The test for amylase is highly sensitive because it is capable of picking up very small amounts of amylase in the blood. Sensitivity can be thought of as ‘how delicate/sensitive the test is to picking up little changes’. The sensitivity of a test is the proportion of people who test positive among all those who actually have the disease.Ī sensitive test helps rule out a disease when the test is negative (e.g. You might also be interested in our OSCE Flashcard Collection which contains over 2000 flashcards that cover clinical examination, procedures, communication skills and data interpretation. These allow you to rule conditions in or out but not definitively diagnose a condition.Ī classic table that allows sensitivity and specificity to be worked out quantitatively can be seen below. 90% specificity = 90% of people who do not have the target disease will test negative). Specificity is the percentage of true negatives (e.g. 90% sensitivity = 90% of people who have the target disease will test positive). Sensitivity is the percentage of true positives (e.g. Prevalence is the number of cases in a defined population at a single point in time and is expressed as a decimal or a percentage. Whereas sensitivity and specificity are independent of prevalence. The significant difference is that PPV and NPV use the prevalence of a condition to determine the likelihood of a test diagnosing that specific disease. Positive predictive value (PPV) and negative predictive value (NPV) are best thought of as the clinical relevance of a test. Sensitivity and specificity are characteristics of a test. The aim of this article is to help provide an understanding of sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) in an intuitive and comprehensible format.
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