Advanced Evidence-Based Diagnosis (ROC Curves and Interval Likelihood Ratios)
Course Description and Objectives:
Diagnosis and diagnostic testing are fundamental to medical decision making, whether or not the decision making is related to COVID-19. When and how should we use a rapid antigen test for COVID-19, seasonal influenza, or strep throat? How should we interpret antinucleocapsid antibody levels for prior COVID infection? What about other quantitative test results, such as BNP for acute heart failure, D-Dimer for pulmonary embolism, or serum lactate for severe sepsis? How can we determine the risk of death in a patient hospitalized for COVID-19? How about the risk of stroke after a TIA?
In this half-day, interactive workshop, we will discuss using the evidence to evaluate and interpret diagnostic tests, including tests related to COVID-19. We will cover dichotomous tests, multilevel and continuous tests, ROC curves, interval likelihood ratios, and bias in studies of test accuracy and believe it or not, we will have fun! Instead of giving and passively listening to a series of lectures, we will discuss and solve real-world diagnostic testing problems in small groups.
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Anne Stiggelbout, PhD
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