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Tools for Decision Making Sections
Author Bio
Introduction
Probability Theory
Case Study 1: Patient History
Bayes' Theorem
Methods for Estimating Pre-test Probability
Estimating Likelihood Ratios
Sensitivity and Specificity
Interpreting Test Results
Calculating Post-test Probabilities
Currently selected section: Post-test Probabilities in Clinical Practice
Conclusions: Case Study 1
Part II
Part III
References

 

Chapter 14: Tools for Decision Making: Post-test Probability in Clinical Practice

        

 

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Selection BProbably no

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It is likely that most physicians wouldn't treat for CAD when the probability of having CAD was this low. At this low probability, the harms of treatment would outweigh the benefits, since most patients who got treatment would not have CAD, yet would experience the harms of treatment.



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