complex neural networks can be applied to enable computers to capture, analyze, and interpret information from clinical images and visual inputs. This annotation summarizes key considerations and future perspectives concerning computer vision, questioning the need for this technology (the ‘why’), the current applications (the ‘what’), and the approach to unlocking its full potential (the ‘how’). Cite this article:
The aim of this study was to determine whether total hip arthroplasty (THA) for chronic hip pain due to unilateral primary osteoarthritis (OA) has a beneficial effect on cognitive performance. A prospective cohort study was conducted with 101 patients with end-stage hip OA scheduled for THA (mean age 67.4 years (SD 9.5), 51.5% female (n = 52)). Patients were assessed at baseline as well as after three and months. Primary outcome was cognitive performance measured by d2 Test of Attention at six months, Trail Making Test (TMT), FAS-test, Rivermead Behavioural Memory Test (RBMT; story recall subtest), and Rey-Osterrieth Complex Figure Test (ROCF). The improvement of cognitive performance was analyzed using repeated measures analysis of variance.Aims
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Fungal and mycobacterial periprosthetic joint infections (PJI) are rare events. Clinicians are wary of missing these diagnoses, often leading to the routine ordering of fungal and mycobacterial cultures on periprosthetic specimens. Our goal was to examine the utility of these cultures and explore a modern bacterial culture technique using bacterial blood culture bottles (BCBs) as an alternative. We performed a retrospective review of patients diagnosed with hip or knee PJI between 1 January 2010 and 31 December 2019, at the Mayo Clinic in Rochester, Minnesota, USA. We included patients aged 18 years or older who had fungal, mycobacterial, or both cultures performed together with bacterial cultures. Cases with positive fungal or mycobacterial cultures were reviewed using the electronic medical record to classify the microbiological findings as representing true infection or not.Aims
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The aim of this study was to assess whether it is possible to predict the mortality, and the extent and time of neurological recovery from the time of the onset of symptoms and MRI grade, in patients with the cerebral fat embolism syndrome (CFES). This has not previously been investigated. The study included 34 patients who were diagnosed with CFES following trauma between 2012 and 2018. The clinical diagnosis was confirmed and the severity graded by MRI. We investigated the rate of mortality, the time and extent of neurological recovery, the time between the injury and the onset of symptoms, the clinical severity of the condition, and the MRI grade. All patients were male with a mean age of 29.7 years (18 to 70). The mean follow-up was 4.15 years (2 to 8), with neurological recovery being assessed by the Glasgow Outcome Scale and the Mini-Mental State Examination.Aims
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There is increasing popularity in the use of artificial intelligence and machine-learning techniques to provide diagnostic and prognostic models for various aspects of Trauma & Orthopaedic surgery. However, correct interpretation of these models is difficult for those without specific knowledge of computing or health data science methodology. Lack of current reporting standards leads to the potential for significant heterogeneity in the design and quality of published studies. We provide an overview of machine-learning techniques for the lay individual, including key terminology and best practice reporting guidelines. Cite this article:
This study used an artificial neural network (ANN) model to determine the most important pre- and perioperative variables to predict same-day discharge in patients undergoing total knee arthroplasty (TKA). Data for this study were collected from the National Surgery Quality Improvement Program (NSQIP) database from the year 2018. Patients who received a primary, elective, unilateral TKA with a diagnosis of primary osteoarthritis were included. Demographic, preoperative, and intraoperative variables were analyzed. The ANN model was compared to a logistic regression model, which is a conventional machine-learning algorithm. Variables collected from 28,742 patients were analyzed based on their contribution to hospital length of stay.Aims
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To assess the characteristic clinical features, management, and outcome of patients who present to orthopaedic surgeons with functional dystonia affecting the foot and ankle. We carried out a retrospective search of our records from 2000 to 2019 of patients seen in our adult tertiary referral foot and ankle unit with a diagnosis of functional dystonia.Aims
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It remains difficult to diagnose early postoperative periprosthetic joint infection (PJI) following total knee arthroplasty (TKA). We aimed to validate the optimal cutoff values of ESR, CRP, and synovial fluid analysis for detecting early postoperative PJI in a large series of primary TKAs. We retrospectively identified 27,066 primary TKAs performed between 2000 and 2019. Within 12 weeks, 169 patients (170 TKAs) had an aspiration. The patients were divided into two groups: those evaluated ≤ six weeks, or between six and 12 weeks postoperatively. The 2011 Musculoskeletal Infection Society (MSIS) criteria for PJI diagnosis in 22 TKAs. The mean follow-up was five years (two months to 17 years). The results were compared using medians and Mann-Whitney U tests and thresholds were analyzed using receiver operator characteristic curves.Aims
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Various surgical techniques have been described for total hip arthroplasty (THA) in patients with Crowe type III dislocated hips, who have a large acetabular bone defect. The aim of this study was to evaluate the long-term clinical results of patients in whom anatomical reconstruction of the acetabulum was performed using a cemented acetabular component and autologous bone graft from the femoral neck. A total of 22 patients with Crowe type III dislocated hips underwent 28 THAs using bone graft from the femoral neck between 1979 and 2000. A Charnley cemented acetabular component was placed at the level of the true acetabulum after preparation with bone grafting. All patients were female with a mean age at the time of surgery of 54 years (35 to 68). A total of 18 patients (21 THAs) were followed for a mean of 27.2 years (20 to 33) after the operation.Aims
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Hip displacement, common in patients with cerebral palsy (CP), causes pain and hinders adequate care. Hip reconstructive surgery (HRS) is performed to treat hip displacement; however, only a few studies have quantitatively assessed femoral head sphericity after HRS. The aim of this study was to quantitatively assess improvement in hip sphericity after HRS in patients with CP. We retrospectively analyzed hip radiographs of patients who had undergone HRS because of CP-associated hip displacement. The pre- and postoperative migration percentage (MP), femoral neck-shaft angle (NSA), and sphericity, as determined by the Mose hip ratio (MHR), age at surgery, Gross Motor Function Classification System level, surgical history including Dega pelvic osteotomy, and triradiate cartilage status were studied. Regression analyses using linear mixed model were performed to identify factors affecting hip sphericity improvement.Aims
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Metagenomic next-generation sequencing (mNGS) is useful in the diagnosis of infectious disease. However, while it is highly sensitive at identifying bacteria, it does not provide information on the sensitivity of the organisms to antibiotics. The purpose of this study was to determine whether the results of mNGS can be used to guide optimization of culture methods to improve the sensitivity of culture from intraoperative samples. Between July 2014 and October 2019, patients with suspected joint infection (JI) from whom synovial fluid (SF) was obtained preoperatively were enrolled. Preoperative aspirated SF was analyzed by conventional microbial culture and mNGS. In addition to samples taken for conventional microbial culture, some samples were taken for intraoperative culture to optimize the culture method according to the preoperative mNGS results. The demographic characteristics, medical history, laboratory examination, mNGS, and culture results of the patients were recorded, and the possibility of the optimized culture methods improving diagnostic efficiency was evaluated.Aims
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