# How to calculate sensitivity, specificity, positive predictive value and negative predictive value.

Medical students need to be dexter in statistics. It is really needed though we often find it boring and hard to get through. These basic things apply in everyday medicine. So ready ?

Lets assume we have **1000 patients for sample.**

Now lets say **100 patients actually have Diabetes not under treatment. **So, **900 people have no Diabetes .**

We want to see if **Random Blood Sugar(RBS)** can be used as screening test to detect Diabetes. All 1000 people under go RBS test.

Among 100 people with diabetes, 95 had positive screen ie high RBS , 5 had normal RBS.

Therefore-

### People with diabetes AND tested positive are the **true positives (TP)= 95**

### People with diabetes AND tested negative are the **false negatives (FN)=5**

### People without diabetes AND tested positive are the **false positives (FP)=90**

### People without diabetes AND tested negative are the **true negatives (TN)=810**

Now applying the Formula,

Sensitivity= True Positive/(True Positive +False Negative) X 100%

Here, Sen = 95/95+5 X 100= 95%

This means, RBS is able to detect diabetes in 95% cases who have diabetes.

Specificity= True Negative/ (True Negative+ False Positive) X 100%

Here, Spec = 810/810+90 X 100=90%

This means the test has ability to rule out diabetes in 90% patients without diabetes.

Positive predictive value=True Positive/( True positive + False positive) X 100

Here, PPV= 95/(95+90) X 100= 51.40%

This means the test has ability to tell us that if the test is postive by RBS, 51.40% will have diabetes.

Negative predictive value=True Negative/( True Negative + False Negative) X 100

Here, PPV= 810/(810+5) X 100= 99.40%

This means the test has ability to tell us that if the test is negative by RBS, 99.4.40% will not have diabetes.

** For a Clearer Picture, this can be applied in all diseases**

Hope, it was helpful!