Introduction: Identification of patients with infection associated with antibioticresistant pathogens remains a serious challenge for the study of drug regimens to treat such infections. The ARREST Program was established as a multidisciplinary, collaborative effort to use surveillance data and analytic techniques to better understand factors associated with antimicrobial resistance. The analyses presented herein were conducted to identify factors predictive of decreased susceptibility of Enterobacter spp. in hospitalized patients.
Methods: Five years (1997-2001) of North American SENTRY Program data were analyzed. MICs for cefepime (CPM), ciprofloxacin (CIP) and piperacillin/tazobactam (P/T) versus patient-specific variables (e.g., age, duration of hospital stay prior to isolate collection, infection source, infection risk factors) and hospital-specific variables (e.g., bed count, geographical region, study year) were analyzed using multivariable general linear modeling for censored data with backwards stepwise elimination (at p > 0.1).
Results: MIC50, MIC range, and % non-susceptible for isolates (n=356, 96% blood, from 30 hospitals) were: ≤ 0.12, ≤ 0.12 to >16, 0.6 for CPM; ≤ 0.25, ≤ 0.015 to > 2, 4.8 for CIP; and 2, ≤ 0.5 to > 64, 22 for P/T. Highly significant variables identified from the multivariable models included bed count (p ≤ 0.001) and hospital duration (p ≤ 0.008). The proportion of explained MIC variability ranged from 20-33%. This range increased to 33-43% when hospital was included as a variable in these models. Higher predicted MICs resulted from combinations of these and other significant variables in the models. Observed MIC50 (% non-susceptible) for each agent was compared in selected patient cohorts possessing combinations of variables identified through these models (see table).
European Congress of Clinical Microbiology and Infectious Disease (ECCMID), Glasgow, Scotland, May 2003
By Bhavnani, S.M., Hammel, J.P., Forrest, A., Ambrose, P.G., Jones, R.N.