By: Dr. George Mastoras
(Presented September 2013)
ROC curves are used to evaluate diagnostic data by plotting sensitivity versus 1-specificity, with higher areas under the curve (AUC) indicating better ability of the test to discriminate between patients with and without the condition. In this paper, the authors claimed than AUCs of 0.95 (which are very high) meant that the assays were very accurate in identifying MI. Unfortunately, ROC curves are not very usefulness to clinicians and particularly in the ED where we are usually focused on sensitivity or the ability of a test to rule-out a condition (SnOut).