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. Methods. We retrospectively collected data from 226 patients (90 hips, 136 knees) with periprosthetic joint infection who underwent two-stage revision between August 2011 and September 2021, with a minimum follow-up of one year. Histology was assessed via the SLIM classification. First, we analyzed whether patients with positive permanent sections at reimplantation had higher reinfection rates than patients with negative histology. Further, we compared permanent and frozen section results, and assessed the influence of anatomical regions (knee versus hip), low- versus high-grade infections, as well as first revision versus multiple prior revisions on the histological result at reimplantation. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), chi-squared tests, and Kaplan-Meier estimates were calculated. Results. Overall, the reinfection rate was 18%. A total of 14 out of 82 patients (17%) with positive permanent sections at reimplantation experienced reinfection, compared to 26 of 144 patients (18%) with negative results (p = 0.996). Neither permanent sections nor fresh frozen sections were significantly associated with reinfection, with a sensitivity of 0.35, specificity of 0.63, PPV of 0.17, NPV of 0.81, and accuracy of 58%. Histology was not significantly associated with reinfection or survival time for any of the analyzed sub-groups. Permanent and frozen section results were in agreement for 91% of cases. Conclusion. Permanent and fresh frozen sections at reimplantation in two-stage revision do not serve as a reliable predictor for reinfection. Cite this article: Bone Joint J 2024;106-B(4):372–379

Aims. 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. Methods. 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). Results. Predictive performance of the best models per outcome ranged from 0.71 for HOOS-PS to 0.84 for EQ-VAS (HA sample). ML statistically significantly outperformed LR and pre-surgery PROM scores in two out of six cases. Conclusion. MCIDs can be predicted with reasonable performance. ML was able to outperform traditional methods, although only in a minority of cases. Cite this article: Bone Joint Res 2023;12(9):512–521

Aims. The efficacy and safety of intrawound vancomycin for preventing surgical site infection in primary hip and knee arthroplasty is uncertain. Methods. A systematic review of the literature was conducted, indexed from inception to March 2020 in PubMed, Web of Science, Cochrane Library, Embase, and Google Scholar databases. All studies evaluating the efficacy and/or safety of intrawound vancomycin in patients who underwent primary hip and knee arthroplasty were included. Incidence of periprosthetic joint infection (PJI), superficial infection, aseptic wound complications, acute kidney injury, anaphylactic reaction, and ototoxicity were meta-analyzed. Results were reported as odds ratios (ORs) and 95% confidence intervals (CIs). The quality of included studies was assessed using the risk of bias in non-randomized studies of interventions (ROBINS-I) assessment tool. Results. Nine studies involving 4,607 patients were included. Intrawound vancomycin was associated with lower incidence of PJI (30 patients (1.20%) vs 58 control patients (2.75%); OR 0.44, 95% CI 0.28 to 0.69) and simultaneous acute kidney injury (four patients (0.28%) vs four control patients (0.35%), OR 0.71, 95% CI 0.19 to 2.55). However, it did not reduce risk of superficial infection (four patients (0.67%) vs six control patients (1.60%), OR 0.60, 95% CI 0.17 to 2.12) and was associated with higher incidence of aseptic wound complications (23 patients (2.15%) vs eight in control patients (0.96%), OR 2.39, 95% CI 1.09 to 5.23). Four studies reported no anaphylactic reactions and three studies reported no ototoxicity in any patient group. Conclusion. The current literature suggests that intrawound vancomycin used in primary hip and knee arthroplasty may reduce incidence of PJI, but it may also increase risk of aseptic wound complications. Cite this article: Bone Joint Res 2020;9(11):778–788

Aims. To estimate the measurement properties for the Oxford Knee Score (OKS) in patients undergoing revision knee arthroplasty (responsiveness, minimal detectable change (MDC-90), minimal important change (MIC), minimal important difference (MID), internal consistency, construct validity, and interpretability). Methods. Secondary data analysis was performed for 10,727 patients undergoing revision knee arthroplasty between 2013 to 2019 using a UK national patient-reported outcome measure (PROM) dataset. Outcome data were collected before revision and at six months postoperatively, using the OKS and EuroQol five-dimension score (EQ-5D). Measurement properties were assessed according to COnsensus-based Standards for the selection of health status Measurement Instruments (COSMIN) guidelines. Results. A total of 9,219 patients had complete outcome data. Mean preoperative OKS was 16.7 points (SD 8.1), mean postoperative OKS 29.1 (SD 11.4), and mean change in OKS + 12.5 (SD 10.7). Median preoperative EQ-5D index was 0.260 (interquartile range (IQR) 0.055 to 0.691), median postoperative EQ-5D index 0.691 (IQR 0.516 to 0.796), and median change in EQ-5D index + 0.240 (IQR 0.000 to 0.567). Internal consistency was good with Cronbach’s α 0.88 (baseline) and 0.94 (post-revision). Construct validity found a high correlation of OKS total score with EQ-5D index (r = 0.76 (baseline), r = 0.83 (post-revision), p < 0.001). The OKS was responsive with standardized effect size (SES) 1.54 (95% confidence interval (CI) 1.51 to 1.57), compared to SES 0.83 (0.81 to 0.86) for the EQ-5D index. The MIC for the OKS was 7.5 points (95% CI 5.5 to 8.5) based on the optimal cut-off with specificity 0.72, sensitivity 0.60, and area under the curve 0.66. The MID for the OKS was 5.2 points. The MDC-90 was 3.9 points. The OKS did not demonstrate significant floor or ceiling effects. Conclusion. This study found that the OKS was a useful and valid instrument for assessment of outcome following revision knee arthroplasty. The OKS was responsive to change and demonstrated good measurement properties. Cite this article: Bone Joint J 2021;103-B(4):627–634

Aims. The aim of this meta-analysis was to determine the pooled incidence of postoperative urinary retention (POUR) following total hip and knee arthroplasty (total joint replacement (TJR)) and to evaluate the risk factors and complications associated with POUR. Methods. Two authors conducted searches in PubMed, Embase, Web of Science, and Scopus on TJR and urinary retention. Eligible studies that reported the rate of POUR and associated risk factors for patients undergoing TJR were included in the analysis. Patient demographic details, medical comorbidities, and postoperative outcomes and complications were separately analyzed. The effect estimates for continuous and categorical data were reported as standardized mean differences (SMDs) and odds ratios (ORs) with 95% CIs, respectively. Results. A total of 31 studies were included in the systematic review. Of these, 29 studies entered our meta-analysis, which included 3,273 patients diagnosed with POUR and 11,583 patients without POUR following TJR. The pooled incidence of POUR was 28.06%. Demographic risk factors included male sex (OR 1.81, 95% CI 1.26 to 2.59), increasing age (SMD 0.16, 95% CI 0.04 to 0.27), and American Society of Anesthesiologists grade 3 to 4 (OR 1.39, 95% CI 1.10 to 1.77). Patients with a history of benign prostatic hyperplasia (OR 1.99, 95% CI 1.41 to 2.83) and retention (OR 3.10, 95% CI 1.58 to 6.06) were more likely to develop POUR. Surgery-related risk factors included spinal anaesthesia (OR 1.44, 95% CI 1.19 to 1.74) and postoperative epidural analgesia (OR 2.82, 95% CI 1.65 to 4.82). Total hip arthroplasty was associated with higher odds of POUR compared to total knee arthroplasty (OR 1.10, 95% CI 1.02 to 1.20). Postoperatively, POUR was associated with a longer length of stay (SMD 0.21, 95% CI 0.02 to 0.39). Conclusion. Our meta-analysis demonstrated key risk variables for POUR following TJR, which may assist in identifying at-risk patients and direct patient-centered pathways to minimize this postoperative complication. Cite this article: Bone Jt Open 2024;5(7):601–611

Aims. While internet search engines have been the primary information source for patients’ questions, artificial intelligence large language models like ChatGPT are trending towards becoming the new primary source. The purpose of this study was to determine if ChatGPT can answer patient questions about total hip (THA) and knee arthroplasty (TKA) with consistent accuracy, comprehensiveness, and easy readability. Methods. We posed the 20 most Google-searched questions about THA and TKA, plus ten additional postoperative questions, to ChatGPT. Each question was asked twice to evaluate for consistency in quality. Following each response, we responded with, “Please explain so it is easier to understand,” to evaluate ChatGPT’s ability to reduce response reading grade level, measured as Flesch-Kincaid Grade Level (FKGL). Five resident physicians rated the 120 responses on 1 to 5 accuracy and comprehensiveness scales. Additionally, they answered a “yes” or “no” question regarding acceptability. Mean scores were calculated for each question, and responses were deemed acceptable if ≥ four raters answered “yes.”. Results. The mean accuracy and comprehensiveness scores were 4.26 (95% confidence interval (CI) 4.19 to 4.33) and 3.79 (95% CI 3.69 to 3.89), respectively. Out of all the responses, 59.2% (71/120; 95% CI 50.0% to 67.7%) were acceptable. ChatGPT was consistent when asked the same question twice, giving no significant difference in accuracy (t = 0.821; p = 0.415), comprehensiveness (t = 1.387; p = 0.171), acceptability (χ. 2. = 1.832; p = 0.176), and FKGL (t = 0.264; p = 0.793). There was a significantly lower FKGL (t = 2.204; p = 0.029) for easier responses (11.14; 95% CI 10.57 to 11.71) than original responses (12.15; 95% CI 11.45 to 12.85). Conclusion. ChatGPT answered THA and TKA patient questions with accuracy comparable to previous reports of websites, with adequate comprehensiveness, but with limited acceptability as the sole information source. ChatGPT has potential for answering patient questions about THA and TKA, but needs improvement. Cite this article: Bone Jt Open 2024;5(2):139–146

Aims. Hereditary haemochromatosis is a genetic disorder that is caused by several known mutations in the human homeostatic iron regulator protein (HFE) gene. Abnormal accumulation of iron causes a joint disease that resembles osteoarthritis (OA), but appears at a relatively younger age and is accompanied by cirrhosis, diabetes, and injury to other organs. Increased serum transferrin saturation and ferritin levels are known markers of haemochromatosis with high positive predictive values. Methods. We have retrospectively analyzed the iron studies of a cohort of 2,035 patients undergoing knee joint arthroplasty due to OA. Results. No patients had HFE gene C282Y, S65C, or H63D mutations testing. In total, 18 patients (2.96%) of the male cohort and 51 (3.58%) of the female cohort had pathologically increased ferritin levels that may be indicative of haemochromatosis. Seven patients (0.34%) had serum transferrin saturation above 45%. Conclusion. The awareness for the diagnosis of this disorder in Orthopaedics is low and needs improvement. Osteoarthritic patients undergoing knee arthroplasty should be routinely screened for haemochromatosis by iron studies and referred to genetic testing when needed. Level of evidence: Level III - Retrospective cohort study. Cite this article: Bone Jt Open 2021;2(12):1062–1066

Aims. Elective orthopaedic services have had to adapt to significant system-wide pressures since the emergence of COVID-19 in December 2019. Length of stay is often recognized as a key marker of quality of care in patients undergoing arthroplasty. Expeditious discharge is key in establishing early rehabilitation and in reducing infection risk, both procedure-related and from COVID-19. The primary aim was to determine the effects of the COVID-19 pandemic length of stay following hip and knee arthroplasty at a high-volume, elective orthopaedic centre. Methods. A retrospective cohort study was performed. Patients undergoing primary or revision hip or knee arthroplasty over a six-month period, from 1 July to 31 December 2020, were compared to the same period in 2019 before the COVID-19 pandemic. Demographic data, American Society of Anesthesiologists (ASA) grade, wait to surgery, COVID-19 status, and length of hospital stay were recorded. Results. A total of 1,311 patients underwent hip or knee arthroplasty in the six-month period following recommencement of elective services in 2020 compared to 1,527 patients the year before. Waiting time to surgery increased in post-COVID-19 group (137 days vs 78; p < 0.001). Length of stay also significantly increased (0.49 days; p < 0.001) despite no difference in age or ASA grade. There were no cases of postoperative COVID-19 infection. Conclusion. Time to surgery and length of hospital stay were significantly higher following recommencement of elective orthopaedic services in the latter part of 2020 in comparison to a similar patient cohort from the year before. Longer waiting times may have contributed to the clinical and radiological deterioration of arthritis and general musculoskeletal conditioning, which may in turn have affected immediate postoperative rehabilitation and mobilization, as well as increasing hospital stay. Cite this article: Bone Jt Open 2021;2(8):655–660

Aims. To develop and validate patient-centred algorithms that estimate individual risk of death over the first year after elective joint arthroplasty surgery for osteoarthritis. Methods. A total of 763,213 hip and knee joint arthroplasty episodes recorded in the National Joint Registry for England and Wales (NJR) and 105,407 episodes from the Norwegian Arthroplasty Register were used to model individual mortality risk over the first year after surgery using flexible parametric survival regression. Results. The one-year mortality rates in the NJR were 10.8 and 8.9 per 1,000 patient-years after hip and knee arthroplasty, respectively. The Norwegian mortality rates were 9.1 and 6.0 per 1,000 patient-years, respectively. The strongest predictors of death in the final models were age, sex, body mass index, and American Society of Anesthesiologists grade. Exposure variables related to the intervention, with the exception of knee arthroplasty type, did not add discrimination over patient factors alone. Discrimination was good in both cohorts, with c-indices above 0.76 for the hip and above 0.70 for the knee. Time-dependent Brier scores indicated appropriate estimation of the mortality rate (≤ 0.01, all models). Conclusion. Simple demographic and clinical information may be used to calculate an individualized estimation for one-year mortality risk after hip or knee arthroplasty (. https://jointcalc.shef.ac.uk. ). These models may be used to provide patients with an estimate of the risk of mortality after joint arthroplasty. Cite this article: Bone Joint Res 2020;9(11):808–820

Aims. The purpose of this study was to develop a personalized outcome prediction tool, to be used with knee arthroplasty patients, that predicts outcomes (lengths of stay (LOS), 90 day readmission, and one-year patient-reported outcome measures (PROMs) on an individual basis and allows for dynamic modifiable risk factors. Methods. Data were prospectively collected on all patients who underwent total or unicompartmental knee arthroplasty at a between July 2015 and June 2018. Cohort 1 (n = 5,958) was utilized to develop models for LOS and 90 day readmission. Cohort 2 (n = 2,391, surgery date 2015 to 2017) was utilized to develop models for one-year improvements in Knee Injury and Osteoarthritis Outcome Score (KOOS) pain score, KOOS function score, and KOOS quality of life (QOL) score. Model accuracies within the imputed data set were assessed through cross-validation with root mean square errors (RMSEs) and mean absolute errors (MAEs) for the LOS and PROMs models, and the index of prediction accuracy (IPA), and area under the curve (AUC) for the readmission models. Model accuracies in new patient data sets were assessed with AUC. Results. Within the imputed datasets, the LOS (RMSE 1.161) and PROMs models (RMSE 15.775, 11.056, 21.680 for KOOS pain, function, and QOL, respectively) demonstrated good accuracy. For all models, the accuracy of predicting outcomes in a new set of patients were consistent with the cross-validation accuracy overall. Upon validation with a new patient dataset, the LOS and readmission models demonstrated high accuracy (71.5% and 65.0%, respectively). Similarly, the one-year PROMs improvement models demonstrated high accuracy in predicting ten-point improvements in KOOS pain (72.1%), function (72.9%), and QOL (70.8%) scores. Conclusion. The data-driven models developed in this study offer scalable predictive tools that can accurately estimate the likelihood of improved pain, function, and quality of life one year after knee arthroplasty as well as LOS and 90 day readmission. Cite this article: Bone Joint J 2020;102-B(9):1183–1193

Aims. Recent studies have suggested that corticosteroid injections into the knee may harm the joint resulting in cartilage loss and possibly accelerating the progression of osteoarthritis (OA). The aim of this study was to assess whether patients with, or at risk of developing, symptomatic osteoarthritis of the knee who receive intra-articular corticosteroid injections have an increased risk of requiring arthroplasty. Methods. We used data from the Osteoarthritis Initiative (OAI), a multicentre observational cohort study that followed 4,796 patients with, or at risk of developing, osteoarthritis of the knee on an annual basis with follow-up available up to nine years. Increased risk for symptomatic OA was defined as frequent knee symptoms (pain, aching, or stiffness) without radiological evidence of OA and two or more risk factors, while OA was defined by the presence of both femoral osteophytes and frequent symptoms in one or both knees. Missing data were imputed with multiple imputations using chained equations. Time-dependent propensity score matching was performed to match patients at the time of receving their first injection with controls. The effect of corticosteroid injections on the rate of subsequent (total and partial) knee arthroplasty was estimated using Cox proportional-hazards survival analyses. Results. After removing patients lost to follow-up, 3,822 patients remained in the study. A total of 249 (31.3%) of the 796 patients who received corticosteroid injections, and 152 (5.0%) of the 3,026 who did not, had knee arthroplasty. In the matched cohort, Cox proportional-hazards regression resulted in a hazard ratio of 1.57 (95% confidence interval (CI) 1.37 to 1.81; p < 0.001) and each injection increased the absolute risk of arthroplasty by 9.4% at nine years’ follow-up compared with those who did not receive injections. Conclusion. Corticosteroid injections seem to be associated with an increased risk of knee arthroplasty in patients with, or at risk of developing, symptomatic OA of the knee. These findings suggest that a conservative approach regarding the treatment of these patients with corticosteroid injections should be recommended. Cite this article: Bone Joint J 2020;102-B(5):586–592

Aims. The primary aim was to assess whether preoperative health-related quality of life (HRQoL) was associated with postoperative mortality following total hip arthroplasty (THA) and knee arthroplasty (KA). Secondary aims were to assess whether patient demographics/comorbidities and/or joint-specific function were associated with postoperative mortality. Methods. Patients undergoing THA (n = 717) and KA (n = 742) during a one-year period were identified retrospectively from an arthroplasty register. Patient demographics, comorbidities, Oxford score, and EuroQol five-dimension (EQ-5D) were recorded preoperatively. Patients were followed up for a minimum of seven years and their mortality status was obtained. Cox regression analysis was used to adjust for confounding. Results. During the study period, 111 patients (15.5%) undergoing THA and 135 patients (18.2%) undergoing KA had died at a mean follow-up of 7.5 years (7 to 8). When adjusting for confounding, the preoperative EQ-5D was associated with postoperative mortality, and for each 0.1 difference in the utility there was an associated change in mortality risk of 6.7% (p = 0.048) after THA, and 6.8% (p = 0.047) after KA. Comorbidities of connective tissue disease (p ≤ 0.026) and diabetes (p ≤ 0.028) were associated with mortality after THA, whereas MI (p ≤ 0.041), diabetes (p ≤ 0.009), and pain in other joints (p ≤ 0.050) were associated with mortality following KA. The preoperative Oxford score was associated with mortality, and for each one-point change in the score there was an associated change in mortality risk of 2.7% (p = 0.025) after THA and 4.3% (p = 0.003) after KA. Conclusion. Worse preoperative HRQoL and joint specific function were associated with an increased risk of postoperative mortality. Both HRQoL and joint-specific function decline with longer waiting times to surgery for THA and KA and therefore may result in an increased postoperative mortality risk than would have been expected if surgery had been undertaken earlier. Cite this article: Bone Jt Open 2022;3(12):933–940

Aims. The aims were to assess whether preoperative joint-specific function (JSF) and health-related quality of life (HRQoL) were associated with level of clinical frailty in patients waiting for a primary total hip arthroplasty (THA) or knee arthroplasty (KA). Methods. Patients waiting for a THA (n = 100) or KA (n = 100) for more than six months were prospectively recruited from the study centre. Overall,162 patients responded to the questionnaire (81 THA; 81 KA). Patient demographics, Oxford score, EuroQol five-dimension (EQ-5D) score, EuroQol visual analogue score (EQ-VAS), Rockwood Clinical Frailty Score (CFS), and time spent on the waiting list were collected. Results. There was a significant correlation between CFS and the Oxford score (THA r = −0.838; p < 0.001, KA r = −0.867; p < 0.001), EQ-5D index (THA r = −0.663, p =< 0.001; KA r = −0.681; p =< 0.001), and EQ-VAS (THA r = −0.414; p < 0.001, KA r = −0.386; p < 0.001). Confounding variables (demographics and waiting time) where adjusted for using multiple regression analysis. For each 8.5 (THA, 95% CI 7.1 to 10.0; p < 0.001) and 9.9 (KA, 95% CI 8.4 to 11.4; p < 0.001) point change in the Oxford score, there was an associated change in level of the CFS. For each 0.16 (THA, 95% CI 0.10 to 0.22; p < 0.001) and 0.20 (KA, 95% CI 0.12 to 0.27; p < 0.001) utility change in EQ-5D, there was an associated change in level of the CFS. EQ-VAS (THA, B = −11.5; p < 0.001, KA B = −7.9; p = 0.005) was also associated with CFS. Conclusion. JSF and HRQoL in patients awaiting THA or KA for more than six months, were independently associated with level of clinical frailty. With further prospective studies, clinical frailty may prove to be a useful metric to assist in the prioritization of arthroplasty waiting lists. Cite this article: Bone Jt Open 2023;4(4):241–249

Aims. The primary aim was to assess the rate of postoperative COVID-19 following hip and knee arthroplasty performed in March 2020 in the UK. The secondary aims were to assess whether there were clinical factors associated with COVID-19 status, the mortality rate of patients with COVID-19, and the rate of potential COVID-19 in patients not presenting to healthcare services. Methods. A multicentre retrospective study was conducted of patients undergoing hip or knee arthroplasty during the first wave of the COVID-19 pandemic (1 March 2020 to 31 March 2020) with a minimum of 60 days follow-up. Patient demographics, American Society of Anesthesiologists grade, procedure type, primary or revision, length of stay (LOS), COVID-19 test status, and postoperative mortality were recorded. A subgroup of patients (n = 211) who had not presented to healthcare services after discharge were contacted and questioned as to whether they had symptoms of COVID-19. Results. Five (0.5%) of 1,073 patients who underwent hip or knee arthroplasty tested positive for SARS-CoV-2 postoperatively. When adjusting for confounding factors, increasing LOS (p = 0.022) was the only significant factor associated with developing COVID-19 following surgery and a stay greater than three days was a reliable predictor with an area under the curve of 81% (p = 0.018). There were three (0.3%) deaths in the study cohort and the overall mortality rate attributable to COVID-19 was 0.09% (n = 1/1,073), with one (20%) of the five patients with COVID-19 dying postoperatively. Of the 211 patients contacted, two had symptoms within two to 14 days postoperatively with a positive predictive value of 31% and it was therefore estimated that one patient may have had undiagnosed COVID-19. Conclusion. The rate of postoperative COVID-19 was 0.5% and may have been as high as 1% when accounting for those patients not presenting to healthcare services, which was similar to the estimated population prevalence during the study period. The overall mortality rate secondary to COVID-19 was low (0.09%), however the mortality rate for those patients developing COVID-19 was 20%. Cite this article: Bone Joint J 2021;103-B(4):681–688

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. Achievement of accurate microbiological diagnosis prior to revision is key to reducing the high rates of persistent infection after revision knee surgery. The effect of change in the microorganism between the first- and second-stage revision of total knee arthroplasty for periprosthetic joint infection (PJI) on the success of management is not clear. Methods. A two-centre retrospective cohort study was conducted to review the outcome of patients who have undergone two-stage revision for treatment of knee arthroplasty PJI, focusing specifically on isolated micro-organisms at both the first- and second-stage procedure. Patient demographics, medical, and orthopaedic history data, including postoperative outcomes and subsequent treatment, were obtained from the electronic records and medical notes. Results. The study cohort consisted of 84 patients, of whom 59.5% (n = 50) had successful eradication of their infection at a mean follow-up of 4.7 years. For the 34 patients who had recurrence of infection, 58.8% (n = 20) had a change in isolated organism, compared to 18% (n = 9) in the infection eradication group (p < 0.001). When adjusting for confound, there was no association when the growth on the second stage was the same as the first (odd ratio (OR) 2.50, 95% confidence interval (CI) 0.49 to 12.50; p = 0.269); however, when a different organism was identified at the second stage, this was independently associated with failure of treatment (OR 8.40, 95% CI 2.91 to 24.39; p < 0.001). There were no other significant differences between the two cohorts with regard to patient demographics or type of organisms isolated. Conclusion. Change in the identified microorganism between first- and second-stage revision for PJI was associated with failure of management. Identification of this change in the microorganism prior to commencement of the second stage may help target antibiotic management and could improve the success of surgery in these patients. Cite this article: Bone Jt Open 2023;4(9):720–727

Aims. The aim of this study was to determine the long-term risk of undergoing knee arthroplasty in a cohort of patients with meniscal tears who had undergone arthroscopic partial meniscectomy (APM). Patients and Methods. A retrospective national cohort of patients with a history of isolated APM was identified over a 20-year period. Patients with prior surgery to the same knee were excluded. The primary outcome was knee arthroplasty. Hazard ratios (HRs) were adjusted by patient age, sex, year of APM, Charlson comorbidity index, regional deprivation, rurality, and ethnicity. Risk of arthroplasty in the index knee was compared with the patient’s contralateral knee (with vs without a history of APM). A total of 834 393 patients were included (mean age 50 years; 37% female). Results. Of those with at least 15 years of follow-up, 13.49% (16 256/120 493; 95% confidence interval (CI) 13.30 to 13.69) underwent subsequent arthroplasty within this time. In women, 22.07% (95% CI 21.64 to 22.51) underwent arthroplasty within 15 years compared with 9.91% of men (95% CI 9.71 to 10.12), corresponding to a risk ratio (RR) of 2.23 (95% CI 2.16 to 2.29). Relative to the general population, patients with a history of APM were over ten times more likely (RR 10.27; 95% CI 10.07 to 10.47) to undergo arthroplasty rising to almost 40 times more likely (RR 39.62; 95% CI 27.68 to 56.70) at a younger age (30 to 39 years). In patients with a history of APM in only one knee, the risk of arthroplasty in that knee was greatly elevated in comparison with the contralateral knee (no APM; HR 2.99; 95% CI 2.95 to 3.02). Conclusion. Patients developing a meniscal tear undergoing APM are at greater risk of knee arthroplasty than the general population. This risk is three-times greater in the patient’s affected knee than in the contralateral knee. Women in the cohort were at double the risk of progressing to knee arthroplasty compared with men. These important new reference data will inform shared decision making and enhance approaches to treatment, prevention, and clinical surveillance. Cite this article: Bone Joint J 2019;101-B:1071–1080

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 determine the long-term mortality rate, and to identify factors associated with this, following primary and revision knee arthroplasty (KA). Methods. Data from the Scottish Arthroplasty Project (1998 to 2019) were retrospectively analyzed. Patient mortality data were linked from the National Records of Scotland. Analyses were performed separately for the primary and revised KA cohorts. The standardized mortality ratio (SMR) with 95% confidence intervals (CIs) was calculated for the population at risk. Multivariable Cox proportional hazards were used to identify predictors and estimate relative mortality risks. Results. At a median 7.4 years (interquartile range (IQR) 4.0 to 11.6) follow-up, 27.8% of primary (n = 27,474/98,778) and 31.3% of revision (n = 2,611/8,343) KA patients had died. Both primary and revision cohorts had lower mortality rates than the general population (SMR 0.74 (95% CI 0.73 to 0.74); p < 0.001; SMR 0.83 (95% CI 0.80 to 0.86); p < 0.001, respectively), which persisted for 12 and eighteight years after surgery, respectively. Factors associated with increased risk of mortality after primary KA included male sex (hazard ratio (HR) 1.40 (95% CI 1.36 to 1.45)), increasing socioeconomic deprivation (HR 1.43 (95% CI 1.36 to 1.50)), inflammatory polyarthropathy (HR 1.79 (95% CI 1.68 to 1.90)), greater number of comorbidities (HR 1.59 (95% CI 1.51 to 1.68)), and periprosthetic joint infection (PJI) requiring revision (HR 1.92 (95% CI 1.57 to 2.36)) when adjusting for age. Similarly, male sex (HR 1.36 (95% CI 1.24 to 1.49)), increasing socioeconomic deprivation (HR 1.31 (95% CI 1.12 to 1.52)), inflammatory polyarthropathy (HR 1.24 (95% CI 1.12 to 1.37)), greater number of comorbidities (HR 1.64 (95% CI 1.33 to 2.01)), and revision for PJI (HR 1.35 (95% 1.18 to 1.55)) were independently associated with an increased risk of mortality following revision KA when adjusting for age. Conclusion. The SMR of patients undergoing primary and revision KA was lower than that of the general population and remained so for several years post-surgery. However, approximately one in four patients undergoing primary and one in three patients undergoing revision KA died within tenten years of surgery. Several patient and surgical factors, including PJI, were associated with the risk of mortality within ten years of primary and revision surgery. Cite this article: Bone Joint J 2022;104-B(1):45–52

Aims. The aim of this study was to compare any differences in the primary outcome (biphasic flexion knee moment during gait) of robotic arm-assisted bi-unicompartmental knee arthroplasty (bi-UKA) with conventional mechanically aligned total knee arthroplasty (TKA) at one year post-surgery. Methods. A total of 76 patients (34 bi-UKA and 42 TKA patients) were analyzed in a prospective, single-centre, randomized controlled trial. Flat ground shod gait analysis was performed preoperatively and one year postoperatively. Knee flexion moment was calculated from motion capture markers and force plates. The same setup determined proprioception outcomes during a joint position sense test and one-leg standing. Surgery allocation, surgeon, and secondary outcomes were analyzed for prediction of the primary outcome from a binary regression model. Results. Both interventions were shown to be effective treatment options, with no significant differences shown between interventions for the primary outcome of this study (18/35 (51.4%) biphasic TKA patients vs 20/31 (64.5%) biphasic bi-UKA patients; p = 0.558). All outcomes were compared to an age-matched, healthy cohort that outperformed both groups, indicating residual deficits exists following surgery. Logistic regression analysis of primary outcome with secondary outcomes indicated that the most significant predictor of postoperative biphasic knee moments was preoperative knee moment profile and trochlear degradation (Outerbridge) (R. 2. = 0.381; p = 0.002, p = 0.046). A separate regression of alignment against primary outcome indicated significant bi-UKA femoral and tibial axial alignment (R. 2. = 0.352; p = 0.029), and TKA femoral sagittal alignment (R. 2. = 0.252; p = 0.016). The bi-UKA group showed a significant increased ability in the proprioceptive joint position test, but no difference was found in more dynamic testing of proprioception. Conclusion. Robotic arm-assisted bi-UKA demonstrated equivalence to TKA in achieving a biphasic gait pattern after surgery for osteoarthritis of the knee. Both treatments are successful at improving gait, but both leave the patients with a functional limitation that is not present in healthy age-matched controls. Cite this article: Bone Joint J 2022;103-B(4):433–443