Literature DB >> 32552054

Surveillance of antimicrobial resistance and evolving microbial populations in Vermont: 2011-2018.

John Stelling1,2, Jennifer S Read3,4, William Fritch3, Thomas F O'Brien1,2, Rob Peters1, Adam Clark1, Marissa Bokhari1, Mattia Lion1, Parisha Katwa1, Patsy Kelso3.   

Abstract

OBJECTIVE: This study presents trends in organism isolation and antimicrobial resistance in routine microbiology test results from acute-care hospital microbiology laboratories in Vermont.
METHODS: Organism identifications and antimicrobial susceptibility test results were captured from acute-care hospital laboratories to monitor geographic and temporal trends in resistance and emerging microbial threats with the free WHONET software.
RESULTS: Data were provided from 12 acute care hospital laboratories from 2011 through 2018 for 318,833 isolates from 148,994 patients (70% female, 74% outpatient, and 63% urine). Significant differences (p < 0.05) in age, gender, and antimicrobial susceptibility results (e.g. Escherichia coli and levofloxacin) between outpatient and inpatient isolates were identified with temporal increases in certain species (e.g. Aerococcus urinae) and resistance (e.g. Streptococcus pneumoniae and erythromycin). The use of multi-resistance phenotypes demonstrated significant heterogeneity (p < 0.05) in MRSA strains between facilities, for example Staphylococcus aureus resistant to six priority antimicrobials were found in no critical access hospitals (fewer than 25 inpatient beds) but in all non-critical access hospitals.
CONCLUSIONS: Comprehensive electronic surveillance of antimicrobial resistance utilizing routine clinical microbiology data with free software tools offers early recognition and tracking of emerging community and healthcare resistance threats at the local and state level.

Entities:  

Keywords:  Microbiology laboratory; Vermont; WHONET; antimicrobial resistance; surveillance

Mesh:

Substances:

Year:  2020        PMID: 32552054      PMCID: PMC7554058          DOI: 10.1080/14787210.2020.1776114

Source DB:  PubMed          Journal:  Expert Rev Anti Infect Ther        ISSN: 1478-7210            Impact factor:   5.091


  12 in total

1.  Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance.

Authors:  A-P Magiorakos; A Srinivasan; R B Carey; Y Carmeli; M E Falagas; C G Giske; S Harbarth; J F Hindler; G Kahlmeter; B Olsson-Liljequist; D L Paterson; L B Rice; J Stelling; M J Struelens; A Vatopoulos; J T Weber; D L Monnet
Journal:  Clin Microbiol Infect       Date:  2011-07-27       Impact factor: 8.067

2.  Automated detection of infectious disease outbreaks in hospitals: a retrospective cohort study.

Authors:  Susan S Huang; Deborah S Yokoe; John Stelling; Hilary Placzek; Martin Kulldorff; Ken Kleinman; Thomas F O'Brien; Michael S Calderwood; Johanna Vostok; Julie Dunn; Richard Platt
Journal:  PLoS Med       Date:  2010-02-23       Impact factor: 11.069

Review 3.  Integrated Multilevel Surveillance of the World's Infecting Microbes and Their Resistance to Antimicrobial Agents.

Authors:  Thomas F O'Brien; John Stelling
Journal:  Clin Microbiol Rev       Date:  2011-04       Impact factor: 26.132

4.  Difficult-to-Treat Resistance in Gram-negative Bacteremia at 173 US Hospitals: Retrospective Cohort Analysis of Prevalence, Predictors, and Outcome of Resistance to All First-line Agents.

Authors:  Sameer S Kadri; Jennifer Adjemian; Yi Ling Lai; Alicen B Spaulding; Emily Ricotta; D Rebecca Prevots; Tara N Palmore; Chanu Rhee; Michael Klompas; John P Dekker; John H Powers; Anthony F Suffredini; David C Hooper; Scott Fridkin; Robert L Danner
Journal:  Clin Infect Dis       Date:  2018-11-28       Impact factor: 9.079

5.  Automated detection of outbreaks of antimicrobial-resistant bacteria in Japan.

Authors:  A Tsutsui; K Yahara; A Clark; K Fujimoto; S Kawakami; H Chikumi; M Iguchi; T Yagi; M A Baker; T O'Brien; J Stelling
Journal:  J Hosp Infect       Date:  2018-10-12       Impact factor: 3.926

6.  The world's microbiology laboratories can be a global microbial sensor network.

Authors:  Thomas F O'Brien; John Stelling
Journal:  Biomedica       Date:  2014-04       Impact factor: 0.935

7.  Automated use of WHONET and SaTScan to detect outbreaks of Shigella spp. using antimicrobial resistance phenotypes.

Authors:  J Stelling; W K Yih; M Galas; M Kulldorff; M Pichel; R Terragno; E Tuduri; S Espetxe; N Binsztein; T F O'Brien; R Platt
Journal:  Epidemiol Infect       Date:  2009-10-02       Impact factor: 2.451

Review 8.  Efficient Delivery of Investigational Antibacterial Agents via Sustainable Clinical Trial Networks.

Authors:  Anthony McDonnell; John H Rex; Herman Goossens; Marc Bonten; Vance G Fowler; Aaron Dane
Journal:  Clin Infect Dis       Date:  2016-08-15       Impact factor: 9.079

9.  Laboratory-based prospective surveillance for community outbreaks of Shigella spp. in Argentina.

Authors:  María R Viñas; Ezequiel Tuduri; Alicia Galar; Katherine Yih; Mariana Pichel; John Stelling; Silvina P Brengi; Anabella Della Gaspera; Claudia van der Ploeg; Susana Bruno; Ariel Rogé; María I Caffer; Martin Kulldorff; Marcelo Galas
Journal:  PLoS Negl Trop Dis       Date:  2013-12-12

Review 10.  The Continuing Threat of Methicillin-Resistant Staphylococcus aureus.

Authors:  Márió Gajdács
Journal:  Antibiotics (Basel)       Date:  2019-05-02
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  1 in total

1.  2018 Survey of factors associated with antimicrobial drug use and stewardship practices in adult cows on conventional California dairies: immediate post-Senate Bill 27 impact.

Authors:  Pius S Ekong; Essam M Abdelfattah; Emmanuel Okello; Deniece R Williams; Terry W Lehenbauer; Betsy M Karle; Joan D Rowe; Sharif S Aly
Journal:  PeerJ       Date:  2021-07-13       Impact factor: 2.984

  1 in total

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