Sensitivity, Specificity and Positive Predictive Value (PPV)
Accurate interpretation of diagnostic tests is essential in emergency medicine and in exam questions on test performance. Sensitivity, specificity and PPV describe different properties of a test and must be read in the clinical context.
This section defines each metric, shows their calculation from a 2×2 table, gives a worked example, explains how prevalence affects PPV/NPV, and summarises clinical implications, common biases and practical exam tips.
Guidance and practical recommendations follow UK diagnostics appraisal documents (NICE) and public‑health guidance (GOV.UK, UK NSC).
What each measure tells you
- Sensitivity: the proportion of people with disease who test positive (true positives / all with disease). High sensitivity → few false negatives. Useful when the clinical goal is to exclude disease.
- Specificity: the proportion of people without disease who test negative (true negatives / all without disease). High specificity → few false positives. Useful when the clinical goal is to confirm disease.
- Positive predictive value (PPV): the probability that a person with a positive test actually has disease (true positives / all positive tests). PPV depends on the test’s sensitivity and specificity and the disease prevalence in the tested population.
- Negative predictive value (NPV): the probability that a person with a negative test does not have disease. Like PPV, NPV depends on prevalence.
Note: sensitivity and...
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