Usefulness of business intelligence to guide antimicrobial treatment decision in infections by infrequent microorganism such as Bordetella bronchiseptica.

Abstract

Human infections by Bordetella bronchiseptica are increasing in recent years. However, due to the lack of clinical susceptibility/resistance breakpoints, antimicrobial treatment is complex. Business Intelligence (BI) is a tool that allows to record and analyze large amounts of data in a very short time. The aim of this study was to analyze a cohort of patients with B. bronchiseptica infections focusing on how BI can help guide empirical antimicrobial therapy Demographic, clinical, and microbiological data about B. bronchiseptica infections were recovered. Then, MIC_50/90 of several antibiotics was automatically calculated through the BI. Thirteen B. bronchiseptica infections were identified. The lowest MICs₉₀ were for carbapenem, aminoglycoside, fluoroquinolones, and tetracyclines. The EUCAST PK-PD (non-species related) breakpoints showed that only piperacillin/tazobactam, imipenem and meropenem would be appropriate treatments to use empirically. In conclusion, BI systems have great potential to optimize the empirical antibiotic treatment in these types of infections.