Aims. Recent improvements in surgical technique and perioperative blood management after total joint replacement (TJR) have decreased rates of transfusion. However, as many surgeons transition to outpatient TJR, obtaining routine postoperative blood tests becomes more challenging. Therefore, we sought to determine if a preoperative outpatient assessment tool that stratifies patients based on numerous medical comorbidities could predict who required postoperative haemoglobin (Hb) measurement. Methods. We performed a prospective study of consecutive unilateral primary total knee arthroplasties (TKAs) and total hip arthroplasties (THAs) performed at a single institution. Prospectively collected data included preoperative and postoperative Hb levels, need for blood transfusion, length of hospital stay, and Outpatient Arthroplasty Risk Assessment (OARA) score. Results. A total of 504 patients met inclusion criteria. Mean age at time of arthroplasty was 65.3 years (SD 10.2). Of the patients, 216 (42.9%) were THAs and 288 (57.1%) were TKAs. Six patients required a blood transfusion postoperatively (1.19%). Transfusion after surgery was associated with lower postoperative day 1 Hb (median of 8.5 (interquartile range (IQR) 7.9 to 8.6) vs 11.3 (IQR 10.4 to 12.2); p < 0.001), longer length of stay (1 day (IQR 1 to 1) vs 2 days (IQR 2 to 3); p < 0.001), higher OARA score (median of 60.0 (IQR 40 to 75) vs 5.0 (IQR 0-35); p = 0.001), and total hip arthroplasty (p < 0.001). All patients who received a transfusion had an OARA score > 34; however, this did not reach statistical significance as a screening threshold. Conclusion. Risk of blood transfusion after primary TJR was uncommon in our series, with an incidence of 1.19%. Transfusion was associated with OARA scores > 60. The OARA score, not American Society of Anesthesiologists grade, reliably identified patients at risk for postoperative blood transfusion. Selective Hb monitoring may result in substantial cost savings in the era of cost containment. Cite this article: Bone Joint J 2021;103-B(1):65–70

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. The primary aim was to assess change in health-related quality of life (HRQoL) of patients as they waited from six to 12 months for a total hip (THA) or total or partial knee arthroplasty (KA). Secondary aims were to assess change in joint-specific function, mental health, quality of sleep, number living in a state worse than death (WTD), wellbeing, and patient satisfaction with their healthcare. Methods. This prospective study included 142 patients awaiting a THA (mean age 66.7 years (SD 11.4); 71 female) and 214 patients awaiting KA (mean age 69.7 years (SD 8.7); 117 female). Patients completed questionnaires (EuroQol five-dimension health questionnaire (EQ-5D), Oxford Hip and Knee Scores (OHS/OKS), Pittsburgh Sleep Quality Index (PSQI), Hospital Anxiety and Depression Score (HADS), University of California, Los Angeles Activity Scale, wellbeing assessment, and satisfaction with their healthcare) at six and 12 months while awaiting surgery. Results. There was a clinical and statistically significant deterioration in the EQ-5D while awaiting THA (mean change 0.071 (95% confidence interval (CI) 0.018 to 0.124); p = 0.009) and KA (mean change 0.069 (95% CI 0.032 to 0.106); p < 0.001). For patients awaiting a THA, there were deteriorations in OHS (p = 0.003), PSQI (p = 0.008), both HADS depression (p = 0.001) and anxiety (p = 0.002), and an increased prevalence in those in a state WTD (p = 0.010). For those awaiting KA, there were significant deteriorations in OKS (p < 0.001), UCLA (p = 0.001), and HADS depression (p < 0.001) and anxiety (p < 0.001). There were significant decreases in wellbeing (satisfaction with life, feeling life to be worthwhile, and happiness) and increases in anxiety for those awaiting THA or KA (p < 0.001). Those awaiting THA (odds ratio (OR) 0.52 (95% CI 0.31 to 0.89); p = 0.016) and KA (OR 0.46 (95% CI 0.31 to 0.71); p < 0.001) had a significant decrease in satisfaction with their healthcare. Conclusion. As patients waited from six to 12 months for THA or KA, they experienced a clinically significant deterioration in HRQoL. There were also deteriorations in joint-specific function, mental health, wellbeing, and patient satisfaction with healthcare. Cite this article: Bone Joint J 2024;106-B(2):166–173

Aims. The diagnosis of periprosthetic joint infection (PJI) can be difficult. All current diagnostic tests have problems with accuracy and interpretation of results. Many new tests have been proposed, but there is no consensus on the place of many of these in the diagnostic pathway. Previous attempts to develop a definition of PJI have not been universally accepted and there remains no reference standard definition. Methods. This paper reports the outcome of a project developed by the European Bone and Joint Infection Society (EBJIS), and supported by the Musculoskeletal Infection Society (MSIS) and the European Society of Clinical Microbiology and Infectious Diseases (ESCMID) Study Group for Implant-Associated Infections (ESGIAI). It comprised a comprehensive review of the literature, open discussion with Society members and conference delegates, and an expert panel assessment of the results to produce the final guidance. Results. This process evolved a three-level approach to the diagnostic continuum, resulting in a definition set and guidance, which has been fully endorsed by EBJIS, MSIS, and ESGIAI. Conclusion. The definition presents a novel three-level approach to diagnosis, based on the most robust evidence, which will be useful to clinicians in daily practice. Cite this article: Bone Joint J 2021;103-B(1):18–25

Aims

The aim of this study was to evaluate the optimal deep tissue specimen sample number for histopathological analysis in the diagnosis of periprosthetic joint infection (PJI).

Aims

The COVID-19 pandemic has disrupted the provision of arthroplasty services in England, Wales, and Northern Ireland. This study aimed to quantify the backlog, analyze national trends, and predict time to recovery.

Aims

Histology is widely used for diagnosis of persistent infection during reimplantation in two-stage revision hip and knee arthroplasty, although data on its utility remain scarce. Therefore, this study aims to assess the predictive value of permanent sections at reimplantation in relation to reinfection risk, and to compare results of permanent and frozen sections.

Aims

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.

Aims

Total femoral arthroplasty (TFA) is a rare procedure used in cases of significant femoral bone loss, commonly from cancer, infection, and trauma. Low patient numbers have resulted in limited published work on long-term outcomes, and even less regarding TFA undertaken for non-oncological indications. The aim of this study was to evaluate the long-term clinical outcomes of all TFAs in our unit.

Aims

The primary aim of this study was to assess whether patients waiting six months or more for a total hip (THA) or knee (KA) arthroplasty had a deterioration in their health-related quality of life (HRQoL). Secondary aims were to assess changes in frailty and the number of patients living in a state considered to be worse than death (WTD), and factors associated with changes in HRQoL and frailty.

Aims

Despite numerous studies focusing on periprosthetic joint infections (PJIs), there are no robust data on the risk factors and timing of metachronous infections. Metachronous PJIs are PJIs that can arise in the same or other artificial joints after a period of time, in patients who have previously had PJI.

Aims

Breast cancer survivors have known risk factors that might influence the results of total hip arthroplasty (THA) or total knee arthroplasty (TKA). This study evaluated clinical outcomes of patients with breast cancer history after primary THA and TKA.

Aims

Our aim was to estimate the total costs of all hospitalizations for treating periprosthetic joint infection (PJI) by main management strategy within 24 months post-diagnosis using activity-based costing. Additionally, we investigated the influence of individual PJI treatment pathways on hospital costs within the first 24 months.

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.

Aims

Periprosthetic joint infections (PJIs) and fracture-related infections (FRIs) are associated with a significant risk of adverse events. However, there is a paucity of data on cardiac complications following revision surgery for PJI and FRI and how they impact overall mortality. Therefore, this study aimed to investigate the risk of perioperative myocardial injury (PMI) and mortality in this patient cohort.

Aims

Routinely collected patient-reported outcome measures (PROMs) have been useful to quantify and quality-assess provision of total hip arthroplasty (THA) and total knee arthroplasty (TKA) in the UK for the past decade. This study aimed to explore whether the outcome following primary THA and TKA had improved over the past seven years.

Aims. The aim of this study was to give estimates of the incidence of component incompatibility in hip and knee arthroplasty and to test the effect of an online, real-time compatibility check. Materials and Methods. Intraoperative barcode registration of arthroplasty implants was introduced in Denmark in 2013. We developed a compatibility database and, from May 2017, real-time compatibility checking was implemented and became part of the registration. We defined four classes of component incompatibility: A-I, A-II, B-I, and B-II, depending on an assessment of the level of risk to the patient (A/B), and on whether incompatibility was knowingly accepted (I/II). Results. A total of 26 524 arthroplasties were analyzed. From 12 307 procedures that were undertaken before implementation of the compatibility check, 21 class A incompatibilities were identified (real- or high-risk combinations; 0.17%; 95% confidence interval (CI) 0.11 to 0.26). From 5692 hip and 6615 knee procedures prior to implementation of the compatibility check, we found rates of class A-I incompatibility (real- or high-risk combinations unknowingly inserted) of 0.14% (95% CI 0.06 to 0.28) and 0.17% (95% CI 0.08 to 0.30), respectively. From 14 217 procedures after the introduction of compatibility checking (7187 hips and 7030 knees), eight class A incompatibilities (0.06%; 95% CI 0.02 to 0.11) were identified. This difference was statistically significant (p = 0.008). Conclusion. Our data presents validated estimates of the baseline incidence of incompatibility events for hip and knee arthroplasty procedures and shows that a significant reduction in class A incompatibility events is possible using a web-based recording system. Cite this article: Bone Joint J 2019;101-B:960–969

Aims

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.

Aims. The diagnosis of periprosthetic joint infection (PJI) remains demanding due to limitations of all the available diagnostic tests. The synovial fluid marker, α-defensin, is a promising adjunct for the assessment of potential PJI. The purpose of this study was to investigate the qualitative assessment of α-defensin, using Synovasure to detect or exclude periprosthetic infection in total joint arthroplasty. Patients and Methods. We studied 50 patients (28 women, 22 men, mean age 65 years; 20 to 89) with a clinical indication for revision arthroplasty who met the inclusion criteria of this prospective diagnostic study. The presence of α-defensin was determined using the qualitative Synovasure test and compared with standard diagnostic methods for PJI. Based on modified Musculoskeletal Infection Society (MSIS) criteria, 13 cases were categorised as septic and 36 as aseptic revisions. One test was inconclusive. Results. The Synovasure test achieved a sensitivity of 69% and a specificity of 94%. The positive and negative likelihood ratios were 12.46 and 0.33, respectively. A good diagnostic accuracy for PJI, with an area under the curve of 0.82, was demonstrated. Adjusted p-values using the method of Hochberg showed that Synovasure is as good at diagnosing PJI as histology (p = 0.0042) and bacteriology with one positive culture (p = 0.0327). Conclusion. With its ease of use and rapid results after approximately ten minutes, Synovasure may be a useful adjunct in the diagnosis of PJI. Cite this article: Bone Joint J 2017;99-B:66–72

Aims

The aim of this study was to determine the diagnostic accuracy of α defensin (AD) lateral flow assay (LFA) and enzyme-linked immunosorbent assay (ELISA) tests for periprosthetic joint infection (PJI) in comparison to conventional synovial white blood cell (WBC) count and polymorphonuclear neutrophil percentage (PMN%) analysis.