Abstract
The authors use a truncated sequential probability ratio test (SPRT) to diagnose diabetes. It is hypothesized that, for a given oral glucose tolerance test (OGTT), the differences between successive observations are more diagnostic than the observations alone. Using such differences in a SPRT, OGTT test data for 950 subjects are analyzed and thresholds for classifying diabetes and normal values are established. This sequential approach provides the same diagnosticity as that obtained by using the National Diabetic Data Group criteria, but it is more efficient. In particular, the procedure significantly reduces the sampling cost and average patient waiting time.
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