Evidence map›Paper›PMID 31005733›Full record

ArticleJournal of global antimicrobial resistance2019

Use of online tools for antimicrobial resistance prediction by whole-genome sequencing in methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant enterococci (VRE).

Ahmed Babiker, Mustapha M Mustapha, Marissa P Pacey, Kathleen A Shutt, Chinelo D Ezeonwuka, Sara L Ohm, Vaughn S Cooper, Jane W Marsh, Yohei Doi, Lee H Harrison

Open access · greenAbstract read
In one paragraph

Article in Journal of global antimicrobial resistance, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
1.7field-weighted citation impact, top 16% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 27 citations in OpenAlex.

  1. Article
  2. Infection and immunity · 2025
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  5. Comparative genomics of Vibrio toranzoniae strains.International microbiology : the official journal of the Spanish Society for Microbiology · 2025
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  15. Assessing the Potential for Unintended Microbial Consequences of Routine Chlorhexidine Bathing for Prevention of Healthcare-associated Infections.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2021
    Review
  16. Article
  17. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 1 institution in 1 country.

Ahmed BabikerDivision of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Microbial Genomic Epidemiology Laboratory, Infectious Diseases Epidemiology Research Unit, University of Pittsburgh, Pittsburgh, PA, USA. Electronic address: ahmed.babiker@emory.edu.
Mustapha M MustaphaMicrobial Genomic Epidemiology Laboratory, Infectious Diseases Epidemiology Research Unit, University of Pittsburgh, Pittsburgh, PA, USA.
Marissa P PaceyMicrobial Genomic Epidemiology Laboratory, Infectious Diseases Epidemiology Research Unit, University of Pittsburgh, Pittsburgh, PA, USA.
Kathleen A ShuttDivision of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Microbial Genomic Epidemiology Laboratory, Infectious Diseases Epidemiology Research Unit, University of Pittsburgh, Pittsburgh, PA, USA.
Chinelo D EzeonwukaMicrobial Genomic Epidemiology Laboratory, Infectious Diseases Epidemiology Research Unit, University of Pittsburgh, Pittsburgh, PA, USA.
Sara L OhmMicrobial Genomic Epidemiology Laboratory, Infectious Diseases Epidemiology Research Unit, University of Pittsburgh, Pittsburgh, PA, USA.
Vaughn S CooperDepartment of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Jane W MarshMicrobial Genomic Epidemiology Laboratory, Infectious Diseases Epidemiology Research Unit, University of Pittsburgh, Pittsburgh, PA, USA.
Yohei DoiDivision of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Lee H HarrisonDivision of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Microbial Genomic Epidemiology Laboratory, Infectious Diseases Epidemiology Research Unit, University of Pittsburgh, Pittsburgh, PA, USA.
University of Pittsburgh · US

Funding

Enhanced Detection System for Healthcare-Associated Transmission of InfectionR01AI127472 · NIAID · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI HARRISON, LEE H · 2016 to 2025
$7.6M
Genomic Epidemiology for Hospital Outbreak DetectionR21AI109459 · NIAID · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI HARRISON, LEE H · 2014 to 2015
$437k
NIAID NIH HHS R01 AI127472NIAID NIH HHS R21 AI109459
6 · The paper itself

Abstract

objectivesThe antimicrobial resistance (AMR) crisis represents a serious threat to public health and has resulted in concentrated efforts to accelerate development of rapid molecular diagnostics for AMR. In combination with publicly available web-based AMR databases, whole-genome sequencing (WGS) offers the capacity for rapid detection of AMR genes. Here we studied the concordance between WGS-based resistance prediction and phenotypic susceptibility test results for methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant enterococci (VRE) clinical isolates using publicly available tools and databases.

methodsClinical isolates prospectively collected at the University of Pittsburgh Medical Center between December 2016 and December 2017 underwent WGS. The AMR gene content was assessed from assembled genomes by BLASTn search of online databases. Concordance between the WGS-predicted resistance profile and phenotypic susceptibility as well as the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were calculated for each antibiotic/organism combination, using the phenotypic results as gold standard.

resultsPhenotypic susceptibility testing and WGS results were available for 1242 isolate/antibiotic combinations. Overall concordance was 99.3%, with a sensitivity, specificity, PPV and NPV of 98.7% (95% CI 97.2-99.5%), 99.6% (95% CI 98.8-99.9%), 99.3% (95% CI 98.0-99.8%) and 99.2% (95% CI 98.3-99.7%), respectively. Additional identification of point mutations in housekeeping genes increased the concordance to 99.4%, sensitivity to 99.3% (95% CI 98.2-99.8%) and NPV to 99.4% (95% CI 98.4-99.8%).

conclusionWGS can be used as a reliable predicator of phenotypic resistance both for MRSA and VRE using readily available online tools.

Indexed as

Drug Resistance, BacterialComputational BiologyGenes, EssentialGenome, BacterialHumansMethicillin-Resistant Staphylococcus aureusMicrobial Sensitivity TestsPhenotypePoint MutationProspective StudiesSensitivity and SpecificityVancomycin-Resistant EnterococciWeb BrowserWhole Genome SequencingAntimicrobial resistanceMethicillin-resistant Staphylococcus aureusMRSAVancomycin-resistant enterococciVREWhole-genome sequencing

Identifiers

PMID31005733
PMCPMC6800622
OpenAlexW2935851696

What OpenQuestion holds

Textmetadata
LicenceTDM
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.