A New Approach to the Analysis of Antibiotic Resistance Data from Hospitals

Abstract

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.

Effect of outpatient antibiotics for urinary tract infections on antimicrobial resistance among commensal Enterobacteriaceae: a multinational prospective cohort study

“…By contrast, nitrofurantoin had minimal impact on total Enterobacteriaceae and was neither associated with emergence of ciprofloxacin nor nitrofurantoin resistance. These findings are consistent with our a priori hypothesis based on a mechanistic conceptual model of the link between exposure to specific antibiotics and emergence of resistance (Table 1) [6,7].…”

“…We adapted a conceptual model to develop a priori hypotheses regarding the impact of different antibiotic classes on the emergence of antimicrobial resistance [6,7] (Table 1), and also hypothesized that any effects would increase with increasing treatment duration.…”

Understanding complex clinical reasoning in infectious diseases for improving clinical decision support design

“…Overuse of antibiotics has been a concern with respect to drug resistance and public health [ 87 , 88 ]. The notion that doing less in medicine sometimes can mean more has been an important discussion in the infectious disease community [ 89 – 91 ].…”

Antibiotic consumption and resistance of gram-negative pathogens (collateral damage)

“…Ward level use was significant for imipenem-resistant P. aeruginosa (HR 1.22; 95% CI 1.15–1.30). Their results showed that combining population- and individual-level data is crucial for the exploration of antimicrobial resistance development (LoE 1b) [ 48 ], [ 49 ].…”