## **Core Concept**
The sensitivity of a test, also known as the true positive rate, is a measure of a test's ability to correctly identify those with the disease. It is calculated as the number of true positive results divided by the sum of true positives and false negatives. This concept is crucial in evaluating the diagnostic accuracy of medical tests.

## **Why the Correct Answer is Right**
The correct formula for sensitivity is: Sensitivity = True Positives / (True Positives + False Negatives). Therefore, the numerator in the calculation of sensitivity is the number of **True Positives (TP)**, which represents the individuals correctly identified as having the disease. This is a direct measure of how well the test can detect those who actually have the condition.

## **Why Each Wrong Option is Incorrect**
- **Option A:** False Positives (FP) - This is incorrect because false positives are those incorrectly identified as having the disease when they do not. This would be the numerator for specificity or in calculations involving false positive rates, not sensitivity.
- **Option B:** False Negatives (FN) - This is incorrect because false negatives are those with the disease who are missed by the test. While they are part of the denominator in the sensitivity calculation, they are not the numerator.
- **Option D:** True Negatives (TN) - This is incorrect because true negatives are those without the disease who are correctly identified as such. This value is used in the calculation of specificity, not sensitivity.

## **Clinical Pearl / High-Yield Fact**
A key point to remember is that a highly sensitive test is useful for ruling out a disease, as it is good at detecting those who have the disease but may also have some false positives. The mnemonic "SnNout" can help: Sensitive test - Negative result rules out the disease.

## **Correct Answer:** B. True Positives.