ArticleMicrobiology spectrum2021
Genomic Update of Phenotypic Prediction Rule for Methicillin-Resistant Staphylococcus aureus (MRSA) USA300 Discloses Jail Transmission Networks with Increased Resistance.
Article in Microbiology spectrum, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
6 citing papers in PubMed.
- The mutational landscape of Staphylococcus aureus during colonisation.Nature communications · 2025Article
- Clonal Diversity, Antibiotic Resistance, and Virulence Factor Prevalence of Community AssociatedPathogens (Basel, Switzerland) · 2023Article
- Article
- Correlation Analysis ofInternational journal of clinical practice · 2023Article
- Progress in the Prevalence, Classification and Drug Resistance Mechanisms of Methicillin-ResistantInfection and drug resistance · 2023Review
- Green synthesis of silver nanoparticles through oil: Promoting full-thickness cutaneous wound healing in methicillin-resistantFrontiers in bioengineering and biotechnology · 2022Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
Methicillin-resistant Staphylococcus aureus (MRSA) is a leading cause of health care-associated (HA) and community-associated (CA) infections. USA300 strains are historically CA-MRSA, while USA100 strains are HA-MRSA. Here, we update an antibiotic prediction rule to distinguish these two genotypes based on antibiotic resistance phenotype using whole-genome sequencing (WGS), a more discriminatory methodology than pulsed-field gel electrophoresis (PFGE). MRSA clinical isolates collected from 2007 to 2017 underwent WGS; associated epidemiologic data were ascertained. In developing the rule, we examined MRSA isolates that included a population with a history of incarceration. Performance characteristics of antibiotic susceptibility for predicting USA300 compared to USA100, as defined by WGS, were examined. Phylogenetic analysis was performed to examine resistant USA300 clades. We identified 275 isolates (221 USA300, 54 USA100). Combination susceptibility to clindamycin or levofloxacin performed the best overall (sensitivity 80.7%, specificity 75.9%) to identify USA300. The average number of antibiotic classes with resistance was higher for USA100 (3 versus 2,
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