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PLoS One ; 15(12): e0243790, 2020.
Article in English | MEDLINE | ID: mdl-33306699

ABSTRACT

Pathogen identification is a critical step during diagnosis of infectious diseases. Matrix-Assisted Laser Desorption/Ionization Time-Of-Flight mass spectrometry (MALDI-TOF-MS) has become the gold standard for identification of microorganisms cultured on solid media in microbiology laboratories. Direct identification of microbes from liquid specimen, circumventing the need for the additional overnight cultivation step, has been successfully established for blood culture, urine and liquor. Here, we evaluate the ability of MALDI-TOF MS for direct identification of pathogens in synovial fluid after liquid enrichment in BacT/Alert blood culture bottles. Influence of synovial specimen quality on direct species identification with the MALDI BioTyper/Sepsityper was tested with samples inoculated from pretested native synovia with concomitant inoculation of blood or pus, or highly viscous fluid. Here, we achieved >90% concordance with culture on solid medium, and only mixed-species samples posed significant problems. Performance in routine diagnostics was tested prospectively on bottles inoculated by treating physicians on ward. There, we achieved >70% concordance with culture on solid media. The major contributors to test failure were the absence of a measurable mass signal and mixed-specimen samples. The Sepsityper workflow worked well on samples derived from BacT/Alert blood culture bottles inoculated with synovial fluid, giving concordant results to identification from solid media. Host remnant material in the inoculum, such as blood or pus, had no detrimental effect on identification score values of the BioTyper system after processing with the Sepsityper workflow, and neither had the initial viscosity of the synovial sample.


Subject(s)
Blood Culture , Infections/blood , Infections/diagnosis , Joint Diseases/blood , Joint Diseases/microbiology , Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization/methods , Humans , Time Factors
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