Table of Contents
ISRN Microbiology
Volume 2012, Article ID 107203, 4 pages
Research Article

Comparison of an Automated System with Conventional Identification and Antimicrobial Susceptibility Testing

1Department of Microbiology, Dr. Baba Saheb Ambedkar Hospital, Rohini, New Delhi 110085, India
2Department of Microbiology, VMMC and Safdarjung Hospital, New Delhi 110029, India
3Department of Microbiology, BLK Super Speciality Hospital, New Delhi 110005, India

Received 5 July 2012; Accepted 23 August 2012

Academic Editors: A. E. Deghmane and H.-P. Horz

Copyright © 2012 Shalini Duggal et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The present study was designed to compare a fully automated identification/antibiotic susceptibility testing (AST) system BD Phoenix (BD) for its efficacy in rapid and accurate identification and AST with conventional manual methods and to determine if the errors reported in AST, such as the (very major errors) VME (false susceptibility), (major errors) ME (false resistance), and (minor errors) MiE (intermediate category interpretation) were within the range certified by FDA. Identification and antimicrobial susceptibility test results of eighty-five clinical isolates including both gram-positive and negative were compared on Phoenix considering the results obtained from conventional manual methods of identification and disc diffusion testing of antibiotics as standards for comparison. Phoenix performed favorably well. There was 100% concordance in identification for gram-negative isolates and 94.83% for gram-positive isolates. In seven cases, Phoenix proved better than conventional identification. For antibiotic results, categorical agreement was 98.02% for gram-positive and 95.7% for gram-negative isolates. VME was 0.33%, ME 0.66%, MiE 0.99% for gram-positive isolates and 1.23% VME, 1.23% ME, and 1.85% MiE for gram-negative isolates. Therefore, this automated system can be used as a tool to facilitate early identification and susceptibility pattern of aerobic bacteria in routine microbiology laboratories.