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 COVID-19 pandemic has caused unprecedented disruption to elective orthopaedic services. The primary objective of this study was to examine changes in functional scores in patients awaiting total hip arthroplasty (THA), total knee arthroplasty (TKA), and unicompartmental knee arthroplasty (UKA). Secondary objectives were to investigate differences between these groups and identify those in a health state ‘worse than death’ (WTD). Methods. In this prospective cohort study, preoperative Oxford hip and knee scores (OHS/OKS) were recorded for patients added to a waiting list for THA, TKA, or UKA, during the initial eight months of the COVID-19 pandemic, and repeated at 14 months into the pandemic (mean interval nine months (SD 2.84)). EuroQoL five-dimension five-level health questionnaire (EQ-5D-5L) index scores were also calculated at this point in time, with a negative score representing a state WTD. OHS/OKS were analyzed over time and in relation to the EQ-5D-5L. Results. A total of 174 patients (58 THA, 74 TKA, 42 UKA) were eligible, after 27 were excluded (one died, seven underwent surgery, 19 non-responders). The overall mean OHS/OKS deteriorated from 15.43 (SD 6.92), when patients were added to the waiting list, to 11.77 (SD 6.45) during the pandemic (p < 0.001). There were significantly worse EQ-5D-5L index scores in the THA group (p = 0.005), with 22 of these patients (38%) in a health state WTD, than either the TKA group (20 patients; 27% WTD), or the UKA group (nine patients; 21% WTD). A strong positive correlation between the EQ-5D-5L index score and OHS/OKS was observed (r = 0.818; p < 0.001). Receiver operating characteristic analysis revealed that an OHS/OKS lower than nine predicted a health state WTD (88% sensitivity and 73% specificity). Conclusion. OHS/OKS deteriorated significantly among patients awaiting lower limb arthroplasty during the COVID-19 pandemic. Overall, 51 patients were in a health state WTD, representing 29% of our entire cohort, which is considerably worse than existing pre-pandemic data. Cite this article: Bone Jt Open 2023;4(3):138–145

Objectives

Patient function after arthroplasty should ideally quickly improve. It is not known which peri-operative function assessments predict length of stay (LOS) and short-term functional recovery. The objective of this study was to identify peri-operative functions assessments predictive of hospital LOS and short-term function after hospital discharge in hip or knee arthroplasty patients.

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

We conducted a multicentre cohort study of 228 patients with osteoarthritis followed up after total hip or knee replacement. Quality of life and patient satisfaction were assessed by self-administered questionnaires. Patient satisfaction was the dependent variable in a multivariate linear regression model. Independent variables included sociodemographic factors, pre- and post-operative clinical characteristics and the pre-operative and post-discharge health-related quality of life.

The mean age of the patients was 69 years (sd 9), and 43.8% were male. Pre- and postoperative clinical characteristics were not associated with satisfaction with health care. Only pre-operative bodily pain (p < 0.01) and pre-operative social functioning (p < 0.05) influenced patient satisfaction with care.

The pre-operative health-related quality of life and patient characteristics have little effect on inpatient satisfaction with care. This suggests that the impact of the care process on satisfaction may be independent of observed and perceived initial patient-related characteristics.

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 study was to evaluate the optimal deep tissue specimen sample number for histopathological analysis in the diagnosis of periprosthetic joint infection (PJI). Methods. In this retrospective diagnostic study, patients undergoing revision surgery after total hip or knee arthroplasty (n = 119) between January 2015 and July 2018 were included. Multiple specimens of the periprosthetic membrane and pseudocapsule were obtained for histopathological analysis at revision arthroplasty. Based on the Infectious Diseases Society of America (IDSA) 2013 criteria, the International Consensus Meeting (ICM) 2018 criteria, and the European Bone and Joint Infection Society (EBJIS) 2021 criteria, PJI was defined. Using a mixed effects logistic regression model, the sensitivity and specificity of the histological diagnosis were calculated. The optimal number of periprosthetic tissue specimens for histopathological analysis was determined by applying the Youden index. Results. Based on the EBJIS criteria (excluding histology), 46 (39%) patients were classified as infected. Four to six specimens showed the highest Youden index (four specimens: 0.631; five: 0.634; six: 0.632). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of five tissue specimens were 76.5% (95% confidence interval (CI) 67.6 to 81.4), 86.8% (95% CI 81.3 to 93.5), 66.0% (95% CI 53.2 to 78.7), and 84.3% (95% CI 79.4 to 89.3), respectively. The area under the curve (AUC) was calculated with 0.81 (as a function of the number of tissue specimens). Applying the ICM and IDSA criteria (excluding histology), 40 (34%) and 32 (27%) patients were categorized as septic. Three to five specimens had the highest Youden index (ICM 3: 0.648; 4: 0.651; 5: 0.649) (IDSA 3: 0.627; 4: 0.629; 5: 0.625). Conclusion. Three to six tissue specimens of the periprosthetic membrane and pseudocapsule should be collected at revision arthroplasty and analyzed by a pathologist experienced and skilled in interpreting periprosthetic tissue. Cite this article: Bone Joint J 2023;105-B(2):158–165

Aims. To determine the trajectories of patient reported pain and functional disability over five years following total hip arthroplasty (THA) or total knee arthroplasty (TKA). Methods. A prospective, longitudinal cohort sub-study within the National Joint Registry (NJR) was undertaken. In all, 20,089 patients who underwent primary THA and 22,489 who underwent primary TKA between 2009 and 2010 were sent Oxford Hip Score (OHS) and Oxford Knee Score (OKS) questionnaires at six months, and one, three, and five years postoperatively. OHS and OKS were disaggregated into pain and function subscales. A k-means clustering procedure assigned each patient to a longitudinal trajectory group for pain and function. Ordinal regression was used to predict trajectory group membership using baseline OHS and OKS score, age, BMI, index of multiple deprivation, sex, ethnicity, geographical location, and American Society of Anesthesiologists grade. Results. Data described two discrete trajectories for pain and function: ‘level 1’ responders (around 70% of cases) in whom a high level of improvement is sustained over five years, and ‘level 2’ responders who had sustained improvement, but at a lower level. Baseline patient variables were only weak predictors of pain trajectory and modest predictors of function trajectory. Those with worse baseline pain and function tended to show a greater likelihood of following a ‘level 2’ trajectory. Six-month patient-reported outcome measures data reliably predicted the class of five-year outcome trajectory for both pain and function. Conclusion. The available preoperative patient variables were not reliable predictors of postoperative pain and function after THA and TKA. Reviewing patient outcomes at six months postoperatively is a reliable indicator of outcome at five years. Cite this article: Bone Joint J 2021;103-B(6):1111–1118

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 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. Synovial fluid white blood cell (WBC) count and percentage of polymorphonuclear cells (%PMN) are elevated at periprosthetic joint infection (PJI). Leucocytes produce different interleukins (IL), including IL-6, so we hypothesized that synovial fluid IL-6 could be a more accurate predictor of PJI than synovial fluid WBC count and %PMN. The main aim of our study was to compare the predictive performance of all three diagnostic tests in the detection of PJI. Methods. Patients undergoing total hip or knee revision surgery were included. In the perioperative assessment phase, synovial fluid WBC count, %PMN, and IL-6 concentration were measured. Patients were labeled as positive or negative according to the predefined cut-off values for IL-6 and WBC count with %PMN. Intraoperative samples for microbiological and histopathological analysis were obtained. PJI was defined as the presence of sinus tract, inflammation in histopathological samples, and growth of the same microorganism in a minimum of two or more samples out of at least four taken. Results. In total, 49 joints in 48 patients (mean age 68 years (SD 10; 26 females (54%), 25 knees (51%)) were included. Of these 11 joints (22%) were infected. The synovial fluid WBC count and %PMN predicted PJI with sensitivity, specificity, accuracy, PPV, and NPV of 82%, 97%, 94%, 90%, and 95%, respectively. Synovial fluid IL-6 predicted PJI with sensitivity, specificity, accuracy, PPV, and NPV of 73%, 95%, 90%, 80%, and 92%, respectively. A comparison of predictive performance indicated a strong agreement between tests. Conclusions. Synovial fluid IL-6 is not superior to synovial fluid WBC count and %PMN in detecting PJI. Level of Evidence: Therapeutic Level II. Cite this article: Bone Jt Open 2020;1-12:737–742

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. Methods. We performed an analysis of the mandatory prospective national registry of all independent and publicly funded hip, knee, shoulder, elbow, and ankle replacements in England, Wales, and Northern Ireland between January 2019 and December 2022 inclusive, totalling 729,642 operations. The deficit was calculated per year compared to a continuation of 2019 volume. Total deficit of cases between 2020 to 2022 was expressed as a percentage of 2019 volume. Sub-analyses were performed based on procedure type, country, and unit sector. Results. Between January 2020 and December 2022, there was a deficit of 158,994 joint replacements. This is equivalent to over two-thirds of a year of normal expected operating activity (71.6%). There were 104,724 (-47.1%) fewer performed in 2020, 41,928 (-18.9%) fewer performed in 2021, and 12,342 (-5.6%) fewer performed in 2022, respectively, than in 2019. Independent-sector procedures increased to make it the predominant arthroplasty provider (53% in 2022). NHS activity was 73.2% of 2019 levels, while independent activity increased to 126.8%. Wales (-136.3%) and Northern Ireland (-121.3%) recorded deficits of more than a year’s worth of procedures, substantially more than England (-66.7%). It would take until 2031 to eliminate this deficit with an immediate expansion of capacity over 2019 levels by 10%. Conclusion. The arthroplasty deficit following the COVID-19 pandemic is now equivalent to over two-thirds of a year of normal operating activity, and continues to increase. Patients awaiting different types of arthroplasty, in each country, have been affected disproportionately. A rapid and significant expansion in services is required to address the deficit, and will still take many years to rectify. Cite this article: Bone Joint J 2024;106-B(8):834–841

Aims. Total hip arthroplasty (THA) and total knee arthroplasty (TKA) are common orthopaedic procedures requiring postoperative radiographs to confirm implant positioning and identify complications. Artificial intelligence (AI)-based image analysis has the potential to automate this postoperative surveillance. The aim of this study was to prepare a scoping review to investigate how AI is being used in the analysis of radiographs following THA and TKA, and how accurate these tools are. Methods. The Embase, MEDLINE, and PubMed libraries were systematically searched to identify relevant articles. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews and Arksey and O’Malley framework were followed. Study quality was assessed using a modified Methodological Index for Non-Randomized Studies tool. AI performance was reported using either the area under the curve (AUC) or accuracy. Results. Of the 455 studies identified, only 12 were suitable for inclusion. Nine reported implant identification and three described predicting risk of implant failure. Of the 12, three studies compared AI performance with orthopaedic surgeons. AI-based implant identification achieved AUC 0.992 to 1, and most algorithms reported an accuracy > 90%, using 550 to 320,000 training radiographs. AI prediction of dislocation risk post-THA, determined after five-year follow-up, was satisfactory (AUC 76.67; 8,500 training radiographs). Diagnosis of hip implant loosening was good (accuracy 88.3%; 420 training radiographs) and measurement of postoperative acetabular angles was comparable to humans (mean absolute difference 1.35° to 1.39°). However, 11 of the 12 studies had several methodological limitations introducing a high risk of bias. None of the studies were externally validated. Conclusion. These studies show that AI is promising. While it already has the ability to analyze images with significant precision, there is currently insufficient high-level evidence to support its widespread clinical use. Further research to design robust studies that follow standard reporting guidelines should be encouraged to develop AI models that could be easily translated into real-world conditions. Cite this article: Bone Joint J 2022;104-B(8):929–937

Aims. 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. 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. Fungal and mycobacterial periprosthetic joint infections (PJI) are rare events. Clinicians are wary of missing these diagnoses, often leading to the routine ordering of fungal and mycobacterial cultures on periprosthetic specimens. Our goal was to examine the utility of these cultures and explore a modern bacterial culture technique using bacterial blood culture bottles (BCBs) as an alternative. Methods. We performed a retrospective review of patients diagnosed with hip or knee PJI between 1 January 2010 and 31 December 2019, at the Mayo Clinic in Rochester, Minnesota, USA. We included patients aged 18 years or older who had fungal, mycobacterial, or both cultures performed together with bacterial cultures. Cases with positive fungal or mycobacterial cultures were reviewed using the electronic medical record to classify the microbiological findings as representing true infection or not. Results. There were 2,067 episodes of PJI diagnosed within the study period. A total of 3,629 fungal cultures and 2,923 mycobacterial cultures were performed, with at least one of these performed in 56% of episodes (n = 1,157). Test positivity rates of fungal and mycobacterial cultures were 5% (n = 179) and 1.2% (n = 34), respectively. After a comprehensive review, there were 40 true fungal and eight true mycobacterial PJIs. BCB were 90% sensitive in diagnosing true fungal PJI and 100% sensitive in detecting rapidly growing mycobacteria (RGM). Fungal stains were performed in 27 true fungal PJI but were only positive in four episodes (14.8% sensitivity). None of the mycobacterial stains was positive. Conclusion. Routine fungal and mycobacterial stains and cultures should not be performed as they have little clinical utility in the diagnosis of PJI and are associated with significant costs. Candida species and RGM are readily recovered using BCB. More research is needed to predict rare non-Candida fungal and slowly growing mycobacterial PJI that warrant specialized cultures. Cite this article: Bone Joint J 2022;104-B(1):53–58

Aims. Calprotectin (CLP) is produced in neutrophils and monocytes and released into body fluids as a result of inflammation or infection. The aim of this study was to evaluate the utility of blood and synovial CLP in the diagnosis of chronic periprosthetic joint infection (PJI). Methods. Blood and synovial fluid samples were collected prospectively from 195 patients undergoing primary or revision hip and knee arthroplasty. Patients were divided into five groups: 1) primary total hip and knee arthroplasty performed due to idiopathic osteoarthritis (OA; n = 60); 2) revision hip and knee arthroplasty performed due to aseptic failure of the implant (AR-TJR; n = 40); 3) patients with a confirmed diagnosis of chronic PJI awaiting surgery (n = 45); 4) patients who have finished the first stage of the PJI treatment with the use of cemented spacer and were qualified for replantation procedure (SR-TJR; n = 25), and 5) patients with rheumatoid arthritis undergoing primary total hip and knee arthroplasty (RA; n = 25). CLP concentrations were measured quantitatively in the blood and synovial fluid using an immunoturbidimetric assay. Additionally, blood and synovial CRP, blood interleukin-6 (IL-6), and ESR were measured, and a leucocyte esterase (LE) strip test was performed. Results. Patients with PJI had higher CLP concentrations than those undergoing aseptic revision in blood (median PJI 2.14 mg/l (interquartile range (IQR) 1.37 to 3.56) vs AR-TJR 0.66 mg/l (IQR 0.3 to 0.83); p < 0.001) and synovial fluid samples (median PJI 20.46 mg/l (IQR 14.3 to 22.36) vs AR-TJR 0.7 mg/l (IQR 0.41 to 0.95); p < 0.001). With a cut-off value of 1.0 mg/l, blood CLP showed a sensitivity, specificity, positive predictive value, and negative predictive value of 93.3%, 87.5%, 89.4%, and 92.1%, respectively. For synovial fluid with a cut-off value of 1.5 mg/l, these were 95.6%, 95%, 95.5%, and 95%, respectively. Conclusion. This small study suggests that synovial and blood CLP are useful markers in chronic PJI diagnosis with similar or higher sensitivity and specificity than routinely used markers such as CRP, ESR, IL-6, and LE. CLP was not useful to differentiate patients with PJI from those with rheumatoid arthritis. Cite this article: Bone Joint J 2021;103-B(1):46–55

Aims. Biopsy of the periprosthetic tissue is an important diagnostic tool for prosthetic joint infection (PJI) as it enables the detection of the responsible microorganism with its sensitivity to antibiotics. We aimed to investigate how often the bacteria identified in the tissue analysis differed between samples obtained from preoperative biopsy and intraoperative revision surgery in cases of late PJI; and whether there was a therapeutic consequence. Methods. A total of 508 patients who required revision surgery of total hip arthroplasty (THA) (n = 231) or total knee arthroplasty (TKA) (n = 277) because of component loosening underwent biopsy before revision surgery. The tissue samples collected at biopsy and during revision surgery were analyzed according to the criteria of the Musculoskeletal Infection Society (MSIS). Results. In total, 178 (113 THA, 65 TKA) were classified as infected. The biopsy procedure had a sensitivity of 93.8%, a specificity of 97.3%, a positive predictive value (PPV) of 94.9%, a negative predictive value (NPV) of 96.7%, and an accuracy of 96.1%. Of the 178 infected patients, 26 showed a difference in the detected bacteria from the biopsy and the revision surgery (14.6%). This difference required a change to antibiotic therapy in only two cases (1.1%). Conclusion. Biopsy is a useful tool to diagnose PJI, but there may be a difference in the detected bacteria between the biopsy and revision surgery. However, this did not affect the choice of antibiotic therapy in most cases, rendering the clinical relevance of this phenomenon as low. Cite this article: Bone Joint J 2020;102-B(3):329–335

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