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 MICs(90) 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.