Effect of Antimicrobial Consumption on Escherichia coli resistance: assessment and forecasting using Dynamic Regression models in a French university hospital (2014-2019).

INTRODUCTION: The aim of this study was to determine the correlation between antimicrobial consumption (AMC) and antimicrobial resistance (AMR) in Escherichia coli at a hospital level, and assess the capacity of dynamic regression (DR) models to predict AMR to use them for the deployment of antimicrobial stewardship programs (ASPs).

METHODS: We conducted a retrospective epidemiological study in a French tertiary hospital between 2014 and 2019. DR models were used to assess the correlation between AMC and AMR between 2014 and 2018. Their predictive abilities were estimated by comparing the predicted data with those observed in 2019.

RESULTS: Rates of fluoroquinolone and cephalosporin resistance has decreased, while AMC has increased overall, except for fluoroquinolones whose consumption decreased. DR models highlighted that the decrease in fluoroquinolone use and the increase in anti-pseudomonal activity penicillin with beta-lactamase inhibitor (AAPBI) use explained 54% of the decrease in fluoroquinolone resistance and 15% of the decrease in cephalosporin resistance. Additionally, the penicillin/beta-lactamase inhibitor (PBI) consumption explained 53% of PBI resistance, and beta-lactam use explained 36% of penicillin resistance, with both remaining stable over time. DR models had predictive capabilities with margins of error from 8% to 34%.

CONCLUSION: Over a six-year period, in a French tertiary hospital, decreasing rates of resistance to fluoroquinolones and cephalosporins were correlated with decreasing use of fluoroquinolone and increasing use of AAPBI, whereas the rates of resistance to penicillin remained high and stable. Our results suggest that DR models should be used with caution for AMR forecasting and ASP implementation.