The hidden impact of antibacterial resistance in respiratory tract infection. Steering an appropriate course: principles to guide antibiotic choice.
The prevalence and degree of antibacterial resistance in common respiratory pathogens are increasing worldwide. The health impact of resistance is not yet fully understood. However, once the impact of resistance becomes measurable, it may be too late to apply interventions to reduce resistance levels and regain previous quality and cost of care. We should address resistance now, before patient care is irreversibly compromised. The association between antibiotic consumption and the prevalence of resistance is widely assumed. However, evidence suggests that there is a more complex. multifactorial relationship between antibiotic use and resistance. It is also assumed that there is an adaptive fitness cost for bacterial resistance mutations. However, in some cases, bacteria are able to acquire 'compensatory genes' negating any negative impact of resistance mutations. Mathematical modeling indicates that the timescale for the emergence of resistance is typically shorter than the decay time following a decline in antibiotic consumption. Against this background, a general principle is proposed: to maximize patient outcome whilst minimizing the potential for selection and spread of resistance. This may be achieved through the use of agents that fulfill defined pharmacodynamic and pharmacokinetic parameters and elicit rapid eradication of the bacterial population, including emerging resistant mutants, from the site of infection. The choice of agent may not be the same in all regions, as selection will depend on local resistance patterns and disease etiology; however, the application of this principle may help to preserve the benefits of antibiotic therapy.
Cars
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Department of Epidemiology, Swedish Institute for Infectious Disease Control, Solna. otto.cars@smi.ki.se
D002648:Child; D002675:Child, Preschool; D004352:Drug Resistance, Microbial; D005798:Genes, Bacterial / Q000235:genetics; D006801:Humans; D008432:Mathematical Computing; D008826:Microbial Sensitivity Tests; D009154:Mutation / Q000235:genetics; D010818:Practice Patterns, Physicians'; D012141:Respiratory Tract Infections / Q000188:drug therapy*; D013997:Time Factors