The outcomes of patients with unexpected positive cultures (UPCs) during revision total hip arthroplasty (THA) and total knee arthroplasty (TKA) remain unknown. The objectives of this study were to establish the prevalence and infection-free implant survival in UPCs during presumed aseptic single-stage revision THA and TKA at mid-term follow-up. This study included 297 patients undergoing presumed aseptic single-stage revision THA or TKA at a single treatment centre. All patients with at least three UPCs obtained during revision surgery were treated with minimum three months of oral antibiotics following revision surgery. The prevalence of UPCs and causative microorganisms, the recurrence of periprosthetic joint infections (PJIs), and the infection-free implant survival were established at minimum five years’ follow-up (5.1 to 12.3).Aims
Methods
Aims. 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. Methods. Data pre-processing and analyses were conducted according to the Artificial intelligence to Revolutionize the patient Care pathway in Hip and knEe aRthroplastY (ARCHERY) project protocol. This included use of de-identified Scottish regional clinical data of patients referred for consideration of THA/TKA, held in a secure data environment designed for artificial intelligence (AI) inference. Only preoperative radiology reports were included. NLP
A higher failure rate has been reported in haematogenous periprosthetic joint infection (PJI) compared to non-haematogenous PJI. The reason for this difference is unknown. We investigated the outcome of haematogenous and non-haematogenous PJI to analyze the risk factors for failure in both groups of patients. Episodes of knee or hip PJI (defined by the European Bone and Joint Infection Society criteria) treated at our institution between January 2015 and October 2020 were included in a retrospective PJI cohort. Episodes with a follow-up of > one year were stratified by route of infection into haematogenous and non-haematogenous PJI. Probability of failure-free survival was estimated using the Kaplan-Meier method, and compared between groups using log-rank test. Univariate and multivariate analysis was applied to assess risk factors for failure.Aims
Methods
We aim to evaluate the usefulness of postoperative blood tests by investigating the incidence of abnormal results following total joint replacement (TJR), as well as identifying preoperative risk factors for abnormal blood test results postoperatively, especially pertaining to anaemia and acute kidney injury (AKI). This is a retrospective cohort study of patients who had elective TJR between January and December 2019 at a tertiary centre. Data gathered included age at time of surgery, sex, BMI, American Society of Anesthesiologists (ASA) grade, preoperative and postoperative laboratory test results, haemoglobin (Hgb), white blood count (WBC), haematocrit (Hct), platelets (Plts), sodium (Na+), potassium (K+), creatinine (Cr), estimated glomerular filtration rate (eGFR), and Ferritin (ug/l). Abnormal blood tests, AKI, electrolyte imbalance, anaemia, transfusion, reoperation, and readmission within one year were reported.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
The aim of this study was to determine the prevalence of depressive and anxiety disorders prior to total hip (THA) and total knee arthroplasty (TKA) and to assess their impact on the rates of any infection, revision, or reoperation. Between January 2000 and March 2019, 21,469 primary and revision arthroplasties (10,011 THAs; 11,458 TKAs), which were undertaken in 15,504 patients at a single academic medical centre, were identified from a 27-county linked electronic medical record (EMR) system. Depressive and anxiety disorders were identified by diagnoses in the EMR or by using a natural language processing program with subsequent validation from review of the medical records. Patients with mental health diagnoses other than anxiety or depression were excluded.Aims
Methods
The extended wait that most patients are now experiencing for hip and knee arthroplasty has raised questions about whether reliance on waiting time as the primary driver for prioritization is ethical, and if other additional factors should be included in determining surgical priority. Our Prioritization of THose aWaiting hip and knee ArthroplastY (PATHWAY) project will explore which perioperative factors are important to consider when prioritizing those on the waiting list for hip and knee arthroplasty, and how these factors should be weighted. The final product will include a weighted benefit score that can be used to aid in surgical prioritization for those awaiting elective primary hip and knee arthroplasty. There will be two linked work packages focusing on opinion from key stakeholders (patients and surgeons). First, an online modified Delphi process to determine a consensus set of factors that should be involved in patient prioritization. This will be performed using standard Delphi methodology consisting of multiple rounds where following initial individual rating there is feedback, discussion, and further recommendations undertaken towards eventual consensus. The second stage will then consist of a Discrete Choice Experiment (DCE) to allow for priority setting of the factors derived from the Delphi through elicitation of weighted benefit scores. The DCE consists of several choice tasks designed to elicit stakeholder preference regarding included attributes (factors).Aims
Methods
The aim of this study was to estimate the 90-day periprosthetic joint infection (PJI) rates following total knee arthroplasty (TKA) and total hip arthroplasty (THA) for osteoarthritis (OA). This was a data linkage study using the New South Wales (NSW) Admitted Patient Data Collection (APDC) and the Australian Orthopaedic Association National Joint Replacement Registry (AOANJRR), which collect data from all public and private hospitals in NSW, Australia. Patients who underwent a TKA or THA for OA between 1 January 2002 and 31 December 2017 were included. The main outcome measures were 90-day incidence rates of hospital readmission for: revision arthroplasty for PJI as recorded in the AOANJRR; conservative definition of PJI, defined by T84.5, the PJI diagnosis code in the APDC; and extended definition of PJI, defined by the presence of either T84.5, or combinations of diagnosis and procedure code groups derived from recursive binary partitioning in the APDC.Aims
Methods
Aims. 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. Methods. 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. Results. Of the 455 studies identified, only 12 were suitable for inclusion. Nine reported implant identification and three described predicting risk of implant failure. Of the 12, three studies compared AI performance with orthopaedic surgeons. AI-based implant identification achieved AUC 0.992 to 1, and most
The aim of this study was to conduct a cross-sectional, observational cohort study of patients presenting for revision of a total hip, or total or unicompartmental knee arthroplasty, to understand current routes to revision surgery and explore differences in symptoms, healthcare use, reason for revision, and the revision surgery (surgical time, components, length of stay) between patients having regular follow-up and those without. Data were collected from participants and medical records for the 12 months prior to revision. Patients with previous revision, metal-on-metal articulations, or hip hemiarthroplasty were excluded. Participants were retrospectively classified as ‘Planned’ or ‘Unplanned’ revision. Multilevel regression and propensity score matching were used to compare the two groups.Aims
Methods
Aims. Fungal periprosthetic joint infections (fPJIs) are rare complications, constituting only 1% of all PJIs. Neither a uniform definition for fPJI has been established, nor a standardized treatment regimen. Compared to bacterial PJI, there is little evidence for fPJI in the literature with divergent results. Hence, we implemented a novel treatment
To determine the trajectories of patient reported pain and functional disability over five years following total hip arthroplasty (THA) or total knee arthroplasty (TKA). A prospective, longitudinal cohort sub-study within the National Joint Registry (NJR) was undertaken. In all, 20,089 patients who underwent primary THA and 22,489 who underwent primary TKA between 2009 and 2010 were sent Oxford Hip Score (OHS) and Oxford Knee Score (OKS) questionnaires at six months, and one, three, and five years postoperatively. OHS and OKS were disaggregated into pain and function subscales. A k-means clustering procedure assigned each patient to a longitudinal trajectory group for pain and function. Ordinal regression was used to predict trajectory group membership using baseline OHS and OKS score, age, BMI, index of multiple deprivation, sex, ethnicity, geographical location, and American Society of Anesthesiologists grade.Aims
Methods
As a proven and comprehensive molecular technique, metagenomic next-generation sequencing (mNGS) has shown its potential in the diagnosis of pathogens in patients with periprosthetic joint infection (PJI), using a single type of specimen. However, the optimal use of mNGS in the management of PJI has not been explored. In this study, we evaluated the diagnostic value of mNGS using three types of specimen with the aim of achieving a better choice of specimen for mNGS in these patients. In this prospective study, 177 specimens were collected from 59 revision arthroplasties, including periprosthetic tissues, synovial fluid, and prosthetic sonicate fluid. Each specimen was divided into two, one for mNGS and one for culture. The criteria of the Musculoskeletal Infection Society were used to define PJI (40 cases) and aseptic failure (19 cases).Aims
Methods
Aims. To develop and validate patient-centred
Currently, the US Center for Medicaid and Medicare Services (CMS) has been testing bundled payments for revision total joint arthroplasty (TJA) through the Bundled Payment for Care Improvement (BPCI) programme. Under the BPCI, bundled payments for revision TJAs are defined on the basis of diagnosis-related groups (DRGs). However, these DRG-based bundled payment models may not be adequate to account appropriately for the varying case-complexity seen in revision TJAs. The 2008-2014 Medicare 5% Standard Analytical Files (SAF5) were used to identify patients undergoing revision TJA under DRG codes 466, 467, or 468. Generalized linear regression models were built to assess the independent marginal cost-impact of patient, procedural, and geographic characteristics on 90-day costs.Aims
Methods
Total joint replacement (TJR) is a high-cost, high-volume procedure that impacts patients’ quality of life. Informed decisions are important for patients facing TJR. The quality of information provided by websites regarding TJR is highly variable. We aimed to measure the quality of TJR information online. We identified 10,800 websites using 18 TJR-related keywords (conditions and procedures) across the Australian, French, German and Spanish Google search engines. We used the Health on the Net (HON) toolbar to evaluate the first 150 websites downloaded for every keyword in each language. The quality of information on websites was inspected, accounting for differences by language and tertiles. We also undertook an analysis of English websites to explore types of website providers.Aims
Methods
Prosthetic joint infection (PJI) remains a major clinical challenge. Neutrophil CD64 index, Fc-gamma receptor 1 (FcγR1), plays an important role in mediating inflammation of bacterial infections and therefore could be a valuable biomarker for PJI. The aim of this study is to compare the neutrophil CD64 index in synovial and blood diagnostic ability with the standard clinical tests for discrimination PJI and aseptic implant failure. A total of 50 patients undergoing revision hip and knee arthroplasty were enrolled into a prospective study. According to Musculoskeletal Infection Society (MSIS) criteria, 25 patients were classified as infected and 25 as not infected. In all patients, neutrophil CD64 index and percentage of polymorphonuclear neutrophils (PMN%) in synovial fluid, serum CRP, ESR, and serum CD64 index levels were measured preoperatively. Receiver operating characteristic (ROC) curves and the area under the curve (AUC) were analyzed for each biomarker.Aims
Methods
The aim of this study was to evaluate the diagnostic accuracy of the synovial alpha-defensin enzyme-linked immunosorbent assay (ELISA) for the diagnosis of prosthetic joint infection (PJI) in the work-up prior to revision of total hip (THA) and knee arthroplasty (TKA). Inclusion criteria for this prospective cohort study were acute or chronic symptoms of the index joint without specific exclusion criteria. Synovial fluid aspirates of 202 patients were analyzed and semiquantitative laboratory alpha-defensin ELISA was performed. Final diagnosis of PJI was established by examination of samples obtained during revision surgery.Aims
Patients and Methods
Aims. This study aimed to develop a virtual clinic for the purpose of reducing face-to-face orthopaedic consultations. Patients and Methods. Anonymized experts (hip and knee arthroplasty patients, surgeons, physiotherapists, radiologists, and arthroplasty practitioners) gave feedback via a Delphi Consensus Technique. This consisted of an iterative sequence of online surveys, during which virtual documents, made up of a patient-reported questionnaire, standardized radiology report, and decision-guiding
Fungal prosthetic joint infections (PJIs) are rare and account for about 1% of total PJIs. Our aim was to present clinical and microbiological results in treating these patients with a two-stage approach and antifungal spacers. We retrospectively reviewed our institutional database and identified 26 patients with positive fungal cultures and positive Musculoskeletal Infection Society (MSIS) criteria for PJI who were treated between 2009 and 2017. We identified 18 patients with total hip arthroplasty (THA) and eight patients with total knee arthroplasty (TKA). The surgical and antifungal treatment, clinical and demographic patient data, complications, relapses, and survival were recorded and analyzed.Aims
Patients and Methods