A 40-year-old woman presents to the office with several months history of atypical chest pain. Her family history is positive for hypertension and type II diabetes mellitus. Her past medical history is insignificant. An ECG stress test is performed to evaluate the possibility of coronary heart disease. This test has 85% sensitivity and 80% specificity. In the low-risk group, its positive predictive value is 25%, and negative predictive value is 96%. If the test is negative, what is the probability that the patient has coronary heart disease?

Question

A 40-year-old woman presents to the office with several months history of atypical chest pain.  Her family history is positive for hypertension and type II diabetes mellitus.  Her past medical history is insignificant.  An ECG stress test is performed to evaluate the possibility of coronary heart disease.  This test has 85% sensitivity and 80% specificity.  In the low-risk group, its positive predictive value is 25%, and negative predictive value is 96%.  If the test is negative, what is the probability that the patient has coronary heart disease?

Quizplus · Accepted Answer

Pre- and post-test probabilities, as well as positive and negative predictive values, are very important concepts in clinical medicine, as they dramatically change the approach to the diagnosis of each disease. Take the time to learn and fully understand these terms. The pre-test probability sets your expectations before performing the diagnostic test. It describes the existing probability of a patient to have the disease in question even before using a particular diagnostic test. (Although there is a mathematical approach to calculate the pre-test probability, we shall simplify this term and use the most basic explanations.) Using the example given above, the pre-test probability of the patient having coronary artery disease can be assumed to be low since she has no risk factors aside from her significant family history, and since she has atypical chest pain. Statistically, the prevalence is directly related to the pre-test probability. In this example, the patient belongs to the low-risk group, which consistently has a relatively low prevalence of coronary artery disease. low low The positive predictive value (PPV) describes the probability of having the disease if the test result is positive. The post-test probability of having the disease is directly related to the PPV. Using the example above, the PPV (25%) is low. Consequently, if the test result is positive, then the post-test probability of having the disease is low. The post-test probability is also dependent on the sensitivity, specificity, and pre-test probability of having the disease. low The negative predictive value (NPV) describes the probability of not having the disease if the test result is negative. In this example, the NPV is 96%. This means that if the test result is negative, the chances of the patient to not have the disease is high (96%). Conversely, if the test result is negative, the chances of the patient to have the disease is low (100% - 96%= 4%). Other cases and diagnostic tests which are high-yield for the USMLE are listed below: Pulmonary embolism and perfusion-ventilation scanningProstate cancer and serum PSA levels Pulmonary embolism and perfusion-ventilation scanning Prostate cancer and serum PSA levels (Choice B) False positive ratio = 1- specificity. (Choice C) False negative ratio = 1 - sensitivity. Educational Objective: If a test result is negative, the probability of having the disease is 1 - negative predictive value.

A 40-Year-Old Woman Presents to the Office with Several Months