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Understanding how and why Bayes theorem translates pre-test into post-test probabilities is the pons asinorum (Euclid's 5th proposition is known as the “bridge of asses” because many folk got stuck crossing it) of evidence-based medicine (EBM). Because different minds are sparked by different methods, we teach the theorem by using several presentations: 2 × 2 tables, trees, geometric figures, and formulas. A good teacher will have several of these in his or her armamentarium.1 However, having crossed the bridge of understanding, we still must cross the bridge to practice. The basic understanding is essential, but the time pressures of clinical practice require that we abandon the training wheels and move to tools of rapid calculation. No single tool will suit all people and circumstances, so a well-stocked tool box is advisable. In this editorial, I describe 3 methods aimed primarily at everyday practice rather than enhancing understanding: pre-calculated tables or graphs, programmed Bayes calculators, and the Bayes nomogram.
Pre-calculated tables and graphs
Applying Bayes theorem in clinical practice will be quicker if the calculations are already done. For specific common tests, this pre-calculation can be achieved by either tabulating or graphing the post-test probabilities for all plausible pre-test probability values.2 The calculation becomes a simple look-up (provided you have properly organised your information about the test). Ideally, software for critically appraised topics should include …
↵* The Bayes nomogram that appeared in the glossary of Evidence-Based Medicine in the July/August, September/October and November/December 1999 issues should not be used because the likelihood ratio is imperfectly drawn, giving inaccurate readings in parts of the nomogram; and the lower 500 on the likelihood ratio scale should be 200.
↵* Approximately 60 additional journals are reviewed. This list is available on request.