 Welcome back to our USMLE question of the week. Let's get right to that question. As always, we start off with the last sentence of the vignette, so we know what this question is looking for. If an individual has a positive test for autoantibodies against the acetylcholine receptor, what is the approximate probability of having this disease? You have a patient in your office that you suspect they have myasthenia gravis. Individuals with myasthenia gravis classically present with complaints of muscle weakness and fatigue, secondary to the formation of autoantibodies directed against the acetylcholine receptors at neuromuscular junctions. The most appropriate method of diagnosis involves the detection of these autoantibodies. On average, this test is approximately 90% sensitive and 80% specific. If an individual has a positive test for autoantibodies against the acetylcholine receptor, what is the approximate probability of having this disease? Take a look at the answer choices, come up with your answer, and write it in the comment box below. Okay, this question is looking for the positive predictive value. What is the positive predictive value? Positive predictive value is known as our true positive over the true positive plus the false positive. So how do we get those values out of a sensitivity and specificity? Well, we can assume that each one of these is based out of a number 10. So a 90% sensitivity means 9 out of 10 are true positives, and an 80% specificity means that we have 2 out of 10 that are false positives. So we can take those numbers and plug that into our equation that true positive is 9 divided by true positive of 9 plus false positive of 2 equals 9 over 11, which comes out to be approximately 81.8%. We can round that up, and 82 is our answer, and that is an answer choice for us. So our final answer will be 82%. And 82 is the correct answer in this situation. So 80 is too low. It doesn't match up. 85, 88, and 90 are too high based off our calculations. So let's look back here. What is sensitivity? Sensitivity is the proportion of people with disease who test positive or the probability of the disease is present, and there's a positive test. Okay, and what is specificity? Specificity is the proportion of people without the disease who test negative, where the probability that when a disease is absent, the test is negative. So when we are looking for a positive predictive value, we are trying to see what the probability is that a person has a positive test actually has the disease, which is exactly what this question is asking us for. What is the positive predictive value? So we use that true positive over a true positive plus false positive to come up with our answer that we have extrapolated from our 80% and 90% specificity and sensitivity, respectively.