Empirical antibiotic treatment is selected to target causative bacteria with antibiotics to which they are not resistant. We analysed the increase in bacterial resistance among individual patients associated with antibiotic exposure in the month prior to infection onset, compared to unexposed patients. From a series of prospective cohort studies in the period 2002-2011 at Beilinson Hospital, Israel, 4232 consecutive patients suspected of infection were included. We analysed resistance to antibiotics in bacterial isolates from patients with clinically significant and microbiologically documented infections, starting antibiotics after obtaining cultures (n = 775). In Gram-negative bacteria, significantly higher rates of resistance was associated with exposure to antibiotics, while no significant associations were found for Gram-positive bacteria. Significant odds ratios (ORs) for increased resistance to classes of antibiotics ranged from 2.1 to 3.3 in Gram-negative bacteria from patients exposed to any antibiotic(s), with quinolones having the highest OR, followed by aminoglycosides, penicillins with β-lactamase inhibitor and cephalosporins. The majority of significant associations also had significant ORs after exposure to another class of antibiotics, indicating a substantial effect of cross-resistance. In conclusion, increased resistance was observed following exposure to antibiotics, both from the same class and from other classes. The results indicate a reason to adjust the expected coverage of empirical antibiotic treatments for patients recently exposed to antibiotics, with some antibiotics being more affected than others.

A practical method for predicting probability for antimicrobial susceptibility could be developed based on a semi-naïve Bayesian approach using statistical data on cross-susceptibilities and cross-resistances. The reduction in Brier distance from 37.7% to 25.3%, indicates a significant advantage to the proposed min2max2 method (p<10(99)).

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