Direct Microbial Identification using An Automated Microbial Identification System to Facilitate the EUCAST RAST Method Without Mass Spectrometry

This research aims to evaluate the diagnostic accuracy of Gram-negatives directly from positively flag blood culture bottles by automated microbial identification system. The purpose is to utilize it as a tool for early clinical reporting by EUCAST rapid antimicrobial susceptibility testing method. EUCAST RAST method was recently introduced in 2018 to enable reporting of anti-microbial susceptibility testing results within four to eight hours of positive flagging of automated blood culture bottles.

It involves performing everywhere disk diffusion method directly from positively flagged bottle and reading results at either four, six, or eight hours. For clinical reporting by EUCAST RAST method, the microbial identification is a prerequisite for determining the interpretative category of AST results. The major challenge in implementing this method is early identification of the microbes within eight hours, especially in resource poor settings, which lacks mass spectrometry.

We found that the direct inoculum protocol was around 94%accurate in identifying a RAST reportable Gram-negative, which includes Escherichia coli, Kiebsiella pneumoniae, Pseudomonas aeruginosa, and Acinetobacter baumannii complex. This approach of identifying Gram-negatives directly was around four times faster than the standard approach of identification after overnight incubation. We will now focus on assessing the impact of this approach of clinical reporting in Gram-negative sepsis on patient outcomes in terms of length of hospitalization and mortality rate.

Furthermore, it can also be used as a tool to reduce anti-microbial usage to facilitate anti-microbial stewardship.