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Annals of Laboratory Medicine ; : 111-117, 2014.
Article in English | WPRIM | ID: wpr-110414

ABSTRACT

BACKGROUND: Microbiological laboratories seek technologically innovative solutions to cope with large numbers of samples and limited personnel and financial resources. One platform that has recently become available is the Kiestra Total Laboratory Automation (TLA) system (BD Kiestra B.V., the Netherlands). This fully automated sample processing system, equipped with digital imaging technology, allows superior detection of microbial growth. Combining this approach with matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MS) (Bruker Daltonik, Germany) is expected to enable more rapid identification of pathogens. METHODS: Early growth detection by digital imaging using Kiestra TLA combined with MS was compared to conventional methods (CM) of detection. Accuracy and time taken for microbial identification were evaluated for the two methods in 219 clinical blood culture isolates. The possible clinical impact of earlier microbial identification was assessed according to antibiotic treatment prescription. RESULTS: Pathogen identification using Kiestra TLA combined with MS resulted in a 30.6 hr time gain per isolate compared to CM. Pathogens were successfully identified in 98.4% (249/253) of all tested isolates. Early microbial identification without susceptibility testing led to an adjustment of antibiotic regimen in 12% (24/200) of patients. CONCLUSIONS: The requisite 24 hr incubation time for microbial pathogens to reach sufficient growth for susceptibility testing and identification would be shortened by the implementation of Kiestra TLA in combination with MS, compared to the use of CM. Not only can this method optimize workflow and reduce costs, but it can allow potentially life-saving switches in antibiotic regimen to be initiated sooner.


Subject(s)
Humans , Automation, Laboratory , Candida albicans/genetics , Disk Diffusion Antimicrobial Tests , Gram-Negative Bacteria/genetics , Gram-Positive Bacteria/genetics , RNA, Ribosomal, 16S/chemistry , Retrospective Studies , Sequence Analysis, RNA , Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
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