When two tests, A and B, are combined (A ∪ B), there are true positives for A, but not B, (A ∪ B) − B; true positives for B, but not A, (A ∪ B) − A; and true positives for both A and B, (A ∩ B). The effect of correlation would be to increase the true positives for both, (A ∩ B), at the expense of the other positives, (A ∪ B) − (A ∩ B). Also, because there would be a higher proportion of both tests positive relative to the false positives, the estimate for risk would be increased. Similarly, with both tests correlated and negative, a higher proportion of patients would have a lower risk. The effect upon results in (Table le3) could be to improve greatly the risk stratification in the first two stages and to reduce the proportion of patients referred for EPS from 10.8% to 3.2%.