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Background Antimicrobial-resistant (AMR) bacteria are a rising healthcare concern and are associated with an estimated five-fold increase in mortality for infected patients. Correct treatment requires antimicrobial susceptibility knowledge, but standard testing methods require multiple days for an accurate phenotype. Rapid identification of AMR immediately after blood culture positivity could potentially improve health outcomes, lower economic cost, prevent the spread of multidrug-resistant outbreaks and assist with antimicrobial stewardship goals. Methods The BioFire® Antimicrobial Resistance (AMR) Panel is a research use only multiplex-nested PCR system with 47 assays for 30 genes conferring resistance to cephalosporins, carbapenems, aminoglycosides, and fluoroquinolones which can be found in E. coli, K. pneumoniae, P. aeruginosa, A. baumannii, and E. cloacae complex. We tested 86 residual positive blood culture samples collected from Primary Children’s Hospital, University of Utah Hospital and Huntsman Cancer Hospital with the BioFire AMR Panel. Molecular genotypic results were compared with phenotypic susceptibility information for each blood culture specimen to confirm resistance detections. Results Of the 86 samples tested, there were 33 cultures phenotypically resistant (beyond intrinsic resistance) to at least one antibiotic class targeted by the panel. BioFire AMR Panel identified resistance to gentamicin, cefoxitin, all penicillins tested, and ciprofloxacin with 100% positive predictive value (PPV). For tobramycin, ceftazidime, and ceftriaxone, the PPV was greater than 85%. Carbapenem resistance was not detected, likely due to the low number of resistant organisms present in our patient population. Conclusion The BioFire AMR Panel provides identification of genetic AMR determinants in a rapid, easy-to-use system that accurately correlates with phenotypic data for specific antimicrobials. Studies will continue to test additional clinical samples at various geographical locations to further evaluate the relationship between genotypic and phenotypic resistance assessment. Data presented is from an assay that has not been cleared or approved by US FDA or other regulatory agencies for in vitro diagnostic use. Disclosures S. Marxreiter, NIH NIAID: Grant Investigator, Research grant. BioFire Diagnostics, LLC: Employee, Salary. E. Lo, BioFire Diagnostics, LLC: Employee, Salary. NIH NIAID: Grant Investigator, Research grant. C. Oswald, BioFire Diagnostics, LLC: Employee, Salary. NIH NIAID: Grant Investigator, Research grant. A. Hopper, Primary Children’s Hospital: Investigator, Research grant. B. Barr, Primary Children’s Hospital: Grant Investigator, Research grant. J. A. Daly, Primary Children’s Hospital: Grant Investigator, Research grant. University of Utah: Grant Investigator, Research grant. C. C. Ginocchio, Biomerieux: Employee, Salary. R. Crisp, BioFire Diagnostics, LLC: Employee, Salary. A. Hemmert, BioFire Diagnostics, LLC: Employee, Salary. NIH NIAID: Grant Investigator, Research grant.

701. Rapid Detection of Antimicrobial Resistance Determinants with the BioFire® System