1. What is Post-Test Probability?

Definition: Post-test probability is the updated probability that a patient has a condition after considering the results of a diagnostic test.

Purpose: It helps clinicians interpret test results in the context of pre-test likelihood of disease.

2. How Does the Calculator Work?

The calculator uses the formula:

Where:

• \( P_{post} \) — Post-test probability (0-1)
• \( P_{pre} \) — Pre-test probability (0-1)
• \( Se \) — Test sensitivity (0-1)
• \( Sp \) — Test specificity (0-1)

Explanation: The formula combines pre-test probability with test characteristics to estimate how the test result changes the probability of disease.

3. Importance of Post-Test Probability

Details: Understanding post-test probability helps in clinical decision-making, determining whether to treat, order more tests, or rule out a condition.

4. Using the Calculator

Tips: Enter values between 0 and 1 for all parameters. Pre-test probability is often based on prevalence or clinical judgment.

5. Frequently Asked Questions (FAQ)

Q1: How is pre-test probability determined?
A: It can be based on disease prevalence in the population or clinical prediction rules.

Q2: What's the difference between sensitivity and specificity?
A: Sensitivity is the true positive rate, specificity is the true negative rate.

Q3: Can post-test probability be higher than pre-test?
A: Yes, with a positive result from a good test, post-test probability increases.

Q4: What if the test is negative?
A: For negative results, use the formula: (P_pre × (1-Se)) / (P_pre × (1-Se) + (1-P_pre) × Sp)

Q5: How accurate is this calculation?
A: It's mathematically precise but depends on accurate input parameters.