Aims

This study aimed to evaluate the clinical application of the PJI-TNM classification for periprosthetic joint infection (PJI) by determining intraobserver and interobserver reliability. To facilitate its use in clinical practice, an educational app was subsequently developed and evaluated.

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 diagnosis and treatment.

Objectives. The aim of this study was to assess the clinical application of, and optimize the variables used in, the BACH classification of long-bone osteomyelitis. Methods. A total of 30 clinicians from a variety of specialities classified 20 anonymized cases of long-bone osteomyelitis using BACH. Cases were derived from patients who presented to specialist centres in the United Kingdom between October 2016 and April 2017. Accuracy and Fleiss’ kappa (Fκ) were calculated for each variable. Bone involvement (B-variable) was assessed further by nine clinicians who classified ten additional cases of long bone osteomyelitis using a 3D clinical imaging package. Thresholds for defining multidrug-resistant (MDR) isolates were optimized using results from a further analysis of 253 long bone osteomyelitis cases. Results. The B-variable had a classification accuracy of 77.0%, which improved to 95.7% when using a 3D clinical imaging package (p < 0.01). The A-variable demonstrated difficulty in the accuracy of classification for increasingly resistant isolates (A1 (non-resistant), 94.4%; A2 (MDR), 46.7%; A3 (extensively or pan-drug-resistant), 10.0%). Further analysis demonstrated that isolates with four or more resistant test results or less than 80% sensitive susceptibility test results had a 98.1% (95% confidence interval (CI) 96.6 to 99.6) and 98.8% (95% CI 98.1 to 100.0) correlation with MDR status, respectively. The coverage of the soft tissues (C-variable) and the host status (H-variable) both had a substantial agreement between users and a classification accuracy of 92.5% and 91.2%, respectively. Conclusions. The BACH classification system can be applied accurately by users with a variety of clinical backgrounds. Accuracy of B-classification was improved using 3D imaging. The use of the A-variable has been optimized based on susceptibility testing results. Cite this article: A. J. Hotchen, M. Dudareva, J. Y. Ferguson, P. Sendi, M. A. McNally. The BACH classification of long bone osteomyelitis. Bone Joint Res 2019;8:459–468. DOI: 10.1302/2046-3758.810.BJR-2019-0050.R1

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This study was designed to characterize the recurrence incidence and risk factors of antibiotic-loaded cement spacer (ALCS) for definitive bone defect treatment in limb osteomyelitis.

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To investigate the efficacy of ethylenediaminetetraacetic acid-normal saline (EDTA-NS) in dispersing biofilms and reducing bacterial infections.

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Bacteriophages infect, replicate inside bacteria, and are released from the host through lysis. Here, we evaluate the effects of repetitive doses of the Staphylococcus aureus phage 191219 and gentamicin against haematogenous and early-stage biofilm implant-related infections in Galleria mellonella.

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With the ageing population, fragility fractures have become one of the most common conditions. The objective of this study was to investigate whether microbiological outcomes and fracture-healing in osteoporotic bone is worse than normal bone with fracture-related infection (FRI).

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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.