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“One-Size-Fits-All”? Optimizing Treatment Duration for Bacterial Infections

Overview of attention for article published in PLOS ONE, January 2012
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131 Mendeley
Title
“One-Size-Fits-All”? Optimizing Treatment Duration for Bacterial Infections
Published in
PLOS ONE, January 2012
DOI 10.1371/journal.pone.0029838
Pubmed ID
Authors

Patricia Geli, Ramanan Laxminarayan, Michael Dunne, David L. Smith

Abstract

Historically, antibiotic treatment guidelines have aimed to maximize treatment efficacy and minimize toxicity, but have not considered the evolution of antibiotic resistance. Optimizing the duration and dosing of treatment to minimize the duration of symptomatic infection and selection pressure for resistance simultaneously has the potential to extend the useful therapeutic life of these valuable life-saving drugs without compromising the interests of individual patients.Here, using mathematical models, we explore the theoretical basis for shorter durations of treatment courses, including a range of ecological dynamics of bacteria that cause infections or colonize hosts as commensals. We find that immunity is an important mediating factor in determining the need for long duration of treatment. When immunity to infection is expected, shorter durations that reduce the selection for resistance without interfering with successful clinical outcome are likely to be supported. Adjusting drug treatment strategies to account for the impact of the differences in the ecological niche occupied by commensal flora relative to invasive bacteria could be effective in delaying the spread of bacterial resistance.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 131 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 2%
Switzerland 1 <1%
Ireland 1 <1%
Brazil 1 <1%
Colombia 1 <1%
Canada 1 <1%
Mexico 1 <1%
Denmark 1 <1%
Spain 1 <1%
Other 0 0%
Unknown 121 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 27 21%
Student > Master 22 17%
Researcher 21 16%
Student > Bachelor 15 11%
Student > Doctoral Student 11 8%
Other 23 18%
Unknown 12 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 30 23%
Medicine and Dentistry 25 19%
Biochemistry, Genetics and Molecular Biology 12 9%
Pharmacology, Toxicology and Pharmaceutical Science 7 5%
Mathematics 7 5%
Other 27 21%
Unknown 23 18%