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. 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 extended wait that most patients are now experiencing for hip and knee arthroplasty has raised questions about whether reliance on waiting time as the primary driver for prioritization is ethical, and if other additional factors should be included in determining surgical priority. Our Prioritization of THose aWaiting hip and knee ArthroplastY (PATHWAY) project will explore which perioperative factors are important to consider when prioritizing those on the waiting list for hip and knee arthroplasty, and how these factors should be weighted. The final product will include a weighted benefit score that can be used to aid in surgical prioritization for those awaiting elective primary hip and knee arthroplasty. Methods. There will be two linked work packages focusing on opinion from key stakeholders (patients and surgeons). First, an online modified Delphi process to determine a consensus set of factors that should be involved in patient prioritization. This will be performed using standard Delphi methodology consisting of multiple rounds where following initial individual rating there is feedback, discussion, and further recommendations undertaken towards eventual consensus. The second stage will then consist of a Discrete Choice Experiment (DCE) to allow for priority setting of the factors derived from the Delphi through elicitation of weighted benefit scores. The DCE consists of several choice tasks designed to elicit stakeholder preference regarding included attributes (factors). Results. The study is co-funded by the University of Aberdeen Knowledge Exchange Commission (Ref CF10693-29) and a Chief Scientist Office (CSO) Scotland Clinical Research Fellowship which runs from 08/2021 to 08/2024 (Grant ref: CAF/21/06). Approval from the University of Aberdeen Institute of Applied Health Sciences School Ethics Review Board was granted 22/03/2022 - Reference number SERB/2021/12/2210. Conclusion. The PATHWAY project provides the first attempt to use patient and surgeon opinions to develop a unified approach to prioritization for those awaiting hip and knee arthroplasty. Development of such a tool will provide more equitable access to arthroplasty services, as well as providing a framework for developing similar approaches in other areas of healthcare delivery. Cite this article: Bone Jt Open 2022;3(10):753–758

Aims. Periprosthetic joint infections (PJIs) are among the most devastating complications after joint arthroplasty. There is limited evidence on the efficacy of different antiseptic solutions on reducing biofilm burden. The purpose of the present study was to test the efficacy of different antiseptic solutions against clinically relevant microorganisms in biofilm. Methods. We conducted an in vitro study examining the efficacy of several antiseptic solutions against clinically relevant microorganisms. We tested antiseptic irrigants against nascent (four-hour) and mature (three-day) single-species biofilm created in vitro using a drip-flow reactor model. Results. With regard to irrigant efficacy against biofilms, Povidone-iodine treatment resulted in greater reductions in nascent MRSA biofilms (logarithmic reduction (LR) = 3.12; p < 0.001) compared to other solutions. Bactisure treatment had the greatest reduction of mature Pseudomonas aeruginosa biofilms (LR = 1.94; p = 0.032) and a larger reduction than Vashe or Irrisept for mature Staphylococcus epidermidis biofilms (LR = 2.12; p = 0.025). Pooled data for all biofilms tested resulted in Bactisure and Povidone-iodine with significantly greater reductions compared to Vashe, Prontosan, and Irrisept solutions (p < 0.001). Conclusion. Treatment failure in PJI is often due to failure to clear the biofilm; antiseptics are often used as an adjunct to biofilm clearance. We tested irrigants against clinically relevant microorganisms in biofilm in vitro and showed significant differences in efficacy among the different solutions. Further clinical outcome data is necessary to determine whether these solutions can impact PJI outcome in vivo. Cite this article: Bone Joint J 2021;103-B(5):908–915

Aims

The aim of this study was to evaluate the diagnostic accuracy of the synovial alpha-defensin enzyme-linked immunosorbent assay (ELISA) for the diagnosis of prosthetic joint infection (PJI) in the work-up prior to revision of total hip (THA) and knee arthroplasty (TKA).

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.

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

Aims. We aim to evaluate the usefulness of postoperative blood tests by investigating the incidence of abnormal results following total joint replacement (TJR), as well as identifying preoperative risk factors for abnormal blood test results postoperatively, especially pertaining to anaemia and acute kidney injury (AKI). Methods. This is a retrospective cohort study of patients who had elective TJR between January and December 2019 at a tertiary centre. Data gathered included age at time of surgery, sex, BMI, American Society of Anesthesiologists (ASA) grade, preoperative and postoperative laboratory test results, haemoglobin (Hgb), white blood count (WBC), haematocrit (Hct), platelets (Plts), sodium (Na. +. ), potassium (K. +. ), creatinine (Cr), estimated glomerular filtration rate (eGFR), and Ferritin (ug/l). Abnormal blood tests, AKI, electrolyte imbalance, anaemia, transfusion, reoperation, and readmission within one year were reported. Results. The study included 2,721 patients with a mean age of 69 years, of whom 1,266 (46.6%) were male. Abnormal postoperative bloods were identified in 444 (16.3%) patients. We identified age (≥ 65 years), female sex, and ASA grade ≥ III as risk factors for developing abnormal postoperative blood tests. Preoperative haemoglobin (≤ 127 g/dl) and packed cell volume (≤ 0.395 l/l) were noted to be significant risk factors for postoperative anaemia, and potassium (≤ 3.7 mmol/l) was noted to be a significant risk factor for AKI. Conclusion. The costs outweigh the benefits of ordering routine postoperative blood tests in TJR patients. Clinicians should risk-stratify their patients and have a lower threshold for ordering blood tests in patients with abnormal preoperative haemoglobin (≤ 127 g/l), blood loss > 300 ml, chronic kidney disease, ASA grade ≥ III, and clinical concern. Cite this article: Bone Jt Open 2023;4(11):899–905

Aims. This study aimed to investigate the estimated change in primary and revision arthroplasty rate in the Netherlands and Denmark for hips, knees, and shoulders during the COVID-19 pandemic in 2020 (COVID-period). Additional points of focus included the comparison of patient characteristics and hospital type (2019 vs COVID-period), and the estimated loss of quality-adjusted life years (QALYs) and impact on waiting lists. Methods. All hip, knee, and shoulder arthroplasties (2014 to 2020) from the Dutch Arthroplasty Register, and hip and knee arthroplasties from the Danish Hip and Knee Arthroplasty Registries, were included. The expected number of arthroplasties per month in 2020 was estimated using Poisson regression, taking into account changes in age and sex distribution of the general Dutch/Danish population over time, calculating observed/expected (O/E) ratios. Country-specific proportions of patient characteristics and hospital type were calculated per indication category (osteoarthritis/other elective/acute). Waiting list outcomes including QALYs were estimated by modelling virtual waiting lists including 0%, 5% and 10% extra capacity. Results. During COVID-period, fewer arthroplasties were performed than expected (Netherlands: 20%; Denmark: 5%), with the lowest O/E in April. In the Netherlands, more acute indications were prioritized, resulting in more American Society of Anesthesiologists grade III to IV patients receiving surgery. In both countries, no other patient prioritization was present. Relatively more arthroplasties were performed in private hospitals. There were no clinically relevant differences in revision arthroplasties between pre-COVID and COVID-period. Estimated total health loss depending on extra capacity ranged from: 19,800 to 29,400 QALYs (Netherlands): 1,700 to 2,400 QALYs (Denmark). With no extra capacity it will take > 30 years to deplete the waiting lists. Conclusion. The COVID-19 pandemic had an enormous negative effect on arthroplasty rates, but more in the Netherlands than Denmark. In the Netherlands, hip and shoulder patients with acute indications were prioritized. Private hospitals filled in part of the capacity gap. QALY loss due to postponed arthroplasty surgeries is considerable. Cite this article: Bone Jt Open 2022;3(12):977–990

Aims. The primary aim of this study was to assess whether patients waiting six months or more for a total hip (THA) or knee (KA) arthroplasty had a deterioration in their health-related quality of life (HRQoL). Secondary aims were to assess changes in frailty and the number of patients living in a state considered to be worse than death (WTD), and factors associated with changes in HRQoL and frailty. Methods. This cross-sectional study included 326 patients, 150 males (46.0%) and 176 females (54.0%), with a mean age of 68.6 years (SD 9.8) who were randomly selected from waiting lists at four centres and had been waiting for six months or more (median 13 months, interquartile range 10 to 21) for a primary THA (n = 161) or KA (n = 165). The EuroQol five-dimension questionnaire (EQ-5D) and visual analogue scores (EQ-VAS), Rockwood Clinical Frailty Scale (CFS), and 36-Item Short Form Survey subjective change in HRQoL were assessed at the time and recalled for six months earlier. A state that was WTD was defined as an EQ-5D of less than zero. Results. There were significant deteriorations in the EQ-5D (mean 0.175, 95% confidence interval (CI) 0.145 to 0.204; p < 0.001), EQ-VAS (mean 8.6, 95% CI 7.0 to 10.4; < 0.001), and CFS (from 3 “managing well” to 4 “vulnerable”; p < 0.001), and a significant increase in the number of those in a state that was WTD (n = 48; p < 0.001) during the previous six months for the whole cohort. A total of 110 patients (33.7%) stated that their health was much worse and 107 (32.8%) felt it was somewhat worse compared with six months previously. A significantly greater EQ-5D (-0.14, 95% CI 0.08 to 0.28; p = 0.038) and a state that was not WTD (-0.14, 95% CI 0.01 to 0.26; p = 0.031) were associated with a deterioration in the EQ-5D. THA (0.21, 95% CI 0.07 to 0.34; p = 0.002) or a lower (better) CFS (0.14, 95% CI 0.07 to 0.20; p < 0.001) were independently significantly associated with a deterioration in the CFS. Conclusion. Patients waiting more than six months for THA or KA had a significant deterioration in their HRQoL and increased frailty, with two-thirds of patients feeling that their health had worsened. Cite this article: Bone Joint J 2022;104-B(11):1215–1224

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. Routinely collected patient-reported outcome measures (PROMs) have been useful to quantify and quality-assess provision of total hip arthroplasty (THA) and total knee arthroplasty (TKA) in the UK for the past decade. This study aimed to explore whether the outcome following primary THA and TKA had improved over the past seven years. Methods. Secondary data analysis of 277,430 primary THAs and 308,007 primary TKAs from the NHS PROMs programme was undertaken. Outcome measures were: postoperative Oxford Hip/Knee Score (OHS/OKS); proportion of patients achieving a clinically important improvement in joint function (responders); quality of life; patient satisfaction; perceived success; and complication rates. Outcome measures were compared based on year of surgery using multiple linear and logistic regression models. Results. For primary THA, multiple linear regression modelling found that more recent year of surgery was associated with higher postoperative OHS (unstandardized coefficient (B) 0.15 points (95% confidence interval (CI) 0.14 to 0.17); p < 0.001) and higher EuroQol five-dimension index (EQ-5D) utility (B 0.002 (95% CI 0.001 to 0.002); p < 0.001). The odds of being a responder (odds ratio (OR) 1.02 (95% CI 1.02 to 1.03); p < 0.001) and patient satisfaction (OR 1.02 (95% CI 1.01 to 1.03); p < 0.001) increased with year of surgery, while the odds of any complication reduced (OR 0.97 (95% CI 0.97 to 0.98); p < 0.001). No trend was found for perceived success (p = 0.555). For primary TKA, multiple linear regression modelling found that more recent year of surgery was associated with higher postoperative OKS (B 0.21 points (95% CI 0.19 to 0.22); p < 0.001) and higher EQ-5D utility (B 0.002 (95% CI 0.002 to 0.003); p < 0.001). The odds of being a responder (OR 1.04 (95% CI 1.03 to 1.04); p < 0.001), perceived success (OR 1.02 (95% CI 1.01 to 1.02); p < 0.001), and patient satisfaction (OR 1.02 (95% CI 1.01 to 1.02); p < 0.001) all increased with year of surgery, while the odds of any complication reduced (OR 0.97 (95% CI 0.97 to 0.97); p < 0.001). Conclusion. Nearly all patient-reported outcomes following primary THA/TKA improved by a small amount over the past seven years. Due to the high proportion of patients achieving good outcomes, PROMs following THA and TKA may need to focus on better discrimination of patients achieving high scores to be able to continue to measure improvement in outcomes. Cite this article: Bone Joint J 2022;104-B(6):687–695

Aims

A higher failure rate has been reported in haematogenous periprosthetic joint infection (PJI) compared to non-haematogenous PJI. The reason for this difference is unknown. We investigated the outcome of haematogenous and non-haematogenous PJI to analyze the risk factors for failure in both groups of patients.

Aims

Revision total knee arthroplasty (rTKA) and revision total hip arthroplasty (rTHA) are complex procedures with higher rates of re-revision, complications, and mortality compared to primary TKA and THA. We report the effects of the establishment of a revision arthroplasty network (the East Midlands Specialist Orthopaedic Network; EMSON) on outcomes of rTKA and rTHA.

Aims

The outcomes of patients with unexpected positive cultures (UPCs) during revision total hip arthroplasty (THA) and total knee arthroplasty (TKA) remain unknown. The objectives of this study were to establish the prevalence and infection-free implant survival in UPCs during presumed aseptic single-stage revision THA and TKA at mid-term follow-up.

Aims

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

Aims

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.