Aim. One of the most accurate and inexpensive tests in detection of prosthetic joint infection (PJI) is
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
Aim.
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
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
Aim. The cut-off values for
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
Aim. To evaluate the analytical performance of
Aims. This study aimed to assess the performance of an automated multiplex polymerase chain reaction (mPCR) technique for rapid diagnosis of native joint septic arthritis. Patients and Methods. Consecutive patients with suspected septic arthritis undergoing aseptic diagnostic joint aspiration were included. The aspirate was used for analysis by mPCR and conventional microbiological analysis. A joint was classed as septic according to modified Newman criteria. Based on receiver operating characteristic (ROC) analysis, the area under the ROC curve (AUC) values of the mPCR and the
Aim. Our goal is to assess diagnostic accuracy of
Aim. We report on the performance of a simple algorithm using a combination of
Aim. Bone and Joint Infections (BJIs) present with non-specific symptoms and can be caused by a wide variety of bacteria and fungi, including many anaerobes and microorganisms that can be challenging to culture or identify by traditional microbiological methods. Clinicians currently rely primarily on culture to identify the pathogen(s) responsible for infection. The BioFire. ®. FilmArray. ®. Bone and Joint Infection (BJI) Panel (BioFire Diagnostics, Salt Lake City, UT) was designed to detect 15 gram-positive (seven anaerobes), 14 gram-negative bacteria (one anaerobe), two yeast, and eight antimicrobial resistance (AMR) genes from
Staphylococcus aureus is the most frequently isolated organism in periprosthetic joint infections. The mechanism by which
Background. The diagnosis of Periprosthetic Joint Infection (PJI) is a considerable challenge in total joint arthroplasty. The mainstay for diagnosis of PJI is a combination of serological markers, including C-reactive protein (CRP), along with joint aspirate for white cell count, differential and culture. The aim of this study was to examine the use of
Aim. To evaluate a panel of peripheral blood and
Objectives. The efficacy of Gram-stain microscopy for diagnosis of septic arthritis is fundamentally limited by an inherent false-negative rate of 25–50%. The aim of this study was to calculate the sensitivity of Gram-stain microscopy of
Aim. Surgical and antimicrobial treatment of periprosthetic joint infections (PJI) depends largely on the causative pathogen. We assessed the pathogen detection rates and the concordance of preoperative
The diagnosis of prosthetic-joint infection (PJI) is challenging, as bacteria adhere on implant and form biofilm. Therefore, current diagnostic methods, such as preoperative culture of joint aspirate have limited sensitivity with false-negative results. Aim. To evaluate the performance of measurement
Aim. Our goal is to increase diagnostic accuracy of
We studied twelve parameters (physical appearance, mucin clot, fibrin clot, white cell count, differential count, red blood cell count, gram stain for bacteria, crystal microscopy, aerobic bacterial culture, anaerobic bacterial culture and ratio between synovial sugar and blood sugar) in over 300 samples of