Use a pulmonary embolism case to practice Bayesian thinking, likelihood ratios, and test threshold decisions.
Choose a pretest probability, reveal a positive D-dimer, update your estimate, and decide whether to order CTPA.
Frame clinical reasoning as moving from a prior estimate to an updated probability after new evidence.
Introduce LR+ and LR- as tools for translating test results into changed probability.
Adjust pretest probability and likelihood ratio to see how post-test probability changes.
Apply the nomogram to the patient from the first page.
See how the CTPA decision and updated probability translate into the patient outcome.