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The form of Bayes'
theorem (post-test odds = pre-test odds x likelihood ratio) is
a clue to a great principle:
"The interpretation
of new information depends on old information."
Expressed in a medical
context, this principle means that the interpretation of a test
result depends on the clinical characteristics of the patient
that determine the pre-test probability of disease.
Clearly, the estimation
of pre-test probability is of central importance in clinical medicine.
How does one estimate the pre-test probability? There are three
basic methods, which are each described in this section.
Click on any of the
methods below. Explore all three to compare your estimate of the
patient's probability of ischemic chest pain to the results of
using each of these three methods.
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