Aims. Tuberculosis (TB) infection of bones and joints accounts for
6.7% of TB cases in England, and is associated with significant
morbidity and disability. Public Health England reports that patients
with TB experience delays in
Aims. This study aimed to assess the performance of an automated multiplex polymerase chain reaction (mPCR) technique for rapid
Introduction. Fracture related infection (FRI) is a challenging complication to manage in an orthoplastic setting. Consensus guidelines have been created to standardise the
Background. The
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
Aims. The International Consensus Meeting on Musculoskeletal Infection (ICM, Philadelphia 2018) recommended histology as one of the diagnostic tests although this is not routinely used in a number of UK hospitals. This study aims to explore the role of histology in the
Aim. Diagnosing periprosthetic joint infections (PJI) can be very challenging, especially infections caused by low virulence microorganisms. No single test with a 100% accuracy is available yet. Hence, different infection definitions were introduced to improve the diagnostic confidence and quality of research articles. Due to constant developments in this field, infection definitions are adopted continuously. The aim of our study was to find the most sensitive currently available infection definition among three currently used criteria (International Consensus Meeting – criteria 2018 (ICM), Infectious Diseases Society of America - criteria 2013 (IDSA), and European Bone and Joint Infection Society – criteria 2021 (EBJIS)) for the
Aim. Differentiation of infected (INF) nonunion from aseptic (AS) nonunion is crucial for the choice of intra- and postoperative treatment. Preoperative
Aim. While 16S rRNA PCR - Sanger sequencing has paved the way for the
Aim. The analysis of synovial fluid has proved to be of crucial importance in the diagnostic process of prosthetic joint infections (PJI), suggesting the presence of an infection before the microbiological culture results. In this context, several studies illustrated the efficacy of synovial calprotectin in supporting the
Background. The identification of novel biomarker which is highly specific and sensitive for periprosthetic joint (PJI) have the potential to improve diagnostic accuracy and ultimately improve patient outcomes. Thus, the aim of this systemic review is to identify and evaluate novel biomarkers for the preoperative diagnostics of PJI. Methods. MEDLINE, EMBASE, PubMed and Cochrane Library databases identified from 1. st. of January 2018 to 30. th. of September. 2022. We used “periprosthetic joint infection” OR “prosthetic joint infection” OR “periprosthetic infection” as the
Aim. Despite the availability of numerous tests, the
Aim. The
Aim. The aim of this study was to investigate the metabolomic profile of synovial fluid in periprosthetic joint infection (PJI) cases regarding a possible diagnostic approach. Also, further information about the metabolic composition of synovial fluid in PJI may point to future diagnostic and therapeutic approaches. Method. Patients with a clinical suspicion of a prosthesis infection who underwent a joint puncture in our outpatient department or ward were included. After sample preparation, the nuclear magnetic resonance (NMR) experiments were performed at 310 K on an AVANCE™ NeoBruker Ultrashield 600 MHz spectrometer. Bruker Topspin version 4.0.2 was used for NMR data acquisition. The spectra for all samples were automatically processed (exponential line broadening of 0.3 Hz), phased, and referenced using TSP at 0.0 ppm. In total, 37 metabolites were analysed using a volume of 200 µl per synovial sample. The PJI and aseptic cases were assigned according to the EBJIS criteria. Results. In total, 76 samples were included in the final analysis with 48 PJI cases and 28 aseptic cases. Five measured metabolites have shown an area under the curve (AUC) over 0.8, with Taurine (AUC 0.8558, p<0.0001) and Glutamine (AUC 0.8333, p<0.0001) showing the best diagnostic performance. When combining two metabolites, the AUC indicated even higher diagnostic performance: Glucose/Glycogen (AUC 0.9073, p<0.0001), Taurine/Mannose (AUC 0.9073, p<0.0001), Mannose/Glycogen (AUC 0.8992, p<0.0001) and Taurine/Glucose (AUC 0.8956, p<0.0001). Conclusions. While NMR as a method in PJI diagnostics is currently not broadly available for daily clinical work, our results indicate that certain synovial metabolites and their combinations can be used for PJI
Aim. The
Heterotopic ossification (HO) is a well-known complication of traumatic elbow injuries. The reported rates of post-traumatic HO formation vary from less than 5% with simple elbow dislocations, to greater than 50% in complex fracture-dislocations. Previous studies have identified fracture-dislocations, delayed surgical intervention, and terrible triad injuries as risk factors for HO formation. There is, however, a paucity of literature regarding the accuracy of diagnosing post-traumatic elbow HO. Therefore, the purpose of our study was to determine the inter-rater reliability of HO
Introduction.
Aim. The clinical relevance of microbial DNA detected via next-generation sequencing (NGS) remains unknown. This multicenter study was conceived to: 1) identify species on NGS that may predict periprosthetic joint infection (PJI), then 2) build a predictive model for PJI in a developmental cohort, and 3) validate predictive utility of the model in a separate multi-institutional cohort. Method. Fifteen institutions prospectively collected samples from 194 revision TKA and 184 revision THA between 2017–2019. Synovial fluid, tissue and swabs were obtained intraoperatively and sent to MicrogenDx (Lubbock, TX) for NGS analysis. Reimplantations were excluded. Patients were classified per the 2018 ICM definition of PJI. DNA analysis of community similarities (ANCOM) was used to identify 17 bacterial species of 294 (W-value>50) for differentiating infected vs. noninfected cases. Logistic regression with LASSO selection and random-forest algorithms were then used to build a model for predicting PJI. ICM classification was the response variable (gold-standard) and species identified through ANCOM were predictors. Patients were randomly allocated 1:1 into training and validation sets. Using the training set, a model for PJI
Aim. Culture-based conventional methods are still the gold standard to identify microorganisms in hip and knee PJIs
Background. Septic arthritis diagnostic is an emergency which implies a treatment with antibiotics and hospitalization. The