Literature DB >> 27413193

Automatic Digital Analysis of Chromogenic Media for Vancomycin-Resistant-Enterococcus Screens Using Copan WASPLab.

Matthew L Faron1, Blake W Buchan2, Christopher Coon1, Theo Liebregts3, Anita van Bree3, Arjan R Jansz3, Genevieve Soucy4, John Korver5, Nathan A Ledeboer6.   

Abstract

Vancomycin-resistant enterococci (VRE) are an important cause of health care-acquired infections (HAIs). Studies have shown that active surveillance of high-risk patients for VRE colonization can aid in reducing HAIs; however, these screens generate a significant cost to the laboratory and health care system. Digital imaging capable of differentiating negative and "nonnegative" chromogenic agar can reduce the labor cost of these screens and potentially improve patient care. In this study, we evaluated the performance of the WASPLab Chromogenic Detection Module (CDM) (Copan, Brescia, Italy) software to analyze VRE chromogenic agar and compared the results to technologist plate reading. Specimens collected at 3 laboratories were cultured using the WASPLab CDM and plated to each site's standard-of-care chromogenic media, which included Colorex VRE (BioMed Diagnostics, White City, OR) or Oxoid VRE (Oxoid, Basingstoke, United Kingdom). Digital images were scored using the CDM software after 24 or 40 h of growth, and all manual reading was performed using digital images on a high-definition (HD) monitor. In total, 104,730 specimens were enrolled and automation agreed with manual analysis for 90.1% of all specimens tested, with sensitivity and specificity of 100% and 89.5%, respectively. Automation results were discordant for 10,348 specimens, and all discordant images were reviewed by a laboratory supervisor or director. After a second review, 499 specimens were identified as representing missed positive cultures falsely called negative by the technologist, 1,616 were identified as containing borderline color results (negative result but with no package insert color visible), and 8,234 specimens were identified as containing colorimetric pigmentation due to residual matrix from the specimen or yeast (Candida). Overall, the CDM was accurate at identifying negative VRE plates, which comprised 84% (87,973) of the specimens in this study.
Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Entities:  

Mesh:

Substances:

Year:  2016        PMID: 27413193      PMCID: PMC5035414          DOI: 10.1128/JCM.01040-16

Source DB:  PubMed          Journal:  J Clin Microbiol        ISSN: 0095-1137            Impact factor:   5.948


  23 in total

1.  Successful treatment of persistent vancomycin-resistant Enterococcus faecium bacteremia with linezolid and gentamicin.

Authors:  G A Noskin; F Siddiqui; V Stosor; J Kruzynski; L R Peterson
Journal:  Clin Infect Dis       Date:  1999-03       Impact factor: 9.079

2.  Projected benefits of active surveillance for vancomycin-resistant enterococci in intensive care units.

Authors:  Eli N Perencevich; David N Fisman; Marc Lipsitch; Anthony D Harris; J Glenn Morris; David L Smith
Journal:  Clin Infect Dis       Date:  2004-04-05       Impact factor: 9.079

Review 3.  Management of multidrug-resistant organisms in health care settings, 2006.

Authors:  Jane D Siegel; Emily Rhinehart; Marguerite Jackson; Linda Chiarello
Journal:  Am J Infect Control       Date:  2007-12       Impact factor: 2.918

4.  Two-sided confidence intervals for the single proportion: comparison of seven methods.

Authors:  R G Newcombe
Journal:  Stat Med       Date:  1998-04-30       Impact factor: 2.373

5.  Vancomycin-resistant enterococci.

Authors:  A H Uttley; C H Collins; J Naidoo; R C George
Journal:  Lancet       Date:  1988 Jan 2-9       Impact factor: 79.321

6.  Clonal outbreak of ST17 multidrug-resistant Enterococcus faecium harbouring an Inc18-like::Tn1546 plasmid in a haemo-oncology ward of a Spanish hospital.

Authors:  Sylvia Valdezate; Consuelo Miranda; Ana Navarro; Ana R Freitas; Jorge J Cabrera; Gema Carrasco; Teresa M Coque; Elena Jiménez-Romano; Juan A Saéz-Nieto
Journal:  J Antimicrob Chemother       Date:  2012-01-06       Impact factor: 5.790

7.  Control of vancomycin-resistant enterococcus in health care facilities in a region.

Authors:  B E Ostrowsky; W E Trick; A H Sohn; S B Quirk; S Holt; L A Carson; B C Hill; M J Arduino; M J Kuehnert; W R Jarvis
Journal:  N Engl J Med       Date:  2001-05-10       Impact factor: 91.245

8.  Characterization of Tn1546, a Tn3-related transposon conferring glycopeptide resistance by synthesis of depsipeptide peptidoglycan precursors in Enterococcus faecium BM4147.

Authors:  M Arthur; C Molinas; F Depardieu; P Courvalin
Journal:  J Bacteriol       Date:  1993-01       Impact factor: 3.490

9.  Enterococcal bacteremia: clinical implications and determinants of death.

Authors:  R N Garrison; D E Fry; S Berberich; H C Polk
Journal:  Ann Surg       Date:  1982-07       Impact factor: 12.969

10.  Urinary tract infection caused by Enterococcus isolates: aetiology and antimicrobial resistance patterns.

Authors:  Qing-Yong Wang; Rong-Hai Li; Xiao-Hong Shang
Journal:  J Chemother       Date:  2014-05-18       Impact factor: 1.714

View more
  18 in total

Review 1.  A Decade of Development of Chromogenic Culture Media for Clinical Microbiology in an Era of Molecular Diagnostics.

Authors:  John D Perry
Journal:  Clin Microbiol Rev       Date:  2017-04       Impact factor: 26.132

2.  Impact of total laboratory automation on workflow and specimen processing time for culture of urine specimens.

Authors:  Melanie L Yarbrough; William Lainhart; Allison R McMullen; Neil W Anderson; Carey-Ann D Burnham
Journal:  Eur J Clin Microbiol Infect Dis       Date:  2018-09-29       Impact factor: 3.267

3.  Automatic Digital Plate Reading for Surveillance Cultures.

Authors:  Thomas J Kirn
Journal:  J Clin Microbiol       Date:  2016-08-10       Impact factor: 5.948

4.  Total Laboratory Automation in Clinical Microbiology: a Micro-Comic Strip.

Authors:  Alexander J McAdam
Journal:  J Clin Microbiol       Date:  2018-03-26       Impact factor: 5.948

5.  Machine Learning Takes Laboratory Automation to the Next Level.

Authors:  Bradley A Ford; Erin McElvania
Journal:  J Clin Microbiol       Date:  2020-03-25       Impact factor: 5.948

6.  Computer Vision and Artificial Intelligence Are Emerging Diagnostic Tools for the Clinical Microbiologist.

Authors:  Daniel D Rhoads
Journal:  J Clin Microbiol       Date:  2020-05-26       Impact factor: 5.948

7.  Evaluation of the WASPLab Segregation Software To Automatically Analyze Urine Cultures Using Routine Blood and MacConkey Agars.

Authors:  Matthew L Faron; Blake W Buchan; Ryan F Relich; James Clark; Nathan A Ledeboer
Journal:  J Clin Microbiol       Date:  2020-03-25       Impact factor: 5.948

Review 8.  Image analysis and artificial intelligence in infectious disease diagnostics.

Authors:  K P Smith; J E Kirby
Journal:  Clin Microbiol Infect       Date:  2020-03-22       Impact factor: 8.067

9.  Benefits Derived from Full Laboratory Automation in Microbiology: a Tale of Four Laboratories.

Authors:  Karissa Culbreath; Heather Piwonka; John Korver; Mir Noorbakhsh
Journal:  J Clin Microbiol       Date:  2021-02-18       Impact factor: 5.948

10.  Commentary: Improving the Efficiency of the Ova and Parasite Examination Using Cloud-Based Image Analysis.

Authors:  Daniel D Rhoads
Journal:  J Pathol Inform       Date:  2017-12-14
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.