Abstract

Identification of pathogen(s) associated with prosthetic joint infection (PJI) is critical for patient management. Historically, many laboratories have not routinely identified organisms such as coagulase-negative staphylococci to the species level. The advent of matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS) has enhanced clinical laboratory capacity for accurate species-level identification. The aim of this study was to describe the species-level identification of microorganisms isolated from periprosthetic tissue and fluid specimens using MALDI-TOF MS alongside other rapid identification tests in a clinical microbiology laboratory. Results of rapid identification of bacteria isolated from periprosthetic joint fluid and/or tissue specimens were correlated with clinical findings at Mayo Clinic, Rochester, Minnesota, between May 2012 and May 2013. There were 178 PJI and 82 aseptic failure (AF) cases analyzed, yielding 770 organisms (median, 3/subject; range, 1–19/subject). MALDI-TOF MS was employed for the identification of 455 organisms (59%) in 197 subjects (123 PJIs and 74 AFs), with 89% identified to the species level using this technique. Gram-positive bacteria accounted for 68% and 93% of isolates in PJI and AF, respectively. However, the profile of species associated with infection compared to specimen contamination differed. Staphylococcus aureus and Staphylococcus caprae were always associated with infection, Staphylococcus epidermidis and Staphylococcus lugdunensis were equally likely to be a pathogen or a contaminant, whereas the other coagulase-negative staphylococci were more frequently contaminants. Most streptococcal and Corynebacterium isolates were pathogens. The likelihood that an organism was a pathogen or contaminant differed with the prosthetic joint location, particularly in the case of Propionibacterium acnes. MALDI-TOF MS is a valuable tool for the identification of bacteria isolated from patients with prosthetic joints, providing species-level identification that may inform culture interpretation of pathogens versus contaminants.

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