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Journal ArticleDOI

Multi-Laboratory Evaluation of an Automated Microbial Detection/Identification System

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TLDR
The AMS was capable of detecting growth of most organisms, including those which it was not designed to identify, however, it identified some of these incorrectly as common urinary tract flora.
Abstract
An automated and computerized system (Automicrobic System [AMS]) for the detection of frequently encountered bacteria in clinical urine specimens was tested in a collaborative study among six laboratories. The sensitivity, specificity, reliability, and reproducibility of the AMS were determined, and the system was compared with conventional detection and identification systems. In this study, pure cultures and mixtures of pure cultures were used to simulate clinical urine specimens. With pure cultures, the sensitivity of the AMS in identifying the nine groups of organisms most commonly found in urine averaged 92.8%. The specificity averaged 99.4%, and the reliability of a positive result averaged 92.1%. The latter value was strongly influenced by a relatively high occurrence of false positive Escherichia coli results. The AMS was capable of detecting growth of most organisms, including those which it was not designed to identify. However, it identified some of these incorrectly as common urinary tract flora. Reproducibility of results, both within laboratories and among different laboratories, was high. Fast-growing organisms, such as E. coli and Klebsiella/Enterobacter species, were detected often at cell populations well below the AMS enumeration threshold of 70,000/ml. In mixed culture studies, high levels of sensitivity and specificity were maintained but when Serratia species were present in mixtures with other organisms, there was often a false positive report of E. coli. The overall performance of the AMS was considered satisfactory under the test conditions used.

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Citations
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Viable microorganism detection by induced fluorescence

TL;DR: In this paper, a spectrometric technique was proposed to determine microorganism detection and identification by taking advantage of the inherent extracellular enzymes present in living organisms, as opposed to dead, non-enzyme producing organisms.
Journal ArticleDOI

Comparison of the automicrobic system with API, enterotube, micro-ID, micro-media systems, and conventional methods for identification of Enterobacteriaceae.

TL;DR: The AutoMicrobic System appears to be an efficient and accurate system for the identification of Enterobacteriaceae, which automatically monitored and interpreted the biochemical reactions and reported organism identifications.
Journal ArticleDOI

Collaborative investigation of the AutoMicrobic System Enterobacteriaceae biochemical card.

TL;DR: Compared with the routine methods used in the various laboratories, the AutoMicrobic System identified 96.4% correctly compared with 98.1% by the standard method selected and 97.6% by a commerically prepared manual system approach.
Journal ArticleDOI

Rapid identification and antimicrobial susceptibility testing of gram-negative bacilli from blood cultures by the AutoMicrobic system.

TL;DR: In using this procedure it was possible to provide accurate preliminary identification and results of antimicrobial susceptibility tests for gram-negative bacilli on the same day that a blood culture was determined to be positive.
Journal ArticleDOI

The Systems Approach to Diagnostic Microbiology

TL;DR: This review analyzes the development of the underlining principles that make the systems approach to diagnostic microbiology possible and the adaptation or streamlining of classical methods in the form of "miniaturized identification systems" and their commercial availability.
References
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Journal ArticleDOI

Automated Microbiological Detection/Identification System

TL;DR: System expansion in progress includes antibiotic susceptibility testing and compatibility with most types of clinical specimens, and the detection, enumeration, and identification of bacteria and yeasts in clinical specimens.
Journal ArticleDOI

Preprototype of an automated microbial detection and identification system: a developmental investigation.

TL;DR: Among problems remaining are adaptation of system for specimens other than urine, improvement of sensitivity for P. aeruginosa and S. aureus, and standardization of manual methods used for comparison and validation.
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