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More than 4,000 clinical urine specimens were evaluated with an automated microbial detection/identification system compared to a standarized manual analysis and the routine modalities used in five peer-group laboratories. The comparison indicates that the automated system recognizes the nine groups of significant microorganisms in urinary tract infections in hospitalized patients with the same efficiency as a standarized manual method. The automated system's ability to enumerate the bacterial populations in the original clinical specimen attained a high degree of accuracy.

Clinical laboratory evaluation of automated microbial detection/identification system in analysis of clinical urine specimens