Journal
CLINICAL INFECTIOUS DISEASES
Volume 62, Issue 2, Pages 181-189Publisher
OXFORD UNIV PRESS INC
DOI: 10.1093/cid/civ837
Keywords
beta-lactams; molecular diagnostics; empiric therapy
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Funding
- National Institute of Allergy and Infectious Diseases of the NIH [UM1AI104681]
- Clinical and Translational Science Collaborative of Cleveland [UL1TR000439]
- Cleveland Department of Veterans Affairs
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Background. Rapid molecular diagnostic (RMD) platforms may lead to better antibiotic use. Our objective was to develop analytical strategies to enhance the interpretation of RMDs for clinicians. Methods. We compared the performance characteristics of 4 RMD platforms for detecting resistance against beta-lactams in 72 highly resistant isolates of Escherichia coli and Klebsiella pneumoniae (PRIMERS I). Subsequently, 2 platforms were used in a blinded study in which a heterogeneous collection of 196 isolates of E. coli and K. pneumoniae (PRIMERS II) were examined. We evaluated the genotypic results as predictors of resistance or susceptibility against beta-lactam antibiotics. We designed analytical strategies and graphical representations of platform performance, including discrimination summary plots and susceptibility and resistance predictive values, that are readily interpretable by practitioners to inform decision-making. Results. In PRIMERS I, the 4 RMD platforms detected beta-lactamase (bla) genes and identified susceptibility or resistance in > 95% of cases. In PRIMERS II, the 2 platforms identified susceptibility against extended-spectrum cephalosporins and carbapenems in > 90% of cases; however, against piperacillin/tazobactam, susceptibility was identified in < 80% of cases. Applying the analytical strategies to a population with 15% prevalence of ceftazidime-resistance and 5% imipenem-resistance, RMD platforms predicted susceptibility in > 95% of cases, while prediction of resistance was 69%-73% for ceftazidime and 41%-50% for imipenem. Conclusions. RMD platforms can help inform empiric beta-lactam therapy in cases where bla genes are not detected and the prevalence of resistance is known. Our analysis is a first step in bridging the gap between RMDs and empiric treatment decisions.
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