title: Discriminant analysis of antibiotic susceptibility as a means of bacterial identification.
abstract: This study shows that antibiotic susceptibility data can be used effectively in the presumptive identification of bacteria. Using 12 antibiotics and determining the zone sizes for each, 82% of the isolates considered were correctly identified without any other information. If the inability to distinguish between Escherichia coli and Shigella is disregarded, the percentage of correct identification is 92%. The method involves determining a set of discriminant functions and defining each taxon by a unique function. An unknown isolate is identified by evaluating each discriminant function and assigning the isolate to the taxon whose discriminant function has the largest value. A total of 468 isolates were examined. After eliminating the multiply resistant isolates, the remaining 369 isolates were used to determine the discriminant functions for the eight taxa considered.
mesh_terms: D000900:Anti-Bacterial Agents / Q000494:pharmacology*; D003201:Computers; D004352:Drug Resistance, Microbial; D004755:Enterobacteriaceae / Q000145:classification* / Q000187:drug effects; D008954:Models, Biological; D013045:Species Specificity
chemical_list: D000900:Anti-Bacterial Agents