Pharmacokinetic/pharmacodynamic analysis as a tool for surveillance of the activity of antimicrobials against Pseudomonas aeruginosa strains isolated in critically ill patients

Abstract

Introduction: To evaluate the changes in the susceptibility of Pseudomonas aeruginosa over time (2000-2017) against antimicrobials used in an intensive care unit of a Spanish tertiary hospital, and to compare them with the antimicrobial activity considering theoretical pharmacokinetic/pharmacodynamic (PK/PD) criteria. The influence of the method for handling duplicate isolates to quantify susceptibility rates was also evaluated.

Methods: The susceptibility was studied considering the Clinical and Laboratory Standards Institute (CLSI) breakpoints. Monte Carlo simulations were conducted to calculate the cumulative fraction of response (CFR). Linear regression analysis was applied to determine the trends in susceptibility and in the CFR.

Results: A significant decrease in the susceptibility to gentamicin and imipenem was observed, and more recently the highest percentages of susceptible strains were found for amikacin, cephalosporins and piperacillin/tazobactam (>80%). The probability of success of an empiric treatment or CFR for most of the evaluated antimicrobials was lower than 70% during the last two-year period. Only meropenem provided high probabilities (>90%) to achieve the PK/PD target. Cephalosporins provided moderate probabilities (>80%) although for ceftazidime, the highest dose (2g/8h) was required. Moreover, a significant decrease in the CFR trend for ciprofloxacin, imipenem and levofloxacin was observed.

Conclusions: Both susceptibility rates and CFR values have to be considered together to optimize the antimicrobial dose regimen for clinical making-decisions. They are complementary tools and, they should be used jointly in surveillance programmes. In fact, susceptibility data are not always useful to detect changes in the CFR. No relevant differences were observed among the methods for handling repeated isolates.

Keywords: Aislados duplicados; Antibiotic resistance surveillance; Cuidados intensivos; Duplicate isolates; Farmacocinética/farmacodinamia; Intensive care; Monte Carlo simulation; Pharmacokinetics/pharmacodynamics; Pseudomonas aeruginosa; Simulación de Monte Carlo; Vigilancia resistencia antimicrobiana.