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Bayesian modeling of the impact of antibiotic resistance on the efficiency of MRSA decolonization

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  • Fanni Ojala
  • Mohamad R Abdul Sater
  • Loren G Miller
  • James A McKinnell
  • Mary K Hayden
  • Susan S Huang
  • Yonatan H Grad
  • Pekka Marttinen

Abstract

Methicillin-resistant Staphylococcus aureus (MRSA) is a major cause of morbidity and mortality. Colonization by MRSA increases the risk of infection and transmission, underscoring the importance of decolonization efforts. However, success of these decolonization protocols varies, raising the possibility that some MRSA strains may be more persistent than others. Here, we studied how the persistence of MRSA colonization correlates with genomic presence of antibiotic resistance genes. Our analysis using a Bayesian mixed effects survival model found that genetic determinants of high-level resistance to mupirocin was strongly associated with failure of the decolonization protocol. However, we did not see a similar effect with genetic resistance to chlorhexidine or other antibiotics. Including strain-specific random effects improved the predictive performance, indicating that some strain characteristics other than resistance also contributed to persistence. Study subject-specific random effects did not improve the model. Our results highlight the need to consider the properties of the colonizing MRSA strain when deciding which treatments to include in the decolonization protocol.Author summary: Methicillin-resistant Staphylococcus aureus (MRSA) is responsible for a high burden of morbidity and mortality. MRSA colonization incurs risk of MRSA infection and transmission, highlighting the need for highly effective decolonization protocols. However, decolonization protocols have had mixed success. The extent to which this mixed success is attributable to MRSA strain variations and their resistance to antibiotics, including those like mupirocin that are commonly used for decolonization, versus study subject factors, has been unclear. Here, we characterized the effect of antibiotic resistance genes on the efficiency of an MRSA decolonization protocol. We found that mupirocin resistance and strain-specific effects were associated with reduced effectiveness of an MRSA decolonization protocol, but that resistance to other antibiotics, including purported chlorhexidine resistance genes, and subject-specific effects had no discernible impact on protocol success. Our results highlight the need to consider the properties of the colonizing MRSA strain when deciding which treatments to include in the decolonization protocol.

Suggested Citation

  • Fanni Ojala & Mohamad R Abdul Sater & Loren G Miller & James A McKinnell & Mary K Hayden & Susan S Huang & Yonatan H Grad & Pekka Marttinen, 2023. "Bayesian modeling of the impact of antibiotic resistance on the efficiency of MRSA decolonization," PLOS Computational Biology, Public Library of Science, vol. 19(10), pages 1-17, October.
  • Handle: RePEc:plo:pcbi00:1010898
    DOI: 10.1371/journal.pcbi.1010898
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    References listed on IDEAS

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    1. Marko Järvenpää & Mohamad R Abdul Sater & Georgia K Lagoudas & Paul C Blainey & Loren G Miller & James A McKinnell & Susan S Huang & Yonatan H Grad & Pekka Marttinen, 2019. "A Bayesian model of acquisition and clearance of bacterial colonization incorporating within-host variation," PLOS Computational Biology, Public Library of Science, vol. 15(4), pages 1-25, April.
    2. Phelim Bradley & N. Claire Gordon & Timothy M. Walker & Laura Dunn & Simon Heys & Bill Huang & Sarah Earle & Louise J. Pankhurst & Luke Anson & Mariateresa de Cesare & Paolo Piazza & Antonina A. Votin, 2015. "Rapid antibiotic-resistance predictions from genome sequence data for Staphylococcus aureus and Mycobacterium tuberculosis," Nature Communications, Nature, vol. 6(1), pages 1-15, December.
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