Acinetobacter baumannii is one of the most difficult-to-treat pathogens worldwide, due to developed resistance. The aim of this study was to evaluate the use of widely prescribed antimicrobials and the respective resistance rates of A. baumannii, and to explore the relationship between antimicrobial use and the emergence of A. baumannii resistance in a tertiary care hospital. Monthly data on A. baumannii susceptibility rates and antimicrobial use, between January 2014 and December 2017, were analyzed using time series analysis (Autoregressive Integrated Moving Average (ARIMA) models) and dynamic regression models. Temporal correlations between meropenem, cefepime, and ciprofloxacin use and the corresponding rates of A. baumannii resistance were documented. The results of ARIMA models showed statistically significant correlation between meropenem use and the detection rate of meropenem-resistant A. baumannii with a lag of two months (p = 0.024). A positive association, with one month lag, was identified between cefepime use and cefepime-resistant A. baumannii (p = 0.028), as well as between ciprofloxacin use and its resistance (p < 0.001). The dynamic regression models offered explanation of variance for the resistance rates (R² > 0.60). The magnitude of the effect on resistance for each antimicrobial agent differed significantly.

Background: Even though, Pseudomonas aeruginosa is a common cause of hospital-acquired infections, treatment is challenging because of decreasing rates of susceptibility to many broad-spectrum antibiotics. Methods: Consumption data of eight broad spectrum antimicrobial agents and resistance rates of P. aeruginosa were collected for 48 consecutive months. Autoregressive integrated moving average (ARIMA) and transfer functions models were used to develop relationships between antibiotic use and resistance. Results: Positive correlations between P. aeruginosa resistance and uses of ciprofloxacin (p < 0.001), meropenem (p < 0.001), and cefepime (p = 0.005) were identified. Transfer function models showed the quantified effect of each of these antibiotics on resistance. Regarding levofloxacin, ceftazidime, piperacillin/tazobactam and imipenem, no significant relationships were found. For ceftazidime and levofloxacin, this was probably due to their low consumption, while for imipenem the reason can possibly be ascribed to the already high established P. aeruginosa resistance in the hospital. Conclusion: In the hospital setting, the effect of antimicrobial agents’ consumption on the susceptibility epidemiology of P. aeruginosa differs significantly for each one of them. In this study, the role of precedent use of meropenem, cefepime and ciprofloxacin was quantified in the development of P. aeruginosa resistance.