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 algorithms were based on the freely available GatorTron model, a LLM trained on over 82 billion words of de-identified clinical text. Two inference tasks were performed: assessment after model-fine tuning (50 Epochs and three cycles of k-fold cross validation), and external validation. Results. For THA, there were 5,558 patient radiology reports included, of which 4,137 were used for model training and testing, and 1,421 for external validation. Following training, model performance demonstrated average (mean across three folds) accuracy, F1 score, and area under the receiver operating curve (AUROC) values of 0.850 (95% confidence interval (CI) 0.833 to 0.867), 0.813 (95% CI 0.785 to 0.841), and 0.847 (95% CI 0.822 to 0.872), respectively. For TKA, 7,457 patient radiology reports were included, with 3,478 used for model training and testing, and 3,152 for external validation. Performance metrics included accuracy, F1 score, and AUROC values of 0.757 (95% CI 0.702 to 0.811), 0.543 (95% CI 0.479 to 0.607), and 0.717 (95% CI 0.657 to 0.778) respectively. There was a notable deterioration in performance on external validation in both cohorts. Conclusion. The use of routinely available preoperative radiology reports provides promising potential to help screen suitable candidates for THA, but not for TKA. The external validation results demonstrate the importance of further model testing and training when confronted with new clinical cohorts. Cite this article: Bone Joint J 2024;106-B(7):688–695

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 algorithms reported an accuracy > 90%, using 550 to 320,000 training radiographs. AI prediction of dislocation risk post-THA, determined after five-year follow-up, was satisfactory (AUC 76.67; 8,500 training radiographs). Diagnosis of hip implant loosening was good (accuracy 88.3%; 420 training radiographs) and measurement of postoperative acetabular angles was comparable to humans (mean absolute difference 1.35° to 1.39°). However, 11 of the 12 studies had several methodological limitations introducing a high risk of bias. None of the studies were externally validated. Conclusion. These studies show that AI is promising. While it already has the ability to analyze images with significant precision, there is currently insufficient high-level evidence to support its widespread clinical use. Further research to design robust studies that follow standard reporting guidelines should be encouraged to develop AI models that could be easily translated into real-world conditions. Cite this article: Bone Joint J 2022;104-B(8):929–937

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 algorithm, were modified until consensus was achieved. We tested the patient-reported questionnaire on seven patients in orthopaedic clinics using a ‘think-aloud’ process to capture difficulties with its completion. Results. A patient-reported 13-item questionnaire was developed covering pain, mobility, and activity. The radiology report included up to ten items (e.g. progressive periprosthetic bone loss) depending on the type of arthroplasty. The algorithm concludes in one of three outcomes: review at surgeon’s discretion (three to 12 months); see at next available clinic; or long-term follow-up/discharge. Conclusion. The virtual clinic approach with attendant documents achieved consensus by orthopaedic experts, radiologists, and patients. The robust development and testing of this standardized virtual clinic provided a sound platform for organizations in the United Kingdom to adopt a virtual clinic approach for follow-up of hip and knee arthroplasty patients. Cite this article: Bone Joint J 2019;101-B:951–959

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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.

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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).

Aims. The aim of this study was to identify the incidence of positive cultures during the second stage of a two-stage revision arthroplasty and to analyse the association between positive cultures and an infection-free outcome. Patients and Methods. This single-centre retrospective review of prospectively collected data included patients with a periprosthetic joint infection (PJI) of either the hip or the knee between 2013 and 2015, who were treated using a standardised diagnostic and therapeutic algorithm with two-stage exchange. Failure of treatment was assessed according to a definition determined by a Delphi-based consensus. Logistic regression analysis was performed to assess the predictors of positive culture and risk factors for failure. The mean follow-up was 33 months (24 to 48). Results. A total of 163 two-stage revision arthroplasties involving 84 total hip arthroplasties (THAs) and 79 total knee arthroplasties (TKAs) were reviewed. In 27 patients (16.6%), ≥ 1 positive culture was identified at re-implantation and eight (29.6%) of these subsequently failed compared with 20 (14.7%) patients who were culture-negative. The same initially infecting organism was isolated at re-implantation in nine of 27 patients (33.3%). The organism causing re-infection in none of the patients was the same as that isolated at re-implantation. The risk of the failure of treatment was significantly higher in patients with a positive culture (odds ratio (OR) 1.7; 95% confidence interval (CI) 1.0 to 3.0; p = 0.049) and in patients with a higher Charlson Comorbidity Index (OR 1.5; 95% CI 1.6 to 1.8; p = 0.001). Conclusion. Positive culture at re-implantation was independently associated with subsequent failure. Surgeons need to be aware of this association and should consider the medical optimisation of patients with severe comorbidities both before and during treatment. Cite this article: Bone Joint J 2017;99-B:1490–5

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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.

During the last ten years, greater attention has been given to the management of peri-operative blood loss after total knee arthroplasty (TKA), as it is a modifiable outcome that has a significant effect on the rate of complications, the recovery, and the economic burden. Blood loss after TKA has been greatly reduced during this time, thereby dramatically reducing the rates of allogeneic transfusion. This has significantly reduced the complications associated with transfusion, such as fluid overload, infection, and increased length of stay. . The greatest advent in lowering peri-operative blood loss after TKA has been the introduction of tranexamic acid, which reduces blood loss without increasing the risk of thromboembolic events. . This paper discusses the ways of reducing blood loss after TKA, for which a multimodal algorithm, with pre-, intra- and post-operative measures, has been adopted at our institution. Cite this article: Bone Joint J 2016;98-B(1 Suppl A):98–100

Aims . Recently, several synovial biomarkers have been introduced into the algorithm for the diagnosis of a prosthetic joint infection (PJI). Alpha defensin is a promising biomarker, with a high sensitivity and specificity, but it is expensive. Calprotectin is a protein that is present in the cytoplasm of neutrophils, is released upon neutrophil activation and exhibits anti-microbial activity. Our aim, in this study, was to determine the diagnostic potential of synovial calprotectin in the diagnosis of a PJI. Patients and Methods. In this pilot study, we prospectively collected synovial fluid from the hip, knee, shoulder and elbow of 19 patients with a proven PJI and from a control group of 42 patients who underwent revision surgery without a PJI. PJI was diagnosed according to the current diagnostic criteria of the Musculoskeletal Infection Society. Synovial fluid was centrifuged and the supernatant was used to measure the level of calprotectin after applying a lateral flow immunoassay. . Results. The median synovial calprotectin level was 991 mg/L (interquartile range (IQR) 154 to 1787) in those with a PJI and 11 mg/L (IQR 3 to 29) in the control group (p < 0.0001). Using a cut-off value of 50 mg/L, this level showed an excellent diagnostic accuracy, with an area under the curve of 0.94. The overall sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) was 89%, 90%, 81% and 95% respectively. The NPV was 97% in the nine patients with a chronic PJI. . Conclusion . Synovial calprotectin may be a valuable biomarker in the diagnosis of a PJI, especially in the exclusion of an infection. With a lateral flow immunoassay, a relatively rapid quantitative diagnosis can be made. The measurement is cheap and is easy to use. . Cite this article: Bone Joint J 2017;99-B:660–5

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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.

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To determine the trajectories of patient reported pain and functional disability over five years following total hip arthroplasty (THA) or total knee arthroplasty (TKA).

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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.

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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.

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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.

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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.

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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).

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To evaluate the effectiveness of an institutionally developed algorithm for evaluation and diagnosis of prosthetic joint injection and to determine the impact of this protocol on overall hospital re-admissions.p

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The aims of this study were to determine the indications and frequency of ordering a CT pulmonary angiography (CTPA) following primary arthroplasty of the hip and knee, and to determine the number of positive scans in these patients, the location of emboli and the outcome for patients undergoing CTPA.

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To investigate the outcomes of treatment of streptococcal periprosthetic joint infection (PJI) involving total knee and hip arthroplasties.

Fungal peri-prosthetic infections of the knee and hip are rare but likely to result in devastating complications. In this study we evaluated the results of their management using a single-stage exchange technique. Between 2001 and 2011, 14 patients (ten hips, four knees) were treated for a peri-prosthetic fungal infection. One patient was excluded because revision surgery was not possible owing to a large acetabular defect. One patient developed a further infection two months post-operatively and was excluded from the analysis. Two patients died of unrelated causes.

After a mean of seven years (3 to 11) a total of ten patients were available for follow-up. One patient, undergoing revision replacement of the hip, had a post-operative dislocation. Another patient, undergoing revision replacement of the knee, developed a wound infection and required revision 29 months post-operatively following a peri-prosthetic femoral fracture.

The mean Harris hip score increased to 74 points (63 to 84; p < 0.02) in those undergoing revision replacement of the hip, and the mean Hospital for Special Surgery knee score increased to 75 points (70 to 80; p < 0.01) in those undergoing revision replacement of the knee.

A single-stage revision following fungal peri-prosthetic infection is feasible, with an acceptable rate of a satisfactory outcome.

Cite this article: Bone Joint J 2014;96-B:492–6.