Aims. The aim of this study was to determine satisfaction rates after hip and knee arthroplasty in patients who did not respond to postoperative patient-reported outcome measures (PROMs), characteristics of non-responders, and contact preferences to maximize response rates. Methods. A prospective cohort study of patients planned to undergo hip arthroplasty (n = 713) and knee arthroplasty (n = 737) at a UK university teaching hospital who had completed preoperative PROMs questionnaires, including the EuroQol five-dimension health-related quality of life score, and Oxford Hip Score (OHS) and Oxford Knee Score (OKS). Follow-up questionnaires were sent by post at one year, including satisfaction scoring. Attempts were made to contact patients who did not initially respond. Univariate, logistic regression, and receiver operator curve analysis was performed. Results. At one year, 667 hip patients (93.5%) and 685 knee patients (92.9%) had undergone surgery and were alive. No response was received from 151/667 hip patients (22.6%), 83 (55.0%) of whom were ultimately contacted); or from 108/685 knee patients (15.8%), 91 (84.3%) of whom were ultimately contacted. There was no difference in satisfaction after arthroplasty between initial non-responders and responders for hips (74/81 satisfied vs 476/516 satisfied; p = 0.847) or knees (81/93 satisfied vs 470/561 satisfied; p = 0.480). Initial non-response and persistent non-response was associated with younger age, higher BMIs, and worse preoperative PROMs for both hip and knee patients (p < 0.050). Being in employment was associated with persistent non-response for hip patients (p = 0.047). Multivariate analysis demonstrated that younger age (p < 0.038), higher BMI (p = 0.018), and poorer preoperative OHS (p = 0.031) were independently associated with persistent non-response to hip PROMs. No independent associations were identified for knees. Using a threshold of > 66.4 years predicted a preference for contact by post (area under the curve 0.723 (95% confidence interval (CI) 0.647 to 0.799; p < 0.001, though this CI crosses the 0.7 limit considered reliable). Conclusion. The majority of initial non-responders were ultimately contactable with effort. Satisfaction rates were not inferior in patients who did not initially respond to PROMs. Cite this article: Bone Jt Open 2022;3(4):275–283

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. To review the evidence and reach consensus on recommendations for follow-up after total hip and knee arthroplasty. Methods. A programme of work was conducted, including: a systematic review of the clinical and cost-effectiveness literature; analysis of routine national datasets to identify pre-, peri-, and postoperative predictors of mid-to-late term revision; prospective data analyses from 560 patients to understand how patients present for revision surgery; qualitative interviews with NHS managers and orthopaedic surgeons; and health economic modelling. Finally, a consensus meeting considered all the work and agreed the final recommendations and research areas. Results. The UK poSt Arthroplasty Follow-up rEcommendations (UK SAFE) recommendations apply to post-primary hip and knee arthroplasty follow-up. The ten-year time point is based on a lack of robust evidence beyond ten years. The term 'complex cases' refers to individual patient and surgical factors that may increase the risk for arthroplasty failure. For Orthopaedic Data Evaluation Panel (ODEP) 10A* minimum implants, it is safe to disinvest in routine follow-up from one to ten years post-non-complex hip and knee arthroplasty provided there is rapid access to orthopaedic review. For ODEP 10A* minimum implants in complex cases, or non-ODEP 10A* minimum implants, periodic follow-up post-hip and knee arthroplasty may be required from one to ten years. At ten years post-hip and knee arthroplasty, clinical and radiological evaluation is recommended. After ten years post-hip and knee arthroplasty, frequency of further follow-up should be based on the ten-year assessment; ongoing rapid access to orthopaedic review is still required. Conclusion. Complex cases, implants not meeting the ODEP 10A* criteria, and follow-up after revision surgery are not covered by this recommendation. Cite this article: Bone Jt Open 2023;4(2):72–78

Aims. The influence of metabolic syndrome (MetS) on the outcome after hip and knee arthroplasty is debated. We aimed to investigate the change in patient-reported outcome measure (PROM) scores after hip and knee arthroplasty, comparing patients with and without MetS. Methods. From 1 May 2017 to 30 November 2019, a prospective cohort of 2,586 patients undergoing elective unilateral hip and knee arthroplasty was established in Denmark. Data from national registries and a local database were used to determine the presence of MetS. Patients’ scores on Oxford Hip Score (OHS) or Oxford Knee Score (OKS), EuroQol five-dimension five-level questionnaire (EQ-5D-5L), University of California, Los Angeles (UCLA) Activity Scale, and Forgotten Joint Score (FJS) at baseline, three, 12, and 24 months after surgery were collected. Primary outcome was the difference between groups from baseline to 12 months in OHS and OKS. Secondary outcomes were scores of OHS and OKS at three and 24 months and EQ-5D-5L, UCLA Activity Scale, and FJS at three, 12, and 24 months after surgery. Generalized linear mixed model was applied, adjusting for age, sex, Charlson Comorbidity Index, and smoking to present marginal mean and associated 95% CIs. Results. A total of 62.3% (1,611/2,586) of the cohort met the criteria for MetS. Both groups showed similar increase in mean OHS (MetS group 22.5 (95% CI 21.8 to 23.1), non-MetS group 22.1 (21.3 to 22.8); p = 0.477) and mean OKS (MetS group 18.0 (17.4 to 18.6), non-MetS group 17.8 (17.0 to 18.7); p = 0.722) at 12 months' follow-up. Between groups, similar improvements were seen for OHS and OKS at three and 24 months postoperatively and for the mean EQ-5D-5L, EuroQol-visual analogue scale (EQ-VAS), UCLA Activity Scale, and FJS at every timepoint. Conclusion. Patients meeting the criteria for MetS obtain the same improvement in PROM scores as individuals without MetS up to 24 months after hip and knee arthroplasty. This is important for the clinician to take into account when assessing and advising patients with MetS. Cite this article: Bone Joint J 2024;106-B(10):1074–1083

Aims. We investigated the efficacy and safety profile of commonly used venous thromboembolism (VTE) prophylaxis agents following hip and knee arthroplasty. Methods. A systematic search of PubMed, Embase, Cochrane Library, Web of Science, and OrthoSearch was performed. Prophylaxis agents investigated were aspirin (< 325 mg and ≥ 325 mg daily), enoxaparin, dalteparin, fondaparinux, unfractionated heparin, warfarin, rivaroxaban, apixaban, and dabigatran. The primary efficacy outcome of interest was the risk of VTE, whereas the primary safety outcomes of interest were the risk of major bleeding events (MBE) and wound complications (WC). VTE was defined as the confirmed diagnosis of any deep vein thrombosis and/or pulmonary embolism. Network meta-analysis combining direct and indirect evidence was performed. Cluster rank analysis using the surface under cumulative ranking (SUCRA) was applied to compare each intervention group, weighing safety and efficacy outcomes. Results. Of 86 studies eligible studies, cluster rank analysis showed that aspirin < 325 mg daily (SUCRA-VTE 89.3%; SUCRA-MBE 75.3%; SUCRA-WC 71.1%), enoxaparin (SUCRA-VTE 55.7%; SUCRA-MBE 49.8%; SUCRA-WC 45.2%), and dabigatran (SUCRA-VTE 44.9%; SUCRA-MBE 52.0%; SUCRA-WC 41.9%) have an overall satisfactory efficacy and safety profile. Conclusion. We recommend the use of either aspirin < 325 mg daily, enoxaparin, or dabigatran for VTE prophylaxis following hip and knee arthroplasty. Cite this article: Bone Joint J 2024;106-B(9):924–934

Aims. The aim of this study was to evaluate the diagnostic accuracy of the absolute synovial polymorphonuclear neutrophil cell (PMN) count for the diagnosis or exclusion of periprosthetic joint infection (PJI) after total hip (THA) or knee arthroplasty (TKA). Methods. In this retrospective cohort study, 147 consecutive patients with acute or chronic complaints following THA and TKA were included. Diagnosis of PJI was established based on the 2018 International Consensus Meeting criteria. A total of 39 patients diagnosed with PJI (32 chronic and seven acute) and 108 patients with aseptic complications were surgically revised. Results. Using receiver operating characteristic curves and calculating the area under the curve (AUC), an optimal synovial cut-off value of 2,000 PMN/µl was determined (AUC 0.978 (95% confidence interval (CI) 0.946 to 1)). Using this cut-off, sensitivity and specificity of absolute synovial PMN count for PJI were 97.4% (95% CI 91.2 to 100) and 93.5% (95% CI 88.9 to 98.1), respectively. Positive and negative predictive value were 84.4% (95% CI 72.7 to 93.9) and 99.0% (95% CI 96.7 to 100), respectively. Exclusion of 20 patients with acute complications improved specificity to 97.9% (95% CI 94.6 to 100). Different cut-off values for THA (< 3,600 PMN/µl) and TKA (< 2,000 PMN/µl) were identified. Absolute synovial PMN count correlated strongly with synovial alpha-defensin (AD) (r = 0.759; p < 0.001). With a positive AD result, no additional PJI could be identified in any case. Conclusion. Absolute synovial PMN count is a widely available, rapid, cost-effective, and accurate marker in PJI diagnostics, whereas synovial AD appears to be a surrogate parameter of absolute synovial PMN count. Despite limitations in the early postoperative phase, wear, and rheumatic diseases in confirming PJI, an absolute synovial PMN count below 2,000/µl is highly suitable for ruling out PJI, with specific cut-off values for THA and TKA. Cite this article: Bone Joint J 2023;105-B(4):373–381

Aims. Our main aim was to describe the trend in the comorbidities of patients undergoing elective total hip arthroplasties (THAs) and knee arthroplasties (KAs) between 1 January 2005 and 31 December 2018 in England. Methods. We combined data from the National Joint Registry (NJR) on primary elective hip and knee arthroplasties performed between 2005 and 2018 with pre-existing conditions recorded at the time of their primary operation from Hospital Episodes Statistics. We described the temporal trend in the number of comorbidities identified using the Charlson Comorbidity Index, and how this varied by age, sex, American Society of Anesthesiologists (ASA) grade, index of multiple deprivation, and type of KA. Results. We included 696,504 and 833,745 elective primary THAs and KAs respectively, performed for any indication. Between 2005 and 2018, the proportion of elective THA and KA patients with one or more comorbidity at the time of their operation increased substantially (THA: 20% to 38%, KA: 22% to 41%). This was driven by increases in four conditions: chronic obstructive pulmonary disease (COPD) (2018: ~17%), diabetes without complications (2018: THA 10%, KA 14%), myocardial infarction (2018: 4%), and renal disease (2018: ~8%). Notably, renal disease prevalence increased from < 1% in 2005 to ~8% in 2018. Conclusion. Between 2005 and 2018 there were significant changes in the number of comorbidities recorded in patients having elective primary THAs and KAs. Renal disease is now one of the most prevalent comorbidities in this patient population. Future research should explore whether this comorbidity trend has increased the burden on other medical specialities to optimize these patients before surgery and to provide additional postoperative care. Cite this article: Bone Joint J 2022;104-B(9):1052–1059

Aims. Access to joint replacement is being restricted for patients with comorbidities in a number of high-income countries. However, there is little evidence on the impact of comorbidities on outcomes. The purpose of this study was to determine the safety and effectiveness of hip and knee arthroplasty in patients with and without comorbidities. Methods. In total, 312,079 hip arthroplasty and 328,753 knee arthroplasty patients were included. A total of 11 common comorbidities were identified in administrative hospital records. Safety risks were measured by assessing length of hospital stay (LOS) and 30-day emergency readmissions and mortality. Effectiveness outcomes were changes in Oxford Hip or Knee Scores (OHS/OKS) (scale from 0 (worst) to 48 (best)) and in health-related quality of life (EQ-5D) (scale from 0 (death) to 1 (full health)) from immediately before, to six months after, surgery. Regression analysis was used to estimate adjusted mean differences (LOS, change in OHS/OKS/EQ-5D) and risk differences (readmissions and mortality). Results. Patients with comorbidities had a longer LOS and higher readmission and mortality rates than patients without. In hip arthroplasty patients with heart disease, for example, LOS was 1.20 days (95% confidence interval (CI) 1.15 to 1.25) longer and readmission rate was 1.52% (95% CI 1.34% to 1.71%) and mortality 0.19% (95% CI 0.15% to 0.23%) higher. Similar patterns were observed for knee arthroplasty patients. Patients without comorbidities reported large improvements in function (mean improvement OHS 21.3 (SD 9.91) and OKS 15.9 (SD 10.0)). Patients with comorbidities reported only slightly smaller improvements. In patients with heart disease, mean improvement in OHS was 0.39 (95% CI 0.27 to 0.51) and in OKS 0.56 (95% CI 0.45 to 0.67) less than in patients without comorbidities. There were no significant differences in EQ-5D improvement. Conclusion. Comorbidities were associated with small increases in adverse safety risks but they have little impact on pain or function in patients undergoing hip or knee arthroplasty. These results do not support restricting access to hip and knee arthroplasty for patients with common comorbidities. Cite this article: Bone Joint J 2021;103-B(1):56–64

Aims. To investigate whether chronic kidney disease (CKD) is associated with the risk of all-cause revision or revision due to a periprosthetic joint infection (PJI) after primary hip or knee arthroplasty. Methods. This retrospective cohort study comprised 18,979 consecutive hip and knee arthroplasties from a single high-volume academic hospital. At a median of 5.6 years (interquartile range (IQR) 3.5 to 8.1), all deaths and revisions were counted. To overcome the competing risk of death, competing risk analysis using the cumulative incidence function (CIF) was applied to analyze the association between different stages of CKD and revisions. Confounding factors such as diabetes and BMI were considered using either a stratified CIF or the Fine and Gray model. Results. There were 2,111 deaths (11.1%) and 677 revisions (3.6%) during the follow-up period. PJI was the reason for revision in 162 cases (0.9%). For hip arthroplasty, 3.5% of patients with CKD stage 1 (i.e. normal kidney function, NKF), 3.8% with CKD stage 2, 4.2% with CKD stage 3, and 0% with CKD stage 4 to 5 had undergone revision within eight years. For knee arthroplasty, 4.7% with NKF, 2.7% with CKD stage 2, 2.4% with CKD stage 3, and 7% of CKD stage 4 to 5 had had undergone revision. With the exception of knee arthroplasty patients in whom normal kidney function was associated with a greater probability of all-cause revision, there were no major differences in the rates of all-cause revisions or revisions due to PJIs between different CKD stages. The results remained unchanged when diabetes and BMI were considered. Conclusion. We found no strong evidence that CKD was associated with an increased risk of all-cause or PJI-related revision. Selection bias probably explains the increased amount of all-cause revision operations in knee arthroplasty patients with normal kidney function. The effect of stage 4 to 5 CKD was difficult to evaluate because of the small number of patients. Cite this article: Bone Joint J 2021;103-B(4):689–695

Aims. The aim of this study was to report health-related quality of life (HRQoL) and joint-specific function in patients waiting for total hip or knee arthroplasty surgery (THA or TKA) in Northern Ireland, compared to published literature and a matched normal population. Secondary aims were to report emergency department (ED) and out-of-hours general practitioner (OOH GP) visits, new prescriptions of strong opioids, and new prescriptions of antidepressants while waiting. Methods. This was a cohort study of 991 patients on the waiting list for arthroplasty in a single Northern Ireland NHS trust: 497 on the waiting list for ≤ three months; and 494 waiting ≥ three years. Postal surveys included the EuroQol five-dimension five-level questionnaire (EQ-5D-5L), visual analogue scores (EQ-VAS), and Oxford Hip and Knee scores to assess HRQoL and joint-specific function. Electronic records determined prescriptions since addition to the waiting list and patient attendances at OOH GP/EDs. Results. Overall, 712/991 (71.8%) responded at ≤ three months for THA (n = 164) and TKA (n = 199), and ≥ three years for THA (n = 88) and TKA (n = 261). The median EQ-5D-5L score in those waiting ≤ three months was 0.155 (interquartile range (IQR) -0.118 to 0.375) and 0.189 (IQR -0.130 to 0.377) for ≥ three years. Matched controls had a median EQ-5D-5L 0.837 (IQR 0.728 to 1.000). Compared to matched controls, EQ-5D-5L scores were significantly lower in both waiting cohorts (p < 0.001) with significant differences found in every domain. Negative scores, indicating a state “worse than death”, were present in 40% at ≤ three months and 38% at ≥ three years. Patients waiting ≥ three years had significantly more opioid (28.4% vs 15.2%; p < 0.001) and antidepressant prescriptions (15.2% vs 9.9%; p = 0.034) and significantly more joint-related attendances at unscheduled care (11.7% vs 0% with ≥ one ED attendance (p < 0.001) and (25.5% vs 2.5% ≥ one OOH GP attendance (p < 0.001)). Conclusion. Patients on waiting lists in Northern Ireland are severely disabled with the worst HRQoL and functional scores studied. The lack of deterioration in EQ-5D-5L and joint-specific scores between patients waiting ≤ three months and ≥ three years likely reflects floor effects of these scores. Prolonged waits were associated with increased dependence on strong opiates, depression, and attendances at unscheduled care. Cite this article: Bone Joint J 2023;105-B(7):783–794

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 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. 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. Arthroplasty has been shown to generate the most waste among all orthopaedic subspecialties, and it is estimated that hip and knee arthroplasty generate in excess of three million kg of waste annually in the UK. Infectious waste generates up to ten times more CO2 compared with recycled waste, and previous studies have shown that over 90% of waste in the infectious stream is misallocated. We assessed the effect of real-time waste segregation by an unscrubbed team member on waste generation in knee and hip arthroplasty cases, and compared this with a simple educational intervention during the ‘team brief’ at the start of the operating list across two sites. Methods. Waste was categorized into five categories: infectious, general, recycling, sharps, and linens. Each category was weighed at the end of each case using a digital weighing scale. At Site A (a tertiary orthopaedic hospital), pre-intervention data were collected for 16 total knee arthroplasy (TKA) and 15 total hip arthroplasty (THA) cases. Subsequently, for ten TKA and ten THA cases, an unscrubbed team member actively segregated waste in real-time into the correct streams. At Site B (a district general hospital), both pre- and post-intervention groups included ten TKA and ten THA cases. The intervention included reminding staff during the ‘team brief’ to segregate waste correctly. Results. Active real-time waste segregation reduced infectious waste by a mean of 2.51 kg (95% CI 1.492 to 3.542) in TKA, and 1.83 kg in THA cases (p = 0.004). Educational intervention reduced infectious waste by a mean of 3.52 kg in TKA and 2.09 kg in THA cases (p = 0.026). Total waste was significantly reduced in both groups post-intervention for TKA cases. Conclusion. Simple educational measures alone can significantly reduce the amount of infectious waste. Extrapolated nationally, our results would yield a reduction of approximately 315,004 kg to 594,577 kg of CO2 annually, which equates to 70 to 132 gasoline-powered passenger vehicles driven for a year. Cite this article: Bone Jt Open 2024;5(12):1119–1124

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 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 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. 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