A new approach to the analysis of antibiotic resistance data from hospitals.


We aimed to develop a new approach to the analysis of antimicrobial resistance data from the hospitals, which allows simultaneous analysis of both individual- and population-level determinants of bacterial resistance. This was a retrospective cohort study that included adult patients who stayed in the hospital >2 days. We analyzed data using shared frailty Cox models and tested our approach using a priori hypotheses based on biology and epidemiology of antibiotic resistance. For gram-negative bacteria, the use of the major selecting antibiotic by an individual was the main risk factor for acquiring resistant species. Hazard ratios (HRs) were strikingly high for ceftazidime-resistant Enterobacter species (HR=11.17; 95% confidence interval [CI]: 5.67-22.02), ciprofloxacin-resistant Pseudomonas aeruginosa (HR=4.41; 95% CI: 2.14-9.08), and imipenem-resistant P. aeruginosa (HR=7.92; 95% CI: 4.35-14.43). Ward-level use was significant for vancomycin-resistant enterococci (VRE) (HR=1.40; 95% CI: 1.07-1.83) and for imipenem-resistant P. aeruginosa (HR=1.40; 95% CI: 1.08-1.83). Previous incidence of infection in the same ward increased the risk of acquiring methicillin-resistant Staphylococcus aureus (HR=1.22; 95% CI: 1.15-1.30) and VRE (HR=1.53; 95% CI: 1.38-1.70). Our results were consistent with our hypotheses and showed that combining population- and individual-level data is crucial for the exploration of antimicrobial resistance development.

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