Quantifying the effect of in-hospital antimicrobial use on the development of colistin-resistant strains: a time series analysis.

OBJECTIVES

Colistin is currently considered an essential therapeutic option for the treatment of hospital-acquired infections caused by resistant isolates of . In this study, conducted in a tertiary care hospital, the effect of previous detection rates and antimicrobial use on colistin-resistant strains was investigated.

METHODS

Susceptibility data for isolates and colistin use information were collected for 48 consecutive months (January 2014 to December 2017). ARIMA models were used to explore the time series of colistin use and resistance to . In addition, dynamic regression models were used to study the relationships between the use of antimicrobials (colistin, imipenem, meropenem, cefepime, ciprofloxacin) and colistin resistance.

RESULTS

The results of the univariate model showed a statistically significant positive association between colistin use and the detection rate of colistin-resistant (p=0.003). Moreover, a multivariate model confirmed the positive association of colistin use with the detection rate of colistin-resistant , also demonstrating statistically significant negative associations with imipenem (p=0.004) and meropenem use (p=0.005).

CONCLUSIONS

This study quantifies the effect of colistin use on the development of resistant strains. These findings can assist antimicrobial stewardship teams to elaborate their plans and predict the effect of their interventions.