Aims. This study aimed to explore the diagnostic value of synovial fluid neutrophil extracellular traps (SF-NETs) in periprosthetic joint infection (PJI)
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
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)
Aims. The
Objectives. The
Aims. Microbiological culture is a key element in the
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
Aims. 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
Objectives. Circulating exosomes represent novel biomarkers for multiple diseases. In this study, we investigated whether circulating exosome levels could be used as a diagnostic biomarker for steroid-induced osteonecrosis of the femoral head (ONFH). Methods. We assessed the serum exosome level of 85 patients with steroid-induced ONFH and 115 healthy donors by Nanosight detection. We then assessed the diagnostic accuracy of serum exosomes by receiver operating characteristic curve analysis. Results. The circulating exosome level of the ONFH group was significantly lower than that of control group. The area under the curve was 0.72, suggesting that the level of serum exosomes has moderate diagnostic accuracy for steroid-induced ONFH. Conclusion. Circulating exosome levels are valuable in the
This study aimed to evaluate calprotectin in synovial fluid for diagnosing chronic prosthetic joint infection (PJI) . 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.Aims
Methods
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
Aims. Lumbar spinal stenosis (LSS) is a common skeletal system disease that has been partly attributed to genetic variation. However, the correlation between genetic variation and pathological changes in LSS is insufficient, and it is difficult to provide a reference for the early
Aims. Socioeconomic and racial disparities have been recognized as impacting the care of patients with cancer, however there are a lack of data examining the impact of these disparities on patients with bone sarcoma. The purpose of this study was to examine socioeconomic and racial disparities that impact the oncological outcomes of patients with bone sarcoma. Methods. We reviewed 4,739 patients diagnosed with primary bone sarcomas from the Surveillance, Epidemiology and End Results (SEER) registry between 2007 and 2015. We examined the impact of race and insurance status associated with the presence of metastatic disease at
Aims. 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
Aims. Knee osteoarthritis (OA) involves a variety of tissues in the joint. Gene expression profiles in different tissues are of great importance in order to understand OA. Methods. First, we obtained gene expression profiles of cartilage, synovium, subchondral bone, and meniscus from the Gene Expression Omnibus (GEO). Several datasets were standardized by merging and removing batch effects. Then, we used unsupervised clustering to divide OA into three subtypes. The gene ontology and pathway enrichment of three subtypes were analyzed. CIBERSORT was used to evaluate the infiltration of immune cells in different subtypes. Finally, OA-related genes were obtained from the Molecular Signatures Database for validation, and diagnostic markers were screened according to clinical characteristics. Quantitative reverse transcription polymerase chain reaction (qRT‐PCR) was used to verify the effectiveness of markers. Results. C1 subtype is mainly concentrated in the development of skeletal muscle organs, C2 lies in metabolic process and immune response, and C3 in pyroptosis and cell death process. Therefore, we divided OA into three subtypes: bone remodelling subtype (C1), immune metabolism subtype (C2), and cartilage degradation subtype (C3). The number of macrophage M0 and activated mast cells of C2 subtype was significantly higher than those of the other two subtypes. COL2A1 has significant differences in different subtypes. The expression of COL2A1 is related to age, and trafficking protein particle complex subunit 2 is related to the sex of OA patients. Conclusion. This study linked different tissues with gene expression profiles, revealing different molecular subtypes of patients with knee OA. The relationship between clinical characteristics and OA-related genes was also studied, which provides a new concept for the
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
Aims. This study aimed to develop and validate a fully automated system that quantifies proximal femoral bone mineral density (BMD) from CT images. Methods. The study analyzed 978 pairs of hip CT and dual-energy X-ray absorptiometry (DXA) measurements of the proximal femur (DXA-BMD) collected from three institutions. From the CT images, the femur and a calibration phantom were automatically segmented using previously trained deep-learning models. The Hounsfield units of each voxel were converted into density (mg/cm. 3. ). Then, a deep-learning model trained by manual landmark selection of 315 cases was developed to select the landmarks at the proximal femur to rotate the CT volume to the neutral position. Finally, the CT volume of the femur was projected onto the coronal plane, and the areal BMD of the proximal femur (CT-aBMD) was quantified. CT-aBMD correlated to DXA-BMD, and a receiver operating characteristic (ROC) analysis quantified the accuracy in diagnosing osteoporosis. Results. CT-aBMD was successfully measured in 976/978 hips (99.8%). A significant correlation was found between CT-aBMD and DXA-BMD (r = 0.941; p < 0.001). In the ROC analysis, the area under the curve to diagnose osteoporosis was 0.976. The diagnostic sensitivity and specificity were 88.9% and 96%, respectively, with the cutoff set at 0.625 g/cm. 2. . Conclusion. Accurate DXA-BMD measurements and
Aims. 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
Aims. This study aimed to explore the role of small colony variants (SCVs) of Staphylococcus aureus in intraosseous invasion and colonization in patients with periprosthetic joint infection (PJI). Methods. A PJI
Aims. We aimed to evaluate the utility of . 68. Ga-citrate positron emission tomography (PET)/CT in the differentiation of periprosthetic joint infection (PJI) and aseptic loosening (AL), and compare it with . 99m. Tc-methylene bisphosphonates (. 99m. Tc-MDP) bone scan. Methods. We studied 39 patients with suspected PJI or AL. These patients underwent . 68. Ga-citrate PET/CT, . 99m. Tc-MDP three-phase bone scan and single-photon emission CT (SPECT)/CT. PET/CT was performed at ten minutes and 60 minutes after injection, respectively. Images were evaluated by three nuclear medicine doctors based on: 1) visual analysis of the three methods based on tracer uptake model, and PET images attenuation-corrected with CT and those not attenuation-corrected with CT were analyzed, respectively; and 2) semi-quantitative analysis of PET/CT: maximum standardized uptake value (SUVmax) of lesions, SUVmax of the lesion/SUVmean of the normal bone, and SUVmax of the lesion/SUVmean of the normal muscle. The final