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Common things are common, but what is common? Incorporating probability information into differential diagnosis
Scott K Aberegg1, Sean J Callahan1
1Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah, USA.
Abstract:
The well-known clinical axiom declaring that 'common things are common' attests to the pivotal role of probability in diagnosis. Despite the popularity of this and related axioms, there is no operationalized definition of a common disease, and no practicable way of incorporating actual disease frequencies into differential diagnosis. In this essay, we aim to disambiguate the definition of a common (or rare) disease and show that incidence-not prevalence-is the proper metric of disease frequency for differential diagnosis. We explore how numerical estimates of disease frequencies based on incidence can be incorporated into differential diagnosis as well as the inherent limitations of this method. These concepts have important implications for diagnostic decision making and medical education, and hold promise as a method to improve diagnostic accuracy.
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