Aims. This study aimed to determine the expression and clinical significance of a cartilage protein, cartilage oligomeric matrix protein (COMP), in knee osteoarthritis (OA) patients. Methods. A total of 270 knee OA patients and 93 healthy controls were recruited. COMP messenger RNA (mRNA) and protein levels in serum, synovial fluid, synovial tissue, and fibroblast-like synoviocytes (FLSs) of knee OA patients were determined using enzyme-linked immunosorbent assay, real-time polymerase chain reaction, and immunohistochemistry. Results. COMP protein levels were significantly elevated in serum and synovial fluid of knee OA patients, especially those in the advanced stages of the disease. Serum COMP was significantly correlated with radiological severity as well as measures of body composition, physical performance, knee pain, and disability. Receiver operating characteristic curve analysis unveiled a diagnostic value of serum COMP as a biomarker of knee OA (41.64 ng/ml, area under the curve (AUC) = 1.00), with a sensitivity of 99.6% and a specificity of 100.0%. Further analysis uncovered that COMP mRNA expression was markedly upregulated in the inflamed synovium of knee OA, consistent with immunohistochemical staining revealing localization of COMP protein in the lining and sub-lining layers of knee OA inflamed synovium. Most notably, relative COMP mRNA expression in knee OA synovium was positively associated with its protein levels in serum and synovial fluid of knee OA patients. In human knee OA FLSs activated with tumour necrosis factor-alpha, COMP mRNA expression was considerably up-regulated in a time-dependent manner. Conclusion. All results indicate that COMP might serve as a supportive diagnostic marker for knee OA in conjunction with the standard diagnostic methods. Cite this article: Bone Joint Res 2024;13(6):261–271

Objectives. The diagnosis of periprosthetic joint infection (PJI) is difficult and requires a battery of tests and clinical findings. The purpose of this review is to summarize all current evidence for common and new serum biomarkers utilized in the diagnosis of PJI. Methods. We searched two literature databases, using terms that encompass all hip and knee arthroplasty procedures, as well as PJI and statistical terms reflecting diagnostic parameters. The findings are summarized as a narrative review. Results. Erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) were the two most commonly published serum biomarkers. Most evidence did not identify other serum biomarkers that are clearly superior to ESR and CRP. Other serum biomarkers have not demonstrated superior sensitivity and have failed to replace CRP and ESR as first-line screening tests. D-dimer appears to be a promising biomarker, but more research is necessary. Factors that influence serum biomarkers include temporal trends, stage of revision, and implant-related factors (metallosis). Conclusion. Our review helped to identify factors that can influence serum biomarkers’ level changes; the recognition of such factors can help improve their diagnostic utility. As such, we cannot rely on ESR and CRP alone for the diagnosis of PJI prior to second-stage reimplantation, or in metal-on-metal or corrosion cases. The future of serum biomarkers will likely shift towards using genomics and proteomics to identify proteins transcribed via messenger RNA in response to infection and sepsis. Cite this article: A. Saleh, J. George, M. Faour, A. K. Klika, C. A. Higuera. Serum biomarkers in periprosthetic joint infections. Bone Joint Res 2018;7:85–93. DOI: 10.1302/2046-3758.71.BJR-2017-0323

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

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. The aim of this study was to further evaluate the accuracy of ten promising synovial biomarkers (bactericidal/permeability-increasing protein (BPI), lactoferrin (LTF), neutrophil gelatinase-associated lipocalin (NGAL), neutrophil elastase 2 (ELA-2), α-defensin, cathelicidin LL-37 (LL-37), human β-defensin (HBD-2), human β-defensin 3 (HBD-3), D-dimer, and procalcitonin (PCT)) for the diagnosis of periprosthetic joint infection (PJI), and to investigate whether inflammatory joint disease (IJD) activity affects their concentration in synovial fluid. Methods. We included 50 synovial fluid samples from patients with (n = 25) and without (n = 25) confirmed PJI from an institutional tissue bank collected between May 2015 and December 2016. We also included 22 synovial fluid samples aspirated from patients with active IJD presenting to Department of Rheumatology, the first Medical Centre, Chinese PLA General Hospital. Concentrations of the ten candidate biomarkers were measured in the synovial fluid samples using standard enzyme-linked immunosorbent assays (ELISA). The diagnostic accuracy was evaluated by receiver operating characteristic (ROC) curves. Results. BPI, LTF, NGAL, ELA-2, and α-defensin were well-performing biomarkers for detecting PJI, with areas under the curve (AUCs) of 1.000 (95% confidence interval, 1.000 to 1.000), 1.000 (1.000 to 1.000), 1.000 (1.000 to 1.000), 1.000 (1.000 to 1.000), and 0.998 (0.994 to 1.000), respectively. The other markers (LL-37, HBD-2, D-dimer, PCT, and HBD-3) had limited diagnostic value. For the five well-performing biomarkers, elevated concentrations were observed in patients with active IJD. The original best thresholds determined by the Youden index, which discriminated PJI cases from non-PJI cases could not discriminate PJI cases from active IJD cases, while elevated thresholds resulted in good performance. Conclusion. BPI, LTF, NGAL, ELA-2, and α-defensin demonstrated excellent performance for diagnosing PJI. However, all five markers showed elevated concentrations in patients with IJD activity. For patients with IJD, elevated thresholds should be considered to accurately diagnose PJI. Cite this article: Bone Joint J 2021;103-B(1):32–38

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. Prosthetic joint infection (PJI) remains a major clinical challenge. Neutrophil CD64 index, Fc-gamma receptor 1 (FcγR1), plays an important role in mediating inflammation of bacterial infections and therefore could be a valuable biomarker for PJI. The aim of this study is to compare the neutrophil CD64 index in synovial and blood diagnostic ability with the standard clinical tests for discrimination PJI and aseptic implant failure. Methods. A total of 50 patients undergoing revision hip and knee arthroplasty were enrolled into a prospective study. According to Musculoskeletal Infection Society (MSIS) criteria, 25 patients were classified as infected and 25 as not infected. In all patients, neutrophil CD64 index and percentage of polymorphonuclear neutrophils (PMN%) in synovial fluid, serum CRP, ESR, and serum CD64 index levels were measured preoperatively. Receiver operating characteristic (ROC) curves and the area under the curve (AUC) were analyzed for each biomarker. Results. Serum CD64 index showed no significant difference between the two groups (p = 0.091). Synovial fluid CD64 index and PMN% discriminated good differentiation between groups of PJI and aseptic failure with AUC of 0.946 (95% confidence interval (CI) 0.842 to 0.990) and 0.938 (95% CI 0.832 to 0.987) separately. The optimal threshold value of synovial CD64 index for the diagnosis of PJI was 0.85, with a sensitivity of 92.00%, a specificity of 96.00%, and diagnostic odds ratio (DOR) of 227.11. Conclusion. The present study demonstrates that CD64 index in synovial fluid could be a promising laboratory marker for screening PJI. The cut-off values of 0.85 for synovial CD64 index has the potential to distinguish aseptic failure from PJI. Cite this article: Bone Joint J 2020;102-B(4):463–469

Aim. In the diagnosis of prosthetic joint infection (PJI), many biomarkers have shown a sound performance in terms of accuracy, sensitivity and specificity. In this study we aimed to test the frequently used serum biomarkers C-reactive Protein (CRP), Fibrinogen, Leukocytes, Interleukin-6 (IL-6), Interferon alpha (IF-alpha) and Procalcitonin (PCT) regarding these qualities. Following that, the optimal multi-biomarker combination was calculated to further improve the diagnostic performance. Method. 124 knee or hip revision arthroplasty procedures were prospectively investigated focusing on preoperative serum blood levels of CRP, Fibrinogen, Leukocytes, IL-6, IF-alpha and PCT. The presence of PJI was determined by a blinded researcher. Logistic regression with lasso-regularization was used for the biomarkers and all their ratios. Following cross-validation on a training sample set to get optimal performance estimates, we performed the final model on a test set (25% of all samples). Results. Out of all evaluated biomarkers, CRP (AUC 0.91, p-value 0.03) and Fibrinogen (AUC 0.93, p-value 0.02) had the best performances. The optimal combination when testing multiple biomarkers in 32 cross-validation runs was calculated including Fibrinogen, CRP, the ratio of Fibrinogen to CRP and the ratio of serum Thrombocytes to CRP (AUC 0.92, accuracy 0.77, specificity 0.92, sensitivity 0.68, cut-off 0.63, p-value 0.04). Conclusions. It was not possible to increase the diagnostic performance by combining multiple biomarkers using sophisticated statistical methods. The calculated Multi-biomarker models did not improve the AUC, accuracy, sensitivity and specificity when compared to single biomarkers

Aims. Metabolic profiling is a top-down method of analysis looking at metabolites, which are the intermediate or end products of various cellular pathways. Our primary objective was to perform a systematic review of the published literature to identify metabolites in human synovial fluid (HSF), which have been categorized by metabolic profiling techniques. A secondary objective was to identify any metabolites that may represent potential biomarkers of orthopaedic disease processes. Methods. A systematic review was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines using the MEDLINE, Embase, PubMed, and Cochrane databases. Studies included were case series, case control series, and cohort studies looking specifically at HSF. Results. The primary analysis, which pooled the results from 17 published studies and four meeting abstracts, identified over 200 metabolites. Seven of these studies (six published studies, one meeting abstract) had asymptomatic control groups and collectively suggested 26 putative biomarkers in osteoarthritis, inflammatory arthropathies, and trauma. These can broadly be categorized into amino acids plus related metabolites, fatty acids, ketones, and sugars. Conclusion. The role of metabolic profiling in orthopaedics is fast evolving with many metabolites already identified in a variety of pathologies. However, these results need to be interpreted with caution due to the presence of multiple confounding factors in many of the studies. Future research should include largescale epidemiological metabolic profiling studies incorporating various confounding factors with appropriate statistical analysis to account for multiple testing of the data. Cite this article:Bone Joint Res. 2020;9(3):108–119

INTRODUCTION:. The diagnosis of periprosthetic joint infection (PJI) remains a serious challenge. Based on previous work, we believe that biomarkers will become the mainstay of diagnosing PJI in the future. We report on completion of our 8 year comprehensive biomarker program, evaluating the diagnostic profile of the 15 most promising synovial fluid biomarkers. METHODS:. Synovial fluid was prospectively collected from 99 patients being evaluated for infection in the setting of revision hip or knee arthroplasty. All synovial fluid samples were tested by immunoassay for 15 putative biomarkers that were developed and optimized specifically for use in synovial fluid. Sensitivity, specificity and receiver operating Characteristic (ROC) curve analysis were performed for all biomarkers. RESULTS:. The MSIS criteria, including cultures, CRP, ESR, fluid WBC, PMN%, and histology, was used to classify 30 PJIs and 69 cases of aseptic failure. Four synovial fluid biomarkers (alpha-defensin, bactericidal/permeability increasing protein, neutrophil gelatinase-associated lipocalin, and resistin) correctly predicted the MSIS classification of all patients in this study, exhibiting an AUC of 1.0 with >98% sensitivity and specificity for the diagnosis of PJI. Eight other biomarkers exhibited an AUC of >0.9. These results all outperformed the tests for serum CRP (specificity 87%, sensitivity 96%) and ESR (specificity 80%, sensitivity 93%). Interestingly, the Pearson correlations comparing the biomarkers to each other and to the synovial fluid WBC in the group of infected samples revealed only weak correlations, demonstrating that these biomarkers are not simply inflammatory biomarkers. DISCUSSION AND CONCLUSION:. A comprehensive biomarker program has led to the identification of several synovial fluid biomarkers that appear to be diagnostic for PJI. The four top biomarkers are proteins that have known functional roles in the cellular response to pathogens. These biomarkers outperform our currently utilized serum tests and can be used to develop rapid bedside immunoassays for PJI

Aims. The diagnosis of periprosthetic joint infection (PJI) has always been challenging. Recently, D-dimer has become a promising biomarker in diagnosing PJI. However, there is controversy regarding its diagnostic value. We aim to investigate the diagnostic value of D-dimer in comparison to ESR and CRP. Methods. PubMed, Embase, and the Cochrane Library were searched in February 2020 to identify articles reporting on the diagnostic value of D-dimer on PJI. Pooled analysis was conducted to investigate the diagnostic value of D-dimer, CRP, and ESR. Results. Six studies with 1,255 cases were included (374 PJI cases and 881 non-PJI cases). Overall D-dimer showed sensitivity of 0.80 (95% confidence interval (CI) 0.69 to 0.87) and specificity of 0.76 (95% CI 0.63 to 0.86). Sub-group analysis by excluding patients with thrombosis and hyper-coagulation disorders showed sensitivity of 0.82 (95% CI 0.70 to 0.90) and specificity of 0.80 (95% CI 0.70 to 0.88). Serum D-dimer showed sensitivity of 0.85 (95% CI 0.76 to 0.92), specificity of 0.83 (95% CI 0.74 to 0.90). Plasma D-dimer showed sensitivity of 0.67 (95% CI 0.60 to 0.73), specificity of 0.58 (95% CI 0.45 to 0.72). CRP showed sensitivity of 0.78 (95% CI 0.72 to 0.83), specificity of 0.81 (95% CI 0.72 to 0.87). ESR showed sensitivity of 0.68 (95% CI 0.63 to 0.73), specificity of 0.83 (95% CI 0.78 to 0.87). Conclusion. In patients without thrombosis or a hyper-coagulation disorder, D-dimer has a higher diagnostic value compared to CRP and ESR. In patients with the aforementioned conditions, D-dimer has higher sensitivity but lower specificity compared to ESR and CRP. We do not recommend the use of serum D-dimer in patients with thrombosis and hyper-coagulation disorders for diagnosing PJI. Serum D-dimer may perform better than plasma D-dimer. Further studies are needed to compare serum D-dimer and plasma D-dimer in arthroplasty patients. Cite this article: Bone Joint Res 2020;9(10):701–708

Introduction. Gelsolin (GSN) is a protein whose function in the cytoplasm is to regulate intracellular actin assembly, while circulating plasma GSN has been implicated in the clearance of cellular byproducts via the body's scavenger system. In knee synovial fluid, GSN appears to be protective of inflammation as lower levels have been found in patients with rheumatoid arthritis while higher levels have been demonstrated in hypersensitivity reactions to metallic implants. The purpose of this study is to define the role of GSN in painful total knee arthroplasty (TKA) patients as a biomarker to distinguish septic from aseptic diagnoses. Methods. After Institutional Review Board (IRB) approval, 50 patients were enrolled in the study into two cohorts. 25 patients presented with a painful TKA and 25 patients had a painful native knee with primary osteoarthritis (OA). Synovial fluid was obtained from each patient's affected knee. Appropriate lab and culture data was also obtained from the painful TKA group. An ELISA was used to determine GSN levels and the groups were compared. Two tailed Student's t tests were used to compare means while Pearson's Correlation Coefficient and linear regression analyses were used to determine association between laboratory findings and GSN levels. Results. 11 of 25 knees in the TKA group had culture positive aspirations while the remaining 14 were sterile and determined to have aseptic component loosening. There was a significant difference in the GSN levels of the entire TKA cohort when compared to the OA group (TKA = 41,218 ng/mL; OA = 84,188 ng/mL; p = 0.002), with no difference noted between the infected and sterile TKA patients (infected = 43,210 ng/mL; sterile = 39,654 ng/mL; p = 0.63). There was a high correlation of ESR and CRP to GSN in the infected TKA group (r = 0.66 and 0.93 respectively; [Fig. 1 and 2]). Discussion. GSN levels correlate highly to other commonly used markers of periprosthetic joint infection (PJI), with overall lower levels seen in PJI when compared to patients with OA. However, GSN levels may be indicative of a painful total knee arthroplasty for multiple reasons, and further study is needed to delineate its role as a biomarker of PJI as well as specific aseptic TKA diagnoses

Aims. Osteoporosis is common in total hip arthroplasty (THA) patients. It plays a substantial factor in the surgery’s outcome, and previous studies have revealed that pharmacological treatment for osteoporosis influences implant survival rate. The purpose of this study was to examine the prevalence of and treatment rates for osteoporosis prior to THA, and to explore differences in osteoporosis-related biomarkers between patients treated and untreated for osteoporosis. Methods. This single-centre retrospective study included 398 hip joints of patients who underwent THA. Using medical records, we examined preoperative bone mineral density measures of the hip and lumbar spine using dual energy X-ray absorptiometry (DXA) scans and the medications used to treat osteoporosis at the time of admission. We also assessed the following osteoporosis-related biomarkers: tartrate-resistant acid phosphatase 5b (TRACP-5b); total procollagen type 1 amino-terminal propeptide (total P1NP); intact parathyroid hormone; and homocysteine. Results. The prevalence of DXA-proven hip osteoporosis (T-score ≤ -2.5) among THA patients was 8.8% (35 of 398). The spinal osteoporosis prevalence rate was 4.5% (18 of 398), and 244 patients (61.3%; 244 of 398) had osteopenia (-2.5 < T-score ≤ -1) or osteoporosis of either the hip or spine. The rate of pharmacological osteoporosis treatment was 22.1% (88 of 398). TRACP-5b was significantly lower in the osteoporosis-treated group than in the untreated group (p < 0.001). Conclusion. Osteoporosis is common in patients undergoing THA, but the diagnosis and treatment for osteoporosis were insufficient. The lower TRACP-5b levels in the osteoporosis-treated group — that is, osteoclast suppression — may contribute to the reduction of the postoperative revision rate after THA. Cite this article: Bone Joint Res 2022;11(12):873–880

Objective: To challenge the validity of using biomarker concentrations in synovial fluid for the assessment of joint pathology. Hypothesis: Synovial fluid biomarker concentrations are influenced by both cartilage and synovial fluid volumes. Methods: Synovial fluid volumes were determined from the equine metacarpophalangeal (MCP), proximal inter-phalangeal (PIP) and distal interphalangeal (DIP) joints, which have different disease prevalences. Chondrocyte density was calculated from a defined site in each joint. Cartilage volume was measured by novel application of Peripheral Quantitative Computed Tomography (pQCT). Cartilage oligomeric matrix protein (COMP), glycos-aminoglycans (GAG) and total protein (TP) concentrations were measured and then adjusted for cartilage and synovial fluid volume and compared between joints. Results: Mean synovial fluid volume was significantly greater in the MCP than the distal joints (p< 0.0001) (3.2 ±0.5ml, 0.5 ±0.1ml and 0.6 ±0.1ml respectively). In contrast, the DIP had the greatest cartilage volume compared to the proximal joints (5360 ±667mm3 2640mm3, 1940 ±331mm3 respectively). There was no significant difference in the cartilage cellularity between all joints. The DIP had higher TP, COMP and GAG concentrations, however, when values were expressed per unit cartilage volume the opposite was found, with the MCP then exhibiting significantly higher concentrations. Conclusions: These data show the joint with the highest prevalence to osteoarthritis has the lowest biomarker synovial fluid concentrations but the highest biomarker levels per unit cartilage, suggesting a higher release. These results indicate that meaningful interpretation of biomarkers in synovial fluid require consideration of both fluid and cartilage volume

Aim. The diagnosis of periprosthetic joint infection (PJI) remains a clinical dilemma, since presentations of PJI usually greatly overlap with aseptic failure (AF). The aim of this study is to evaluate the values of plasma fibrinogen, individually or in combination with CRP, ESR and WBC, for distinguishing PJI from AF. Method. We retrospectively enrolled 357 cases who underwent revision hip or knee arthroplasties in the Third Affiliated Hospital of Southern Medical University, Sun Yat-sen Memorial Hospital and the First Affiliated Hospital of Sun Yat-sen University from January 2013 to December 2021, including 197 AF, 116 PJI and 44 reimplantation. The diagnostic capacity of preoperative fibrinogen, CRP, ESR and WBC as well as their combinations for differentiating PJI from AF were assessed by ROC curves. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy were calculated according to the optimal cutoff value based on the Youden index. All biomarkers were further investigated for their potential ability to predict optimal timing of reimplantation as well as their diagnostic capacity in the subgroups of the knee and hip PJI. Furthermore, the correlations among fibrinogen, CRP and ESR in the patients with PJI and AF were analyzed to further evaluate the potential capacity of fibrinogen in the diagnosis of PJI. Results. The levels of fibrinogen, CRP, ESR and WBC were significantly higher in PJI group than in AF group. ROC analyses showed that the AUCs of fibrinogen, CRP, ESR and WBC were 0.879, 0.903, 0.879 and 0.685, respectively. The optimal threshold of fibrinogen is 4.04 g/L (74.1% sensitivity, 85.6% specificity, 76.1% PPV, 85.0% NPV and 81.8% accuracy). Combining fibrinogen with CRP and/or ESR (AUC: 0.903∼0.914) yielded almost equivalent diagnostic efficiency compared with the combination of CRP and ESR (AUC: 0.910). Besides, fibrinogen yielded AUCs of 0.869 (cutoff: 3.44 g/L) and 0.887 (cutoff: 4.12 g/L) in the hip and knee subgroups, with higher specificity and PPV of 93.1% and 96.1% in the knee PJI. Intriguingly, as for the cases with CRP < 10mg/L and ESR ≧ 30 mm/h, the specificity and NPV of fibrinogen for diagnosing PJI were 92.2% and 83.9%. Conclusions. Plasma fibrinogen is considered as a potential first-line screening marker for PJI detection and timing of reimplantation. As for the patients with an increased ESR but normal CRP, a low fibrinogen level (below 4.04 g/L) is more likely to rule out PJI

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. This study aimed to explore the biological and clinical importance of dysregulated key genes in osteoarthritis (OA) patients at the cartilage level to find potential biomarkers and targets for diagnosing and treating OA. Methods. Six sets of gene expression profiles were obtained from the Gene Expression Omnibus database. Differential expression analysis, weighted gene coexpression network analysis (WGCNA), and multiple machine-learning algorithms were used to screen crucial genes in osteoarthritic cartilage, and genome enrichment and functional annotation analyses were used to decipher the related categories of gene function. Single-sample gene set enrichment analysis was performed to analyze immune cell infiltration. Correlation analysis was used to explore the relationship among the hub genes and immune cells, as well as markers related to articular cartilage degradation and bone mineralization. Results. A total of 46 genes were obtained from the intersection of significantly upregulated genes in osteoarthritic cartilage and the key module genes screened by WGCNA. Functional annotation analysis revealed that these genes were closely related to pathological responses associated with OA, such as inflammation and immunity. Four key dysregulated genes (cartilage acidic protein 1 (CRTAC1), iodothyronine deiodinase 2 (DIO2), angiopoietin-related protein 2 (ANGPTL2), and MAGE family member D1 (MAGED1)) were identified after using machine-learning algorithms. These genes had high diagnostic value in both the training cohort and external validation cohort (receiver operating characteristic > 0.8). The upregulated expression of these hub genes in osteoarthritic cartilage signified higher levels of immune infiltration as well as the expression of metalloproteinases and mineralization markers, suggesting harmful biological alterations and indicating that these hub genes play an important role in the pathogenesis of OA. A competing endogenous RNA network was constructed to reveal the underlying post-transcriptional regulatory mechanisms. Conclusion. The current study explores and validates a dysregulated key gene set in osteoarthritic cartilage that is capable of accurately diagnosing OA and characterizing the biological alterations in osteoarthritic cartilage; this may become a promising indicator in clinical decision-making. This study indicates that dysregulated key genes play an important role in the development and progression of OA, and may be potential therapeutic targets. Cite this article: Bone Joint Res 2024;13(2):66–82

Aims. Accurate diagnosis of chronic periprosthetic joint infection (PJI) presents a significant challenge for hip surgeons. Preoperative diagnosis is not always easy to establish, making the intraoperative decision-making process crucial in deciding between one- and two-stage revision total hip arthroplasty (THA). Calprotectin is a promising point-of-care novel biomarker that has displayed high accuracy in detecting PJI. We aimed to evaluate the utility of intraoperative calprotectin lateral flow immunoassay (LFI) in THA patients with suspected chronic PJI. Methods. The study included 48 THAs in 48 patients with a clinical suspicion of PJI, but who did not meet European Bone and Joint Infection Society (EBJIS) PJI criteria preoperatively, out of 105 patients undergoing revision THA at our institution for possible PJI between November 2020 and December 2022. Intraoperatively, synovial fluid calprotectin was measured with LFI. Cases with calprotectin levels ≥ 50 mg/l were considered infected and treated with two-stage revision THA; in negative cases, one-stage revision was performed. At least five tissue cultures were obtained; the implants removed were sent for sonication. Results. Calprotectin was positive (≥ 50 mg/l) in 27 cases; out of these, 25 had positive tissue cultures and/or sonication. Calprotectin was negative in 21 cases. There was one false negative case, which had positive tissue cultures. Calprotectin showed an area under the curve of 0.917, sensitivity of 96.2%, specificity of 90.9%, positive predictive value of 92.6%, negative predictive value of 95.2%, positive likelihood ratio of 10.6, and negative likelihood ratio of 0.04. Overall, 45/48 patients were correctly diagnosed and treated by our algorithm, which included intraoperative calprotectin measurement. This yielded a 93.8% concordance with postoperatively assessed EBJIS criteria. Conclusion. Calprotectin can be a valuable tool in facilitating the intraoperative decision-making process for cases in which chronic PJI is suspected and diagnosis cannot be established preoperatively. Cite this article: Bone Joint J 2024;106-B(5 Supple B):118–124

Aim. Diagnosis of periprosthetic joint infection (PJI) is still challenging due to limitations of available diagnostic tests. Many efforts are ongoing to find out novel methods for PJI diagnosis. Recently, several studies have shown a role of the long pentraxin PTX3 as a biomarker in inflammatory diseases and infections. This pilot diagnostic study evaluated the diagnostic ability of synovial fluid and serum PTX3 for the infection of total hip arthroplasty (THA) and total knee arthroplasty (TKA). Method. Consecutive patients undergoing revision surgery for painful THA or TKA were enrolled. Patients with antibiotic therapy suspended for less than 2 weeks prior to surgery and patients eligible for spacer removal and prosthesis re-implantation were excluded. Quantitative assessment of synovial fluid and serum PTX3 was performed with ELISA method. Musculoskeletal Infection Society (MSIS) criteria were used as reference standard for diagnosis of PJI. Continuous data values were compared for statistical significance with univariate unpaired, 2-tailed Student's t-tests. Receiver operating characteristic (ROC) curve analyses was performed to assess the ability of serum and synovial fluid PTX3 concentration to determine the presence of PJI. Youden's J statistic was used to determine optimum threshold values for the diagnosis of infection. Sensitivity (Se), specificity (Sp), positive (PPV) and negative (NPV) predictive values, positive (LR+) and negative (LR-) likelihood ratio, area under the ROC curve (AUC) were calculated. Results. Sixty-two patients (M:F=28:34) with a mean age of 64 years (40–78) underwent revision of THA (n=52) or TKA (n=10). According with MSIS criteria, 10 cases were categorized as septic and 52 as aseptic revisions. The average synovial fluid concentration of PTX3 was significantly higher in patients with PJI compared to patients undergoing aseptic revision (23,56 ng/mL vs 3,71 ng/mL; P=0.0074). There was no significant difference in terms of serum concentration of PTX3 between the two groups. Synovial fluid PTX3 demonstrated an AUC of 0.93 (95%IC 0.86–0.97) with Se 100%, Sp 85%, PPV 55%, NPV 100%, LR+ 6.6 and LR- <0.01 for a threshold value of 3 ng/mL. Serum PTX3 demonstrated an AUC of 0.59 (95%IC 0.38–0.8) with Se 78%, Sp 50%, PPV 25%, NPV 90%, LR+ 1.56 and LR- 0.44 for a threshold value of 3 ng/mL. Conclusions. Synovial PTX3 demonstrated a strong diagnostic ability for PJI. PTX3 could represent a useful biomarker for detection of PJI in patients undergoing revision surgery for painful THA or TKA. Larger diagnostic studies are required to confirm these preliminary data

Aims. This study aimed, through bioinformatics analysis, to identify the potential diagnostic markers of osteoarthritis, and analyze the role of immune infiltration in synovial tissue. Methods. The gene expression profiles were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified by R software. Functional enrichment analyses were performed and protein-protein interaction networks (PPI) were constructed. Then the hub genes were screened. Biomarkers with high value for the diagnosis of early osteoarthritis (OA) were validated by GEO datasets. Finally, the CIBERSORT algorithm was used to evaluate the immune infiltration between early-stage OA and end-stage OA, and the correlation between the diagnostic marker and infiltrating immune cells was analyzed. Results. A total of 88 DEGs were identified. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses indicated that DEGs were significantly enriched in leucocyte migration and interleukin (IL)-17 signalling pathways. Disease ontology (DO) indicated that DEGs were mostly enriched in rheumatoid arthritis. Six hub genes including FosB proto-oncogene, AP-1 transcription factor subunit (FOSB); C-X-C motif chemokine ligand 2 (CXCL2); CXCL8; IL-6; Jun proto-oncogene, AP-1 transcription factor subunit (JUN); and Activating transcription factor 3 (ATF3) were identified and verified by GEO datasets. ATF3 (area under the curve = 0.975) turned out to be a potential biomarker for the diagnosis of early OA. Several infiltrating immune cells varied significantly between early-stage OA and end-stage OA, such as resting NK cells (p = 0.016), resting dendritic cells (p = 0.043), and plasma cells (p = 0.043). Additionally, ATF3 was significantly correlated with resting NK cells (p = 0.034), resting dendritic cells (p = 0.026), and regulatory T cells (Tregs, p = 0.018). Conclusion. ATF3 may be a potential diagnostic marker for early diagnosis and treatment of OA, and immune cell infiltration provides new perspectives for understanding the mechanism during OA progression. Cite this article: Bone Joint Res 2022;11(9):679–689