Aims. The aim of this study was to evaluate the performance of metagenomic next-generation sequencing (mNGS) in detecting pathogens from synovial fluid of prosthetic joint infection (PJI) patients. Methods. A group of 75 patients who underwent revision knee or hip arthroplasties were enrolled prospectively. Ten patients with primary arthroplasties were included as negative controls. Synovial fluid was collected for mNGS analysis. Optimal thresholds were determined to distinguish pathogens from background microbes. Synovial fluid, tissue, and sonicate fluid were obtained for culture. Results. A total of 49 PJI and 21 noninfection patients were finally included. Of the 39 culture-positive PJI cases, mNGS results were positive in 37 patients (94.9%), and were consistent with culture results at the genus level in 32 patients (86.5%) and at the species level in 27 patients (73.0%). Metagenomic next-generation sequencing additionally identified 15 pathogens from five culture-positive and all ten culture-negative PJI cases, and even one pathogen from one noninfection patient, while yielding no positive findings in any primary arthroplasty. However, seven pathogens identified by culture were missed by mNGS. The sensitivity of mNGS for diagnosing PJI was 95.9%, which was significantly higher than that of comprehensive culture (79.6%; p = 0.014). The specificity is similar between mNGS and comprehensive culture (95.2% and 95.2%, respectively; p = 1.0). Conclusion. Metagenomic next-generation sequencing can effectively identify pathogens from synovial fluid of PJI patients, and demonstrates high accuracy in diagnosing PJI. Cite this article: Bone Joint Res 2020;9(7):440–449

Aims. Histology is an established tool in diagnosing periprosthetic joint infections (PJIs). Different thresholds, using various infection definitions and histopathological criteria, have been described. This study determined the performance of different thresholds of polymorphonuclear neutrophils (≥ 5 PMN/HPF, ≥ 10 PMN/HPF, ≥ 23 PMN/10 HPF) , when using the European Bone and Joint Infection Society (EBJIS), Infectious Diseases Society of America (IDSA), and the International Consensus Meeting (ICM) 2018 criteria for PJI. Methods. A total of 119 patients undergoing revision total hip (rTHA) or knee arthroplasty (rTKA) were included. Permanent histology sections of periprosthetic tissue were evaluated under high power (400× magnification) and neutrophils were counted per HPF. The mean neutrophil count in ten HPFs was calculated (PMN/HPF). Based on receiver operating characteristic (ROC) curve analysis and the z-test, thresholds were compared. Results. Using the EBJIS criteria, a cut-off of ≥ five PMN/HPF showed a sensitivity of 93% (95% confidence interval (CI) 81 to 98) and specificity of 84% (95% CI 74 to 91). The optimal threshold when applying the IDSA and ICM criteria was ≥ ten PMN/HPF with sensitivities of 94% (95% CI 79 to 99) and 90% (95% CI 76 to 97), and specificities of 86% (95% CI 77 to 92) and 92% (95% CI 84 to 97), respectively. In rTKA, a better performance of histopathological analysis was observed in comparison with rTHA when using the IDSA criteria (p < 0.001). Conclusion. With high accuracy, histopathological analysis can be supported as a confirmatory criterion in diagnosing periprosthetic joint infections. A threshold of ≥ five PMN/HPF can be recommended to distinguish between septic and aseptic loosening, with an increased possibility of detecting more infections caused by low-virulence organisms. However, neutrophil counts between one and five should be considered suggestive of infection and interpreted carefully in conjunction with other diagnostic test methods. Cite this article: Bone Joint Res 2021;10(8):536–547

Aims. This study aimed to evaluate the clinical application of the PJI-TNM classification for periprosthetic joint infection (PJI) by determining intraobserver and interobserver reliability. To facilitate its use in clinical practice, an educational app was subsequently developed and evaluated. Methods. A total of ten orthopaedic surgeons classified 20 cases of PJI based on the PJI-TNM classification. Subsequently, the classification was re-evaluated using the PJI-TNM app. Classification accuracy was calculated separately for each subcategory (reinfection, tissue and implant condition, non-human cells, and morbidity of the patient). Fleiss’ kappa and Cohen’s kappa were calculated for interobserver and intraobserver reliability, respectively. Results. Overall, interobserver and intraobserver agreements were substantial across the 20 classified cases. Analyses for the variable ‘reinfection’ revealed an almost perfect interobserver and intraobserver agreement with a classification accuracy of 94.8%. The category 'tissue and implant conditions' showed moderate interobserver and substantial intraobserver reliability, while the classification accuracy was 70.8%. For 'non-human cells,' accuracy was 81.0% and interobserver agreement was moderate with an almost perfect intraobserver reliability. The classification accuracy of the variable 'morbidity of the patient' reached 73.5% with a moderate interobserver agreement, whereas the intraobserver agreement was substantial. The application of the app yielded comparable results across all subgroups. Conclusion. The PJI-TNM classification system captures the heterogeneity of PJI and can be applied with substantial inter- and intraobserver reliability. The PJI-TNM educational app aims to facilitate application in clinical practice. A major limitation was the correct assessment of the implant situation. To eliminate this, a re-evaluation according to intraoperative findings is strongly recommended. Cite this article: Bone Joint Res 2024;13(1):19–27

Aims. Serum inflammatory parameters are widely used to aid in diagnosing a periprosthetic joint infection (PJI). Due to their limited performances in the literature, novel and more accurate biomarkers are needed. Serum albumin-to-globulin ratio (AGR) and serum CRP-to-albumin ratio (CAR) have previously been proposed as potential new parameters, but results were mixed. The aim of this study was to assess the diagnostic accuracy of AGR and CAR in diagnosing PJI and to compare them to the established and widely used marker CRP. Methods. From 2015 to 2022, a consecutive series of 275 cases of revision total hip (n = 129) and knee arthroplasty (n = 146) were included in this retrospective cohort study. Based on the 2021 European Bone and Joint Infection Society (EBJIS) definition, 144 arthroplasties were classified as septic. Using receiver operating characteristic curve (ROC) analysis, the ideal thresholds and diagnostic performances were calculated. The areas under the curve (AUCs) were compared using the z-test. Results. AGR, CAR, and CRP were associated with PJI (p < 0.001). Sensitivities were 62.5% (95% CI 54.3 to 70.0), 73.6% (95% CI 65.8 to 80.1), and 71.5% (95% CI 63.6 to 78.3), respectively. Specificities were calculated with 84.7% (95% CI 77.5 to 89.9), 86.3% (95% CI 79.2 to 91.2), and 87.8% (95% CI 80.9 to 92.4), respectively. The AUC of CRP (0.797 (95% CI 0.750 to 0.843)) was significantly higher than the AUC of AGR (0.736 (95% CI 0.686 to 0.786), p < 0.001), and similar to AUC of CAR (0.799 (95% CI 0.753 to 0.846), p = 0.832). Decreased sensitivities were observed in PJIs caused by low-virulence organisms (AGR: 60%, CAR: 78%) compared to high-virulence pathogens (AGR: 80%, p = 0.042; CAR: 88%, p = 0.158). Higher sensitivities were seen in acute haematogenous (AGR: 83%, CAR: 96%) compared to chronic PJIs (AGR: 54%, p = 0.001; CAR: 65%, p < 0.001). Conclusion. Serum AGR and CAR showed limited diagnostic accuracy (especially in low-grade and chronic infections) and did not outperform the established marker CRP in our study. Hence, neither parameter can be recommended as an additional tool for diagnosing PJI. Cite this article: Bone Joint Res 2024;13(8):372–382

Aims. This study aimed to explore the diagnostic value of synovial fluid neutrophil extracellular traps (SF-NETs) in periprosthetic joint infection (PJI) diagnosis, and compare it with that of microbial culture, serum ESR and CRP, synovial white blood cell (WBC) count, and polymorphonuclear neutrophil percentage (PMN%). Methods. In a single health centre, patients with suspected PJI were enrolled from January 2013 to December 2021. The inclusion criteria were: 1) patients who were suspected to have PJI; 2) patients with complete medical records; and 3) patients from whom sufficient synovial fluid was obtained for microbial culture and NET test. Patients who received revision surgeries due to aseptic failure (AF) were selected as controls. Synovial fluid was collected for microbial culture and SF-WBC, SF-PNM%, and SF-NET detection. The receiver operating characteristic curve (ROC) of synovial NET, WBC, PMN%, and area under the curve (AUC) were obtained; the diagnostic efficacies of these diagnostic indexes were calculated and compared. Results. The levels of SF-NETs in the PJI group were significantly higher than those of the AF group. The AUC of SF-NET was 0.971 (95% confidence interval (CI) 0.903 to 0.996), the sensitivity was 93.48% (95% CI 82.10% to 98.63%), the specificity was 96.43% (95% CI 81.65% to 99.91%), the accuracy was 94.60% (95% CI 86.73% to 98.50%), the positive predictive value was 97.73%, and the negative predictive value was 90%. Further analysis showed that SF-NET could improve the diagnosis of culture-negative PJI, patients with PJI who received antibiotic treatment preoperatively, and fungal PJI. Conclusion. SF-NET is a novel and ideal synovial fluid biomarker for PJI diagnosis, which could improve PJI diagnosis greatly. Cite this article: Bone Joint Res 2023;12(2):113–120

Objectives. The aim of this study was to assess the clinical application of, and optimize the variables used in, the BACH classification of long-bone osteomyelitis. Methods. A total of 30 clinicians from a variety of specialities classified 20 anonymized cases of long-bone osteomyelitis using BACH. Cases were derived from patients who presented to specialist centres in the United Kingdom between October 2016 and April 2017. Accuracy and Fleiss’ kappa (Fκ) were calculated for each variable. Bone involvement (B-variable) was assessed further by nine clinicians who classified ten additional cases of long bone osteomyelitis using a 3D clinical imaging package. Thresholds for defining multidrug-resistant (MDR) isolates were optimized using results from a further analysis of 253 long bone osteomyelitis cases. Results. The B-variable had a classification accuracy of 77.0%, which improved to 95.7% when using a 3D clinical imaging package (p < 0.01). The A-variable demonstrated difficulty in the accuracy of classification for increasingly resistant isolates (A1 (non-resistant), 94.4%; A2 (MDR), 46.7%; A3 (extensively or pan-drug-resistant), 10.0%). Further analysis demonstrated that isolates with four or more resistant test results or less than 80% sensitive susceptibility test results had a 98.1% (95% confidence interval (CI) 96.6 to 99.6) and 98.8% (95% CI 98.1 to 100.0) correlation with MDR status, respectively. The coverage of the soft tissues (C-variable) and the host status (H-variable) both had a substantial agreement between users and a classification accuracy of 92.5% and 91.2%, respectively. Conclusions. The BACH classification system can be applied accurately by users with a variety of clinical backgrounds. Accuracy of B-classification was improved using 3D imaging. The use of the A-variable has been optimized based on susceptibility testing results. Cite this article: A. J. Hotchen, M. Dudareva, J. Y. Ferguson, P. Sendi, M. A. McNally. The BACH classification of long bone osteomyelitis. Bone Joint Res 2019;8:459–468. DOI: 10.1302/2046-3758.810.BJR-2019-0050.R1

Aims. This study aimed to explore whether serum combined with synovial interleukin-6 (IL-6) measurement can improve the accuracy of prosthetic joint infection (PJI) diagnosis, and to establish the cut-off values of IL-6 in serum and synovial fluid in detecting chronic PJI. Methods. Patients scheduled to have a revision surgery for indications of chronic infection of knee and hip arthroplasties or aseptic loosening of an implant were prospectively screened before being enrolled into this study. The Musculoskeletal Infection Society (MSIS) definition of PJI was used for the classification of cases as aseptic or infected. Serum CRP, ESR, IL-6, and percentage of polymorphonuclear neutrophils (PMN%) and IL-6 in synovial fluid were analyzed. Statistical tests were performed to compare these biomarkers in the two groups, and receiver operating characteristic (ROC) curves and area under the curve (AUC) were analyzed for each biomarker. Results. A total of 93 patients were enrolled. There was no difference in demographic data between both groups. Synovial fluid IL-6, with a threshold of 1,855.36 pg/ml, demonstrated a mean sensitivity of 94.59% (95% confidence interval (CI) 81.8% to 99.3%) and a mean specificity of 92.86% (95% CI 82.7 to 98.0) for detecting chronic PJI. Then 6.7 pg/ml was determined to be the optimal threshold value of serum IL-6 for the diagnosis of chronic PJI, with a mean sensitivity of 97.30% (95% CI 85.8% to 99.9%) and a mean specificity of 76.79% (95% CI 63.6% to 87.0%). The combination of synovial IL-6 and serum IL-6 led to improved accuracy of 96.77% in diagnosing chronic PJI. Conclusion. The present study identified that a combination of IL-6 in serum and synovial IL-6 has the potential for further improvement of the diagnosis of PJI. Cite this article: Bone Joint Res 2020;9(9):587–592

Aims. This pilot study tested the performance of a rapid assay for diagnosing prosthetic joint infection (PJI), which measures synovial fluid calprotectin from total hip and knee revision patients. Methods. A convenience series of 69 synovial fluid samples from revision patients at the Norfolk and Norwich University Hospital were collected intraoperatively (52 hips, 17 knees) and frozen. Synovial fluid calprotectin was measured retrospectively using a new commercially available lateral flow assay for PJI diagnosis (Lyfstone AS) and compared to International Consensus Meeting (ICM) 2018 criteria and clinical case review (ICM-CR) gold standards. Results. According to ICM, 24 patients were defined as PJI positive and the remaining 45 were negative. The overall accuracy of the lateral flow test compared to ICM was 75.36% (52/69, 95% CI 63.51% to 84.95%), sensitivity and specificity were 75.00% (18/24, 95% CI 53.29% to 90.23%) and 75.56% (34/45, 95% CI 60.46% to 87.12%), respectively, positive predictive value (PPV) was 62.07% (18/29, 95% CI 48.23% to 74.19%) and negative predictive value (NPV) was 85.00% (34/40, 95% CI 73.54% to 92.04%), and area under the receiver operating characteristic (ROC) curve (AUC) was 0.78 (95% CI 0.66 to 0.87). Patient data from discordant cases were reviewed by the clinical team to develop the ICM-CR gold standard. The lateral flow test performance improved significantly when compared to ICM-CR, with accuracy increasing to 82.61% (57/69, 95% CI 71.59% to 90.68%), sensitivity increasing to 94.74% (18/19, 95% CI 73.97% to 99.87%), NPV increasing to 97.50% (39/40, 95% CI 85.20% to 99.62%), and AUC increasing to 0.91 (95% CI 0.81 to 0.96). Test performance was better in knees (100.00% accurate (17/17, 95% CI 80.49% to 100.00%)) compared to hips (76.92% accurate (40/52, 95% CI 63.16% to 87.47%)). Conclusion. This study demonstrates that the calprotectin lateral flow assay could be an effective diagnostic test for PJI, however additional prospective studies testing fresh samples are required. Cite this article:Bone Joint Res. 2020;9(5):202–210

Objectives. Prosthetic joint infection (PJI) diagnosis is a major challenge in orthopaedics, and no reliable parameters have been established for accurate, preoperative predictions in the differential diagnosis of aseptic loosening or PJI. This study surveyed factors in synovial fluid (SF) for improving PJI diagnosis. Methods. We enrolled 48 patients (including 39 PJI and nine aseptic loosening cases) who required knee/hip revision surgery between January 2016 and December 2017. The PJI diagnosis was established according to the Musculoskeletal Infection Society (MSIS) criteria. SF was used to survey factors by protein array and enzyme-linked immunosorbent assay to compare protein expression patterns in SF among three groups (aseptic loosening and first- and second-stage surgery). We compared routine clinical test data, such as C-reactive protein level and leucocyte number, with potential biomarker data to assess the diagnostic ability for PJI within the same patient groups. Results. Cut-off values of 1473 pg/ml, 359 pg/ml, and 8.45 pg/ml were established for interleukin (IL)-16, IL-18, and cysteine-rich with EGF-like domains 2 (CRELD2), respectively. Receiver operating characteristic curve analysis showed that these factors exhibited an accuracy of 1 as predictors of PJI. These factors represent potential biomarkers for decisions associated with prosthesis reimplantation based on their ability to return to baseline values following the completion of debridement. Conclusion. IL-16, IL-18, and CRELD2 were found to be potential biomarkers for PJI diagnosis, with SF tests outperforming blood tests in accuracy. These factors could be useful for assessing successful debridement based on their ability to return to baseline values following the completion of debridement. Cite this article: M-F. Chen, C-H. Chang, L-Y. Yang, P-H. Hsieh, H-N. Shih, S. W. N. Ueng, Y. Chang. Synovial fluid interleukin-16, interleukin-18, and CRELD2 as novel biomarkers of prosthetic joint infections. Bone Joint Res 2019;8:179–188. DOI: 10.1302/2046-3758.84.BJR-2018-0291.R1

Aims. Preoperative diagnosis is important for revision surgery after prosthetic joint infection (PJI). The purpose of our study was to determine whether reverse transcription-quantitative polymerase chain reaction (RT-qPCR), which is used to detect bacterial ribosomal RNA (rRNA) preoperatively, can reveal PJI in low volumes of aspirated fluid. Methods. We acquired joint fluid samples (JFSs) by preoperative aspiration from patients who were suspected of having a PJI and failed arthroplasty; patients with preoperative JFS volumes less than 5 ml were enrolled. RNA-based polymerase chain reaction (PCR) and bacterial culture were performed, and diagnostic efficiency was compared between the two methods.According to established Musculoskeletal Infection Society (MSIS) criteria, 21 of the 33 included patients were diagnosed with PJI. Results. RNA-based PCR exhibited 57.1% sensitivity, 91.7% specificity, 69.7% accuracy, 92.3% positive predictive value, and 55.0% negative predictive value. The corresponding values for culture were 28.6%, 83.3%, 48.5%, 75.0%, and 40.0%, respectively. A significantly higher sensitivity was thus obtained with the PCR method versus the culture method. Conclusion. In situations in which only a small JFS volume can be acquired, RNA-based PCR analysis increases the utility of preoperative puncture for patients who require revision surgery due to suspected PJI. Cite this article:Bone Joint Res. 2020;9(5):219–224

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To investigate the optimal thresholds and diagnostic efficacy of commonly used serological and synovial fluid detection indexes for diagnosing periprosthetic joint infection (PJI) in patients who have rheumatoid arthritis (RA).

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This study evaluated the definitions developed by the European Bone and Joint Infection Society (EBJIS) 2021, the International Consensus Meeting (ICM) 2018, and the Infectious Diseases Society of America (IDSA) 2013, for the diagnosis of periprosthetic joint infection (PJI).

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Electromagnetic induction heating has demonstrated in vitro antibacterial efficacy over biofilms on metallic biomaterials, although no in vivo studies have been published. Assessment of side effects, including thermal necrosis of adjacent tissue, would determine transferability into clinical practice. Our goal was to assess bone necrosis and antibacterial efficacy of induction heating on biofilm-infected implants in an in vivo setting.

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Fracture-related infection (FRI) is commonly classified based on the time of onset of symptoms. Early infections (< two weeks) are treated with debridement, antibiotics, and implant retention (DAIR). For late infections (> ten weeks), guidelines recommend implant removal due to tolerant biofilms. For delayed infections (two to ten weeks), recommendations are unclear. In this study we compared infection clearance and bone healing in early and delayed FRI treated with DAIR in a rabbit model.

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This aim of this study was to analyze the detection rate of rare pathogens in bone and joint infections (BJIs) using metagenomic next-generation sequencing (mNGS), and the impact of mNGS on clinical diagnosis and treatment.

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We aimed to evaluate the utility of ⁶⁸Ga-citrate positron emission tomography (PET)/CT in the differentiation of periprosthetic joint infection (PJI) and aseptic loosening (AL), and compare it with ^99mTc-methylene bisphosphonates (^99mTc-MDP) bone scan.

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Prompt and sufficient broad-spectrum empirical antibiotic treatment is key to preventing infection following open tibial fractures. Succeeding co-administration, we dynamically assessed the time for which vancomycin and meropenem concentrations were above relevant epidemiological cut-off (ECOFF) minimal inhibitory concentrations (T > MIC) in tibial compartments for the bacteria most frequently encountered in open fractures. Low and high MIC targets were applied: 1 and 4 µg/ml for vancomycin, and 0.125 and 2 µg/ml for meropenem.

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Microbiological culture is a key element in the diagnosis of periprosthetic joint infection (PJI). However, cultures of periprosthetic tissue do not have optimal sensitivity. One of the main reasons for this is that microorganisms are not released from the tissues, either due to biofilm formation or intracellular persistence. This study aimed to optimize tissue pretreatment methods in order to improve detection of microorganisms.

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This study aimed to evaluate calprotectin in synovial fluid for diagnosing chronic prosthetic joint infection (PJI) .

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The purpose of this study was to validate our hypothesis that centrifugation may eliminate false-positive leucocyte esterase (LE) strip test results caused by autoimmune diseases in the diagnosis of knee infection.