## Definition of Sensitivity **Key Point:** Sensitivity is the ability of a test to correctly identify those WITH the disease. It is the proportion of true positives among all people who actually have the disease. ### Formula $$\text{Sensitivity} = \frac{TP}{TP + FN}$$ Where: - TP = True Positives (correctly identified diseased individuals) - FN = False Negatives (diseased individuals missed by the test) ### Interpretation A sensitivity of 95% means that if 100 people with tuberculosis are tested, the test will correctly identify 95 of them as positive. In other words, 95% of people WITH the disease will test positive. **High-Yield:** Sensitivity answers the question: "If someone HAS the disease, what is the probability the test will be POSITIVE?" It is a **disease-centric** measure. ### Clinical Pearl Sensitivity is crucial for **screening tests** and **ruling out disease** (SnNout: high Sensitivity = Negative result rules OUT disease). A test with high sensitivity has few false negatives, making it reliable for excluding disease. ### Common Confusion ~~Sensitivity = Positive Predictive Value (PPV)~~ — PPV tells you the probability of having disease GIVEN a positive test result, which is different from sensitivity.
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