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

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. To analyze the potential role of synovial fluid peptidase activity as a measure of disease burden and predictive biomarker of progression in knee osteoarthritis (KOA). Methods. A cross-sectional study of 39 patients (women 71.8%, men 28.2%; mean age of 72.03 years (SD 1.15) with advanced KOA (Ahlbäck grade ≥ 3 and clinical indications for arthrocentesis) recruited through the (Orthopaedic Department at the Complejo Asistencial Universitario de León, Spain (CAULE)), measuring synovial fluid levels of puromycin-sensitive aminopeptidase (PSA), neutral aminopeptidase (NAP), aminopeptidase B (APB), prolyl endopeptidase (PEP), aspartate aminopeptidase (ASP), glutamyl aminopeptidase (GLU) and pyroglutamyl aminopeptidase (PGAP). Results. Synovial fluid peptidase activity varied significantly as a function of clinical signs, with differences in levels of PEP (p = 0.020), ASP (p < 0.001), and PGAP (p = 0. 003) associated with knee locking, PEP (p = 0.006), ASP (p = 0.001), GLU (p = 0.037), and PGAP (p = 0.000) with knee failure, and PEP (p = 0.006), ASP (p = 0.001), GLU (p = 0.037), and PGAP (p < 0.001) with knee effusion. Further, patients with the greatest functional impairment had significantly higher levels of APB (p = 0.005), PEP (p = 0.005), ASP (p = 0.006), GLU (p = 0.020), and PGAP (p < 0.001) activity, though not of NAP or PSA, indicating local alterations in the renin-angiotensin system. A binary logistic regression model showed that PSA was protective (p = 0.005; Exp (B) 0.949), whereas PEP (p = 0.005) and GLU were risk factors (p = 0.012). Conclusion. These results suggest synovial fluid peptidase activity could play a role as a measure of disease burden and predictive biomarker of progression in KOA. Cite this article: Bone Joint Res 2020;9(11):789–797

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

Objectives. This study looked to analyse the expression levels of microRNA-140-3p and microRNA-140-5p in synovial fluid, and their correlations to the severity of disease regarding knee osteoarthritis (OA). Methods. Knee joint synovial fluid samples were collected from 45 patients with OA of the knee (15 mild, 15 moderate and 15 severe), ten healthy volunteers, ten patients with gouty arthritis, and ten with rheumatoid arthritis. The Kellgren–Lawrence grading (KLG) was used to assess the radiological severity of knee OA, and the patients were stratified into mild (KLG < 2), moderate (KLG = 2), and severe (KLG > 2). The expression of miR-140-3p and miR-140-5p of individual samples was measured by SYBR Green quantitative polymerase chain reaction (PCR) analysis. The expression of miR-140-3p and miR-140-5p was normalised to U6 internal control using the 2. -△△CT. method. All data were processed using SPSS software. Results. Expression of both miR-140-3p and miR-140-5p was downregulated in OA synovial fluid, showing a statistical difference between the OA and non-OA group, and increased OA severity was associated with a decreased expression of miR-140-3p or miR-140-5p. The Spearman rank correlation analysis suggested that the expression of miR-140-3p or miR-140-5p was negatively correlated with OA severity. In addition, the expression of miR-140-5p was 7.4 times higher than that of miR-140-3p across all groups. Conclusion. The dysregulation of miR-140-3p and miR-140-5p in synovial fluid and their correlations with the disease severity of OA may provide an important experimental basis for OA classification, and the miR-140-3p/miR-140-5p are of great potential as biomarkers in the diagnosis and clinical management of patients with OA. Cite this article: C-M. Yin, W-C-W. Suen, S. Lin, X-M. Wu, G. Li, X-H. Pan. Dysregulation of both miR-140-3p and miR-140-5p in synovial fluid correlate with osteoarthritis severity. Bone Joint Res 2017;6:612–618. DOI: 10.1302/2046-3758.611.BJR-2017-0090.R1

Aims. The diagnosis of joint infections is an inexact science using combinations of blood inflammatory markers and microscopy, culture, and sensitivity of synovial fluid (SF). There is potential for small molecule metabolites in infected SF to act as infection markers that could improve accuracy and speed of detection. The objective of this study was to use nuclear magnetic resonance (NMR) spectroscopy to identify small molecule differences between infected and noninfected human SF. Methods. In all, 16 SF samples (eight infected native and prosthetic joints plus eight noninfected joints requiring arthroplasty for end-stage osteoarthritis) were collected from patients. NMR spectroscopy was used to analyze the metabolites present in each sample. Principal component analysis and univariate statistical analysis were undertaken to investigate metabolic differences between the two groups. Results. A total of 16 metabolites were found in significantly different concentrations between the groups. Three were in higher relative concentrations (lipids, cholesterol, and N-acetylated molecules) and 13 in lower relative concentrations in the infected group (citrate, glycine, glycosaminoglycans, creatinine, histidine, lysine, formate, glucose, proline, valine, dimethylsulfone, mannose, and glutamine). Conclusion. Metabolites found in significantly greater concentrations in the infected cohort are markers of inflammation and infection. They play a role in lipid metabolism and the inflammatory response. Those found in significantly reduced concentrations were involved in carbohydrate metabolism, nucleoside metabolism, the glutamate metabolic pathway, increased oxidative stress in the diseased state, and reduced articular cartilage breakdown. This is the first study to demonstrate differences in the metabolic profile of infected and noninfected human SF, using a noninfected matched cohort, and may represent putative biomarkers that form the basis of new diagnostic tests for infected SF. Cite this article: Bone Joint Res 2021;10(1):85–95

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. Current guidelines consider analyses of joint aspirates, including leucocyte cell count (LC) and polymorphonuclear percentage (PMN%) as a diagnostic mainstay of periprosthetic joint infection (PJI). It is unclear if these parameters are subject to a certain degree of variability over time. Therefore, the aim of this study was to evaluate the variation of LC and PMN% in patients with aseptic revision total knee arthroplasty (TKA). Methods. We conducted a prospective, double-centre study of 40 patients with 40 knee joints. Patients underwent joint aspiration at two different time points with a maximum period of 120 days in between these interventions and without any events such as other joint aspirations or surgeries. The main indications for TKA revision surgery were aseptic implant loosening (n = 24) and joint instability (n = 11). Results. Overall, 80 synovial fluid samples of 40 patients were analyzed. The average time period between the joint aspirations was 50 days (SD 32). There was a significantly higher percentage change in LC when compared to PMN% (44.1% (SD 28.6%) vs 27.3% (SD 23.7%); p = 0.003). When applying standard definition criteria, LC counts were found to skip back and forth between the two time points with exceeding the thresholds in up to 20% of cases, which was significantly more compared to PMN% for the European Bone and Joint Infection Society (EBJIS) criteria (p = 0.001), as well as for Musculoskeletal Infection Society (MSIS) (p = 0.029). Conclusion. LC and PMN% are subject to considerable variation. According to its higher interindividual variance, LC evaluation might contribute to false-positive or false-negative results in PJI assessment. Single LC testing prior to TKA revision surgery seems to be insufficient to exclude PJI. On the basis of the obtained results, PMN% analyses overrule LC measurements with regard to a conclusive diagnostic algorithm. Cite this article: Bone Jt Open 2021;2(8):566–572

Aim. One of the most accurate and inexpensive tests in detection of prosthetic joint infection (PJI) is synovial fluid white blood cell (WBC) count and differential. Since leukocytes produce many different interleukins (IL) in situation of PJI, we hypothesized that ILs could be even more accurate in detection of PJI. The aim of the study was to test, if the synovial fluid IL-6 level is superior to WBC count and differential in detection of PJI. Methods. Unselected patients undergoing total hip or knee revision surgery were prospectively included. In perioperative assessment phase, WBC count, differential and IL-6 levels of synovial fluid were measured. Patients were labelled as positive or negative according to the predefined cut-off values for IL-6 (230pg/ml) and WBC count with differential (1,7 × 10. 9. WBC/ml with ≥65% of granulocytes). During the surgery, at least 4 intraoperative samples for microbiological and one for histopathological analysis were obtained. PJI was defined as presence of sinus tract, inflammation in histopathological samples, and growth of the same microorganism in at least two or more samples of periprosthetic tissue or synovial fluid. Binary diagnostic test was performed to check the diagnostic strength of both methods in detection of PJI. Results. 49 joints of 48 patients (mean age, 71 years; 53% females) undergoing artificial hip (n = 24) or knee (n = 25) revision surgery were included. 11 joints (22%) were infected. Sensitivity of synovial fluid WBC count with differential was 82%, specificity 97%, accuracy 94%, positive and negative predictive values were 90% and 95%, respectively. Sensitivity of IL-6 level was 73%, specificity 95%, accuracy 90%, positive and negative predictive values were 80% and 92%, respectively. There was a strong statistical agreement between both tests (Kappa value=0.749) and consequently there was no significant difference in detection of PJI comparing both tests (P=0.171). Conclusion. Our study revealed that synovial fluid IL-6 level is not superior to synovial fluid WBC count with differential in detecting PJI

The paramount importance of synovial fluid in lubrication and protection of articular joints has long been recognized. Synovial fluid, a dialysate of plasma, forms an interface with both the synovium and cartilage and plays a crucial role in joint lubrication and bearing functions. In an osteoarthritic joint, damage to the articular cartilage causes modifications in the rheological properties of synovial fluid and, reducing the viscoelasticity and increasing the friction between articular surfaces. Viscosupplementation is a treatment for osteoarthritis that uses hyaluronic acid as a (visco)supplement to the diseased joint. The aim of this treatment is to restore the rheological properties of synovial fluid. Osteoarthritis is the most common disease affecting the joints in human population and among the most important causes of pain, disability and economic loss. Therefore, innovative methods are needed to more effectively treat osteoarthritis, directly addressing the disease process. Among various locomotor mechanisms that could serve to illustrate the integrated nature of functional morphology, perhaps none is more complex than the equine locomotor system. Confronting the need for evaluating the current methods to control joint disease, the horse provides an excellent animal model. As it suffers similar clinical manifestations to those seen in human, it may provide tentative biomedical extrapolations

Aim. Prosthetic joint infection (PJI) represents the second most frequent complication of total joint arthroplasty (TJA) with up to 20% of low-grade PJI treated as aseptic failure. Sensitive diagnostic criteria have been provided by EBJIS. However, to date there is no single test to reliably diagnose all PJIs. Studies of Mazzucco et al. and Fu et al. suggest that synovial fluid (SF) viscosity could be considered as an important marker for PJI. The primary aim of our study was to determine if SF viscosity is a more reliable diagnostic criterion of PJI than the SF cell count with differential (CCD), and the combined diagnostic value of SF viscosity and CCD. Method. We prospectively analysed the viscosity of SF samples obtained during TJA of hip and knee revisions. We sampled 2.5–5mL of SF for viscosity and CCD. Intraoperatively, 1mL of the sample was analysed for the CCD. The remaining SF was centrifuged for 4min at 7000rpm. The viscosity of the supernatant was determined on Ostwald viscometer as the time required to pass the viscometer at 20°C. During each surgery at least 5 microbiological and multiple histopathological samples were harvested, and explant sonication was performed. The diagnosis was based on EBJIS definition. The viscosity threshold for detecting PJI was set at 65 seconds. Results. Between December 2020 and January 2023, we analysed 65 knee and 47 hip TJA revision procedures. There were 55 septic and 57 aseptic diagnoses. As a diagnostic marker of PJI, SF viscosity achieved 100% sensitivity and 82.5% specificity, with area under the receiver operating characteristic curve (AUC) of 0.832 (95% CI 0.739, 0.925). The specificity and sensitivity of SF CCD were 98.2% and 78.2%, respectively, with AUC of 0.921 (95% CI 0.869, 0.974). Of the 10 cases incorrectly diagnosed as aseptic based on SF viscosity, 2 were acute traumas and 8 metalloses. The SF CCD in all these cases was <0.5. Of the 12 cases incorrectly diagnosed as aseptic based on SF CCD, 6 cases were culture negative, 4 C. acnes and 2 S. epidemidis isolates in microbiology. Taken together, SF viscosity and CCD achieved a combined AUC of 0.953 (95% CI 0.919, 0.987). Conclusions. Our study is the first to report that SF viscosity is more sensitive but slightly less specific for PJI than SF CCD. The study demonstrates diagnostic value of combining SF viscosity with CCD in decision making in TJA revision surgery

Aim. Synovial fluid D-lactate may be useful for diagnosing septic arthritis (SA) as this biomarker is almost exclusively produced by bacteria. We evaluated the performance of synovial fluid D-lactate and determined its optimal cut-off value for diagnosing SA. Method. Consecutive patients with suspicion of septic arthritis were prospectively included. They underwent joint aspiration and synovial fluid was collected for culture, leukocyte count and D-lactate concentration (by spectrophotometry). Youden's J statistic was used for determining optimal D-lactate cut-off value on the receiver operating characteristic (ROC) curve by maximizing sensitivity and specificity. Results. A total of 155 patients were included. Using institutional criteria, 21 patients (14%) were diagnosed with SA and 134 (86%) patients with aseptic arthropathy, out of which 43 (27%) had osteoarthrosis, 80 (52%) had rheumatic arthropathy and 11 (7%) reactive arthritis. The optimal cut-off of synovial fluid D-lactate to differentiate SA from aseptic cases was 0,035 mmol/l. Synovial fluid D-lactate had a sensitivity 90% (95% CI: 70–99%) and specificity 87% (95% CI: 80–92%) compared to leukocyte count with sensitivity 81% (95% CI: 60–95%) and specificity 83% (95% CI: 76–90%). Culture was positive in only 17 (80%) out of 21 patients with SA. Conclusions. The synovial fluid D-lactate showed high sensitivity and specificity for diagnosis of SA which was higher than the current gold standard of diagnosis (culture and leukocyte count). The high sensitivity makes this biomarker useful as a point-of-care screening test for SA

Aims. This study aimed to evaluate calprotectin in synovial fluid for diagnosing chronic prosthetic joint infection (PJI) . Methods. A total of 63 patients who were suspected of PJI were enrolled. The synovial fluid calprotectin was tested by an enzyme-linked immunosorbent assay (ELISA). Laboratory test data, such as ESR, CRP, synovial fluid white blood cells (SF-WBCs), and synovial fluid polymorphonuclear cells (SF-PMNs), were documented. Chi-squared tests were used to compare the sensitivity and specificity of calprotectin and laboratory tests. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was calculated to determine diagnostic efficacy. Results. The median calprotectin level was 776 μg/ml (interquartile range (IQR) 536.5 to 1132) in the PJI group and 54.5 μg/ml (IQR, 38.75 to 78.25) in the aseptic failure (AF) group (p < 0.05). Using a threshold of 173 ug/ml, the sensitivity was 95.2%, with a 97.6% specificity, and the AUC was 0.993. The sensitivity of calprotectin of the antibiotic-treated PJI group was 100% versus 90.9% of the non-antibiotic-treated PJI group. Although 47.6% (ten cases) of the patients in the PJI group received antibiotics before aspiration, the diagnostic efficacy of calprotectin was not affected. The sensitivity and specificity of ESR, CRP, SF-WBCs, and SF-PMNs ranged from 76.2% to 90.5% and 64.3% to 85.7%, respectively. Conclusion. Calprotectin in synovial fluid has great diagnostic efficacy for PJI diagnosisand outperformed ESR, CRP, SF-WBCs, and SF-PMNs. Cite this article: Bone Joint Res 2020;9(8):450–456

Aim. Periprosthetic joint infections (PJI) are severe complications after total joint arthroplasty (TJA). Up to now, a gold standard in the diagnostics of PJI is missing. Small extracellular vesicles (sEVs) are secreted by all types of cells and play a key role in immune response in presence of infection (1). In this prospective study, the diagnostic accuracy of sEVs in the synovial fluid to detect PJI of knee, hip and shoulder joints was investigated. We hypothesized increased surface markers of sEVs in PJI compared to aseptic complications (e.g. implant loosening, stress shielding related pain). Method. Synovial fluid from 48 patients with painful arthroplasty was examined. The distinction between aseptic and infectious cases was made on the basis of the 2018 Definition of Periprosthetic Hip and Knee Infection (2). 35 (72,9%) probands assigned to aseptic and 13 patients (27,1%) to PJI group. Immuno-fluorescence flow cytometry served to document the concentrations of CD9, CD63, CD66b, CD82 and HLA-DR on sEVs. Results. The concentration of CD9 surface marker on sEVs in synovial fluid was significantly lower (p=0.002) in PJI group than in aseptic group. In contrast, the levels of CD82 on sEVs in synovial fluid was significantly higher (p<0.0001) in the PJI group than in aseptic group. The concentrations of CD63, CD66b and HLA-DR on sEVs in synovial fluid did not differ significantly between the two cohorts (CD63: p=0.372; CD66b: p=0.634; HLA-DR: p=0.558). Conclusions. Overall, the significance of sEVs in the diagnostics of PJI is not well enough understood and the subject of current research and scientific discussion. Our data suggest, that CD82 and CD9 on sEVs in synovial fluid are promising biomarkers to differentiate between PJI and aseptic complications

Aim. Prosthetic joint infection (PJI) presents the second most common complication of total joint arthroplasty (TJA). Accumulating evidence suggests that up to 20% of aseptic failures are low-grade PJI. However, there is still no single test to reliably diagnose all PJI. In his thesis, Mazzucco emphasized the viscosity differences between normal, osteoarthritic, and rheumatic synovial fluid. Similarly, a recent study by Fu et al. reported significantly lower viscosity in patients with PJI compared to the aseptic failure cohort. The primary aim of our study was to determine whether synovial fluid viscosity is a more reliable diagnostic criterion for PJI compared to the synovial fluid cell count with differential and serum C-reactive protein (CRP) levels. Method. We prospectively analyzed the viscosity of synovial fluid samples obtained during TJA of hip and knee joint revision procedures. We sampled 2.5–5 mL of synovial fluid for viscosity measurement. The samples were centrifuged (4 min at 7000 rpm) and the resulting supernatant was immediately transferred into the Ostwald viscometer. Viscosity was derived from the time required for a given volume of synovial fluid to pass the viscometer at 20 °C. The synovial fluid samples were also analysed for their cell count with differential and serum CRP was measured. The definite diagnosis of PJI was established on basis of EBJIS criteria. For the viscosity, the threshold for detecting PJI was set at 65 seconds. Results. Between December 2020 and March 2021, we analyzed 12 knee and 11 hip TJA revision samples. These included 14 septic and 9 aseptic synovial fluid samples. The average viscometer time in the PJI group was 31s (range 20–48s) compared to 247s (range 68–616s) in the group of aseptic revision procedures. The specificity and sensitivity of our viscosity measurements were 100%. The sensitivity and specificity of cell count was 100% and 85.7%, for the synovial fluid differential they were 100% and 85.7%, and for the CRP they were 88.9% and 71.4%, respectively. Conclusions. Our study is the first to report a significant difference in synovial fluid viscosity between the PJI and the aseptic cohort. It points towards the diagnostic superiority of viscosity measurements over conventional synovial fluid cell count, synovial fluid differential, and serum CRP levels. Albeit currently limited by small sample size, the study remains ongoing

Aims. The lack of disease-modifying treatments for osteoarthritis (OA) is linked to a shortage of suitable biomarkers. This study combines multi-molecule synovial fluid analysis with machine learning to produce an accurate diagnostic biomarker model for end-stage knee OA (esOA). Methods. Synovial fluid (SF) from patients with esOA, non-OA knee injury, and inflammatory knee arthritis were analyzed for 35 potential markers using immunoassays. Partial least square discriminant analysis (PLS-DA) was used to derive a biomarker model for cohort classification. The ability of the biomarker model to diagnose esOA was validated by identical wide-spectrum SF analysis of a test cohort of ten patients with esOA. Results. PLS-DA produced a streamlined biomarker model with excellent sensitivity (95%), specificity (98.4%), and reliability (97.4%). The eight-biomarker model produced a fingerprint for esOA comprising type IIA procollagen N-terminal propeptide (PIIANP), tissue inhibitor of metalloproteinase (TIMP)-1, a disintegrin and metalloproteinase with thrombospondin motifs 4 (ADAMTS-4), monocyte chemoattractant protein (MCP)-1, interferon-γ-inducible protein-10 (IP-10), and transforming growth factor (TGF)-β3. Receiver operating characteristic (ROC) analysis demonstrated excellent discriminatory accuracy: area under the curve (AUC) being 0.970 for esOA, 0.957 for knee injury, and 1 for inflammatory arthritis. All ten validation test patients were classified correctly as esOA (accuracy 100%; reliability 100%) by the biomarker model. Conclusion. SF analysis coupled with machine learning produced a partially validated biomarker model with cohort-specific fingerprints that accurately and reliably discriminated esOA from knee injury and inflammatory arthritis with almost 100% efficacy. The presented findings and approach represent a new biomarker concept and potential diagnostic tool to stage disease in therapy trials and monitor the efficacy of such interventions. Cite this article: Bone Joint Res 2020;9(9):623–632

Aims. 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). Methods. The data from 348 patients who had RA or osteoarthritis (OA) and had previously undergone a total knee (TKA) and/or a total hip arthroplasty (THA) (including RA-PJI: 60 cases, RA-non-PJI: 80 cases; OA-PJI: 104 cases, OA-non-PJI: 104 cases) were retrospectively analyzed. A receiver operating characteristic curve was used to determine the optimal thresholds of the CRP, ESR, synovial fluid white blood cell count (WBC), and polymorphonuclear neutrophil percentage (PMN%) for diagnosing RA-PJI and OA-PJI. The diagnostic efficacy was evaluated by comparing the area under the curve (AUC) of each index and applying the results of the combined index diagnostic test. Results. For PJI prediction, the results of serological and synovial fluid indexes were different between the RA-PJI and OA-PJI groups. The optimal cutoff value of CRP for diagnosing RA-PJI was 12.5 mg/l, ESR was 39 mm/hour, synovial fluid WBC was 3,654/μl, and PMN% was 65.9%; and those of OA-PJI were 8.2 mg/l, 31 mm/hour, 2,673/μl, and 62.0%, respectively. In the RA-PJI group, the specificity (94.4%), positive predictive value (97.1%), and AUC (0.916) of synovial fluid WBC were higher than those of the other indexes. The optimal cutoff values of synovial fluid WBC and PMN% for diagnosing RA-PJI after THA were significantly higher than those of TKA. The specificity and positive predictive value of the combined index were 100%. Conclusion. Serum inflammatory and synovial fluid indexes can be used for diagnosing RA-PJI, for which synovial fluid WBC is the best detection index. Combining multiple detection indexes can provide a reference basis for the early and accurate diagnosis of RA-PJI. Cite this article: Bone Joint Res 2023;12(9):559–570

Aim. The cut-off values for synovial fluid leukocyte count and neutrophils differential (%PMN) for differentiating aseptic from septic failure in total knee arthroplasties were already defined in the past. Our goal was to determine the cut-off values for synovial fluid leukocyte count and %PMN in failed total hip arthroplasties (THA). Method. Patients undergoing revision THA were prospectively included. In perioperative assessment phase, synovial fluid leukocyte count and %PMN were determined. During the surgery, at least 4 intraoperative samples for microbiological and one for histopathological analysis were obtained. Infection was defined as presence of sinus tract, inflammation in histopathological samples, and ≥2 tissue and/or synovial fluid samples growing the same microorganism. Exclusion criteria were systemic inflammatory diseases, revision surgery performed less than 3 months from index surgery and insufficient tissue sampling. Receiver operating characteristic (ROC) curves were constructed to assess the diagnostic performance and Youden's J statistic was computed to identify optimal cut-off values. Results. During the study period (between June 2006 and June 2011) 227 revision THAs were performed by the senior author. 31 patients were excluded. 196 patients (mean age, 69 years; 68% females) with THA failure were included. Aseptic failure was diagnosed in 150 patients (76,5%) and THA infection was diagnosed in 46 patients (23,5%). Synovial fluid leukocyte counts were significantly higher in the infected group (median, 5.50×10. 6. leukocytes/ml range, 0.05 to 143.9×10. 6. leukocytes/mL) than in the aseptic group (median, 0.23×10. 6. cells/ml; range, 0 to 21.3×10. 6. leukocytes/ml, P<0,0001). The %PMN was also significantly higher in the infected group (median, 83%; range, 6% to 97%) than in the aseptic group (median, 27,5%; range, 0% to 94%, P<0,0001). A synovial fluid leukocyte count of > 1.54×10. 6. leukocytes/ml, had a sensitivity of 63%, specificity of 95%, positive and negative predictive values of 78% and 89%, respectively. A synovial fluid %PMN of > 64%, had a sensitivity of 65%, specificity of 93%, positive and negative predictive values of 73% and 90%, respectively. Conclusion. The synovial fluid leukocyte count of > 1.54×10. 6. leukocytes/ml and %PMN of > 64% are useful and reliable tests for excluding THA infection, having a negative predictive value of around 90%. This tests and calculated cut-off values are highly recommended in the diagnostic process of failed THAs

Abstract. OBJECTIVE. Knee varus malalignment increases medial knee compartment loading and is associated with knee osteoarthritis (OA) progression and severity. 1. Altered biomechanical loading and dysregulation of joint tissue biology drive OA progression, but mechanistic links between these factors are lacking. Subchondral bone structural changes are biomechanically driven, involve bone resorption, immune cell influx, angiogenesis, and sensory nerve invasion, and contribute to joint destruction and pain. 2. We have investigated mechanisms underlying this involving RANKL and alkaline phosphatase (ALP), which reflect bone resorption and mineralisation respectively. 3. and the axonal guidance factor Sema3A. Sema3A is osteotropic, expressed by mechanically sensitive osteocytes, and an inhibitor of sensory nerve, blood vessel and immune cell invasion. 4. Sema3A is also differentially expressed in human OA bone. 5. HYPOTHESIS: Medial knee compartment overloading in varus knee malalignment patients causes dysregulation of bone derived Sema3A signalling directly linking joint biomechanics to pathology and pain. METHODS. Synovial fluid obtained from 30 subjects with medial knee OA (KL grade II-IV) undergoing high tibial osteotomy surgery (HTO) was analysed by mesoscale discovery and ELISA analysis for inflammatory, neural and bone turnover markers. 11 of these patients had been previously analysed in a published patient-specific musculoskeletal model. 6. of gait estimating joint contact location, pressure, forces, and medial-lateral condyle load distribution in a published data set included in analyses. Data analysis was performed using Pearson's correlation matrices and principal component analyses. Principal Components (PCs) with eigenvalues greater than 1 were analysed. RESULTS. PC1 (32.94% of variation) and PC2 (25.79% of variation) from PCA analysis and correlation matrices separated patients according to correlated clusters of established inflammatory markers of OA pain and progression (IL6/IL8, r=0.754, p<0.001) and anti-inflammatory mediators (IL4/IL10, r=0.469, p=0.005). Bone turnover marker ALP was positively associated with KL grade (r=0.815, p=0.002) and negatively associated with IL10 (r=−0.402, p=0.018) and first peak knee loading pressures (r=−0.688, p=0.019). RANKL was positively associated with IL4 (r=0.489, p=0.003). Synovial fluid Sema3A concentrations showed separate clustering from all OA progression markers and was inversely correlated with TNF-α (r=−0.423, p=0.022) in HTO patients. Sema3A was significantly inversely correlated with total predicted force in the medial joint compartment (r=−0.621, p=0.041), mean (r=−0.63, p=0.038) and maximum (r=−0.613, p=0.045) calculated medial compartment joint pressures during the first phase and mean (r=−0.618, p=0.043) and maximum (r=−0.641, p=0.034) medial compartment joint pressures during midstance outputs of patient-specific musculoskeletal model. CONCLUSIONS. This study shows joint inflammatory status and mechanical overloading influence subchondral bone-remodelling. Synovial Sema3A concentrations are inversely correlated to patient-specific musculoskeletal model estimations of pathological medial overloading. This study reveals Sema3A as a biological mediator with capacity to induce OA pain and disease progression that is directly regulated by gait mechanical loading. Declaration of Interest. (b) declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported:I declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research project

Aim. There is growing evidence that bacteria encountered in periprosthetic joint infections (PJI) form surface-attached biofilms on prostheses, as well as biofilm aggregates embedded in synovial fluid and tissues. However, models allowing the investigation of these biofilms and the assessment of their antimicrobial susceptibility in physiologically relevant conditions are currently lacking. To address this, we developed a synthetic synovial fluid (SSF) model and we validated this model in terms of growth, aggregate formation and antimicrobial susceptibility testing, using multiple PJI isolates. Methods. 17 PJI isolates were included, belonging to Staphylococcus aureus, coagulase negative staphylococci, Cutibacterium acnes, Pseudomonas aeruginosa, enterococci, streptococci, Candida species and Enterobacterales. Growth and aggregate formation in SSF, under microaerophilic or anaerobic conditions, were evaluated using light microscopy. The biofilm preventing concentration (BPC) and minimum biofilm inhibitory concentration (MBIC) of relevant antibiotics (doxycyclin, rifampicin and oxacillin) were determined for the staphylococcal strains (n=8). To this end, a high throughput approach was developed, using a fluorescent viability resazurin staining. BPC and MBIC values were compared to the minimum inhibitory concentration (MIC) obtained with conventional methods. Results. The SSF model allowed all isolates to grow well under microaerophilic or anaerobic conditions. When cultured in SSF, all isolates formed biofilm aggregates, varying in size and shape along different species. A susceptibility testing method based on measuring resazurin-derived fluorescence was successfully developed, allowing high throughput determination of the BPC and the MBIC in SSF. For all staphylococci cultured in SSF a reduced susceptibility to the tested antibiotics was observed when compared to susceptibility data obtained in general medium. For rifampicin and doxycyclin the BPC was consistently higher than the MIC (two- to fourfold dilution difference for rifampicin and four- to sixfold dilution difference for doxycyclin). For oxacillin the MIC equaled the BPC for two isolates, while for the other isolates the BPC was higher than the MIC (two- to fourfold dilution difference). Expectedly, the MBIC was higher than the BPC and differences with the MIC were even more pronounced for all antibiotics tested (differences of six- to fourteenfold dilutions were observed). Conclusion. Our data indicate that the in vitro SSF model could provide more insight in how PJI-related pathogens form biofilms in physiologically relevant conditions. The BPC and MBIC were consistently and substantially higher than MIC. This model could be a valuable addition to evaluate the antimicrobial susceptibility in biofilms in a PJI context. Sources of funding: FWO-Vlaanderen (grant G066523N)