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not be applied to interpret profiles obtained by other testing methods.

Furthermore, most databases are established with the assumption that the isolate to be identified has been appropriately characterized using adjunctive tests. For example, if an S. aureus isolate is mistakenly tested using a system for identification of Enterobacteriaceae, the database will not identify the gram-positive coccus because the results obtained will only be compared with data available for enteric bacilli. This underscores the importance of accuratdy performing preliminary tests and observations, such as colony and Gram stain morphologies, before selecting a particular identification battery.

Use of the Database to Identify Unknown Isolates

Once a metabolic profile has been obtained with a bacterial isolate of unknown identity, the profile must be converted to a numeric code that will facilitate comparison of the unknown's phenotypic fingerprint with the appropriate database.

To exemplify this step in the identification process, a binary code conversion system that uses the numerals 0 and 1 to represent negative and positive metabolic reactions, respectively, is used as an example (although other strategies are now used). As shown in Figure 7-18, using binary code conversion, a 21-digit binomial number (e.g., 101100001001101111010, as read from top to bottom in the figure) is produced from the test result. This number is then used in an octal code conversion scheme to produce a mathematic number (octal profile [see Figure 7-18]). The octal profile number is used to generate a numerical profile distinctly related to a specific bacterial species. As shown in Figure 7-18, the octal profile for the unknown organism is 5144572. This profile would then be compared with database profiles to determine the most likely identity of the organism. In this example, the octal profile indicates the unknown organism is E. coli.

Confidence in Identification. Once metabolic profiles have been translated into numeric scores, the probability that a correct correlation with the database has been made must be established, that is, how confident can the laboratorian be in knowing that a correct identification has been made. This is accomplished by establishing the percentage probability, which is usually provided as part of most commercially available identification database schemes.

For example, unknown organism X is tested against the four biochemicals listed in Table 7-2 and yields results as follows: lactose (+), sucrose (+), indole (-), and ornithine (+). Based on the results of each test, the percentage of known strains in the database that produced positive results are used to calculate the percentage probability that strain X is a member of one of the two genera (Escherichia or Shigella) given in the example (Table 7-3). Therefore, if 91% of Escherichia spp. are lactose-positive (see Table 7-2), the probability that X is a species of Escherichia based on lactose alone is 0.91. If 38% of Shigella spp. are indole positive (see Table 7-2), then the probability that X is a species of Shigella based on indole alone is 0.62 (1.00 {all Shigella] -0.38 [percent positive Shigella] = 0.62 [percent of all Shigella that are indole negative]). The probabilities of the individual tests are then multiplied to achieve a calculated likelihood that X is one of these two genera, In this example, X is more likely to be a species of Escherichia, with a probability of 357:1 (1 divided by

Table 7-3 Generation and Use of Genus-Identification Database Probability: Probability That Unknown Strain X is Member of Known Genus Based on Results of Each Individual Parameter Tested

Biochemical Parameter

Table 7-3 Generation and Use of Genus-Identification Database Probability: Probability That Unknown Strain X is Member of Known Genus Based on Results of Each Individual Parameter Tested

Biochemical Parameter

Organism

Lactose

Sucrose

Indole

Ornithine

\

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Bacterial Vaginosis Facts

Bacterial Vaginosis Facts

This fact sheet is designed to provide you with information on Bacterial Vaginosis. Bacterial vaginosis is an abnormal vaginal condition that is characterized by vaginal discharge and results from an overgrowth of atypical bacteria in the vagina.

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