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Likelihood ratios (LRs) have emerged as one of the most useful means to describe the implications of diagnostic test results. Unfortunately, many clinicians have difficulty relating likelihood ratios to the more familiar concepts of pretest and post-test probability, perhaps because the mathematics of LRs do not conveniently mesh with probabilities.1 Below I present a novel, integer-only algorithm useful in quickly appreciating the clinical implications of a likelihood ratio. The method is simple enough to be applied mentally, without recourse to calculators or other mechanical aids.
The algorithm computes the post-test probability (P) of disease as P = MI / (MI+NJ)—conveniently …