Infect Drug Resist. 2021 Jun 30;14:2461-2498. doi: 10.2147/IDR.S314241. eCollection 2021.
Prompt implementation of appropriate targeted antibiotic therapy represents a valuable approach in improving clinical and ecological outcome in critically septic patients. This multidisciplinary opinion article focused at developing evidence-based algorithms for targeted antibiotic therapy of bloodstream (BSIs), complicated urinary tract (cUTIs), and complicated intrabdominal infections (cIAIs) caused by Enterobacterales. The aim was to provide a guidance for intensive care physicians either in appropriately placing novel antibiotics or in considering strategies for sparing the broadest-spectrum antibiotics. A multidisciplinary team of experts (one intensive care physician, one infectious disease consultant, one clinical microbiologist and one MD clinical pharmacologist), performed several rounds of assessment to reach agreement in developing six different algorithms according to the susceptibility pattern (one each for multi-susceptible, extended-spectrum beta-lactamase-producing, AmpC beta-lactamase-producing, Klebsiella pneumoniae carbapenemase (KPC)-producing, OXA-48-producing, and Metallo-beta-lactamase (MBL)-producing Enterobacterales). Whenever multiple therapeutic options were feasible, a hierarchical scale was established. Recommendations on antibiotic dosing optimization were also provided. In order to retrieve evidence-based support for the therapeutic choices proposed in the algorithms, a comprehensive literature search was performed by a researcher on PubMed-MEDLINE from inception until March 2021. Quality and strength of evidence was established according to a hierarchical scale of the study design. Only articles published in English were included. It is expected that these algorithms, by allowing prompt revision of antibiotic regimens whenever feasible, appropriate place in therapy of novel beta-lactams, implementation of strategies for sparing the broadest-spectrum antibiotics, and pharmacokinetic/pharmacodynamic optimization of antibiotic dosing regimens, may be helpful either in improving clinical outcome or in containing the spread of antimicrobial resistance.