Literature DB >> 23486713

Multilaboratory study of the Biomic automated well-reading instrument versus MicroScan WalkAway for reading MicroScan antimicrobial susceptibility and identification panels.

Robert C Fader1, Emily Weaver, Rhonda Fossett, Michele Toyras, John Vanderlaan, David Gibbs, Andrew Wang, Nikolaus Thierjung.   

Abstract

This study compared the Biomic automated well reader results to the MicroScan WalkAway results for reading MicroScan antimicrobial susceptibility and identification panels at four different sites. Routine fresh clinical isolates and quality control (QC) organisms were tested at each study site. A total of 46,176 MicroScan panel drug-organism combinations were read. The Biomic category agreement for 3,117 Gram-negative bacteria was 98.4%, with 1.4% minor and 0.2% major discrepancies. The Biomic category agreement for 5,233 Gram-positive bacteria was 98.7%, with 0.9% minor, 0.3% major, and 0.1% very major errors. Essential agreement, defined as Biomic results that were within ±1 2-fold dilution of the MicroScan results, was 99.3% for Gram-negative bacteria and 98.3% for Gram-positive bacteria. Biomic reading of MicroScan identification panels provided an overall agreement (first- and second-choice organism match) of 99.5% with 846 Gram-negative isolates and 99.5% with 430 Gram-positive isolates. These results suggest that the Biomic automated reader can provide accurate reading of MicroScan panels and has the capability of a visual panel read for manual adjustment of results.

Mesh:

Year:  2013        PMID: 23486713      PMCID: PMC3647896          DOI: 10.1128/JCM.03088-12

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


  6 in total

1.  In vitro susceptibility of a large collection of Candida Strains against fluconazole and voriconazole by using the CLSI disk diffusion assay.

Authors:  Ana Carolina Azevedo; Fernando César Bizerra; Daniel Arquimedes da Matta; Leila Paula de Almeida; Robert Rosas; Arnaldo Lopes Colombo
Journal:  Mycopathologia       Date:  2010-12-23       Impact factor: 2.574

2.  Evaluation of the Biomic V3 microbiology system for identification of selected species on BBL CHROMagar orientation agar and CHROMagar MRSA medium.

Authors:  Ellen Jo Baron; Holly D'Souza; Andrew Qi Wang; David L Gibbs
Journal:  J Clin Microbiol       Date:  2008-08-13       Impact factor: 5.948

3.  Comparison of efficacy and cost-effectiveness of BIOMIC VIDEO and Vitek antimicrobial susceptibility test systems for use in the clinical microbiology laboratory.

Authors:  I Berke; P M Tierno
Journal:  J Clin Microbiol       Date:  1996-08       Impact factor: 5.948

4.  Evaluation of the BIOMIC video reader system for determining interpretive categories of isolates on the basis of disk diffusion susceptibility results.

Authors:  E K Korgenski; J A Daly
Journal:  J Clin Microbiol       Date:  1998-01       Impact factor: 5.948

5.  Comparison of the susceptibilities of Candida spp. to fluconazole and voriconazole in a 4-year global evaluation using disk diffusion.

Authors:  Kevin C Hazen; Ellen Jo Baron; Arnaldo Lopes Colombo; Corrado Girmenia; Aurora Sanchez-Sousa; Amalia del Palacio; Catalina de Bedout; David L Gibbs
Journal:  J Clin Microbiol       Date:  2003-12       Impact factor: 5.948

6.  Comparison of cefoxitin and oxacillin disk diffusion methods for detection of mecA-mediated resistance in Staphylococcus aureus in a large-scale study.

Authors:  Nicole M Broekema; Tam T Van; Timothy A Monson; Steven A Marshall; David M Warshauer
Journal:  J Clin Microbiol       Date:  2008-11-19       Impact factor: 5.948

  6 in total
  1 in total

1.  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

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.