The evidence based clinician: part 4 - applying evidence to your patient
Christopher Ball looks at how to apply the evidence to your patient, focusing on diagnosing conditions
Doctors spend their careers making guesses--they are constantly predicting the probability of certain diseases or outcomes in every patient they see. Most of the time this happens subconsciously, but if quizzed any doctor should be able to come up with rough figures. Doctors are often good at ruling in conditions--for example, angina or delirium--but much worse at ruling them out--for example, myocardial infarction or delirium. Tests provide information that can help alter these predictions, but by how much?
This article considers the types of numbers you will find in evidence relating to diagnosis and how you can adapt this information to your patient.
Pre-test probability of pulmonary embolism 9.5% (95% confidence interval 7.5% to 11.3%)
Diagnostic test Likelihood ratio of test Post-test probability Likelihood ratio of test Post-test probability
being positive (95% CI) being negative (95% CI)
Diagnosis other than 2.0 (1.92.2) 17% 0.023 (0.00320.16) 0.2% low risk and d-dimer