A-290 Evaluation of a Commercial Turbidity Monitoring System Followed by Mass Spectrometry to Rapid Identification of Microorganisms from Urine Samples

Abstract

Abstract Background Urinary tract infections (UTIs) are one of the most common bacterial infections in worldwide and represent a worried public health problem, especially due to a significant rise in global antibiotic use in recent years. The purpose of the study was to evaluate the performance of Uro-Quick (UQ) system (Alifax) and the Vitek-MS system (bioMérieux) to identify bacteria isolates directly from urine samples. Methods We analyzed 352 clinical samples of urine. From automated screening by UQ system was used 500 µL of homogenized urine sample manually pipetted into a UQ vial containing 4 mL of broth. The inoculated vials were manually introduced into the Uro-Quick reading unit and incubated for 3 h. The signals are processed by software which monitors the growth curves and calculates the microbial count as colony forming units (CFU/mL). Sample preparation to the mass spectrometry (Vitek-MS) was performed using an in-house protocol based on a centrifugation-wash (CW) method. In parallel with the Vitek-MS direct identification, all the urine samples were submitted to standard culture (SC) method on ChromID™CPS® plate by semi-quantitative technique using 1 µL disposable loop, incubated at 35–37°C and the colony counting were read after 24 and 48h of incubation. Bacterial isolates from positive cultures were identified by Vitek®2 System, according to the manufacture’s recommendations. Cultures with the presence of three or more microorganisms were considered negative. Results Out of 334 clinical samples, 261 (78.1%) were negative for the growth by UQ system and for the presence of microorganisms by SC, 78 (21.9%) samples were positive with growth as ≥104 CFU/mL by UQ system, of which 32 samples were also positive with microorganism isolated by SC. Among the 78 microorganisms detected on the samples with growth curve by UQ system, 74 (94.8%) were identified to the species level by the mass spectrometry and 4 (5.2%) were not identified. The microorganisms were Escherichia coli (n = 40), Enterococcus faecalis (n = 12), Klebsiella pneumoniae (n = 6), Proteus mirabilis (n = 4), Citrobacter koseri (n = 4), Streptococcus agalactiae (n = 3), Morganella morganii (n = 2), Enterobacter cloacae (n = 1), Citrobacter freundii (n = 1) and Gardnerella vaginalis (n = 1). Among the 32 microorganisms detected by SC, 28 showed the same identification at species level when was compared with direct identification by Vitek-MS. Conclusion This study showed that both UQ and CW methods by Vitek-MS technology used together were able to provides a rapid result (<4 h) for bacterial identification directly from urine samples, that can be useful in clinical practices, especially in severe infectious cases like pyelonephritis. So, future studies should address with a larger number of samples to improve the sensibility of this test for different groups of microorganisms.