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Estimated Impact Of Low Isolate Numbers On The Reliability Of Cumulative Antibiogram Data, Christian Tran, John Hargy, Bryan Hess, Matthew Pettengill

Department of Pathology, Anatomy, and Cell Biology Faculty Papers

Antibiograms are cumulative reports of antimicrobial susceptibility results that are used to guide the selection of empirical antibiotic therapy. Although Clinical and Laboratory Standards Institute (CLSI) guidelines recommend including only organisms that have at least 30 isolates in an antibiogram, previous studies demonstrated that adherence to this recommendation is highly variable. This paper aims to model the impact of small sample sizes on expected levels of error in cumulative antibiograms by comparing percent susceptibility results for random samples to those of the larger, entire data set. The results demonstrate relatively high error rates when utilizing low numbers of isolates in …