Annals of Clinical Microbiology and Antimicrobials · 2016 · 25 citations · 47 references
Life SciencesInfectious DiseasesMicrobiologyBacteriologyDiagnostic MicrobiologyMedical MicrobiologyBloodstream Infection DiagnosticsBloodstream InfectionsDiagnostic BacteriologyGenotypic CharacterizationMicrobial IdentificationPathogen DetectionAutomated Blood Culture SystemsBlood Culture BottlesDna Sequencing For IdentificationGenotypic IdentificationPhenotypic Bacterial IdentificationPhenotypic IdentificationPhenotypic Microbial IdentificationRapid Blood Culture Identification
BACKGROUND: Bloodstream infections are responsible for thousands of deaths each year. The rapid identification of the microorganisms causing these infections permits correct therapeutic management that will improve the prognosis of the patient. In an attempt to reduce the time spent on this step, microorganism identification devices have been developed, including the VITEK(®) 2 system, which is currently used in routine clinical microbiology laboratories. METHODS: This study evaluated the accuracy of the VITEK(®) 2 system in the identification of 400 microorganisms isolated from blood cultures and compared the results to those obtained with conventional phenotypic and genotypic methods. In parallel to the phenotypic identification methods, the DNA of these microorganisms was extracted directly from the blood culture bottles for genotypic identification by the polymerase chain reaction (PCR) and DNA sequencing. RESULTS: The automated VITEK(®) 2 system correctly identified 94.7 % (379/400) of the isolates. The YST and GN cards resulted in 100 % correct identifications of yeasts (15/15) and Gram-negative bacilli (165/165), respectively. The GP card correctly identified 92.6 % (199/215) of Gram-positive cocci, while the ANC card was unable to correctly identify any Gram-positive bacilli (0/5). CONCLUSIONS: The performance of the VITEK(®) 2 system was considered acceptable and statistical analysis showed that the system is a suitable option for routine clinical microbiology laboratories to identify different microorganisms.
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The Measurement of Observer Agreement for Categorical Data
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