OpGen Data Predicting Antibiotic Resistance Published in Antimicrobial Agents and Chemotherapy Journal
The manuscript highlights results from a rapid, high-throughput PCR test that evaluated more than 7,500 highly antibiotic-resistant clinical isolates of Escherichia coli, Klebsiella pneumoniae, Proteus mirabilis, and Pseudomonas aeruginosa selected from Merck’s Study for Monitoring Antimicrobial Resistance Trends (SMART) surveillance network to predict phenotypic resistance to several antibiotic classes.
The study developed statistical methods to predict phenotypic resistance from resistance genes for various combinations of the four bacterial species and the antibiotics gentamicin, tobramycin, ciprofloxacin, levofloxacin, trimethoprim-sulfamethoxazole, ertapenem, imipenem, cefazolin, cefepime, cefotaxime, ceftazidime, ceftriaxone, ampicillin, piperacillin and aztreonam. Average positive predictive values for predicting phenotypic resistance were 91% for E. coli, 93% for K. pneumoniae, 87% for P. mirabilis, and 92% for P. aeruginosa.
Dr. Walker noted, “We believe this study is the most comprehensive of its kind completed to date. The results support the use of rapid DNA testing to help guide antibiotic decision making. The study evaluated approximately two million data points from patients globally and in
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Source: OpGen, Inc.