  In biomedical research the use of discrete scales which describe
characteristics of individuals are widely applied for the evaluation of
clinical conditions. However, the number of classes (partitions) used in a
discrete scale has never been mathematically evaluated against the accuracy of
a scale to predict the true cases. This work, using as accuracy markers the
sensitivity and specificity, revealed that the number of classes of a discrete
scale affects its estimating ability of correctly classifying the true
diseased. In particular, it was proved that the sensitivity of scales is a
non-decreasing function of the number of their classes. This result has
particular interest in clinical research providing a methodology for developing
more accurate tools for disease diagnosis.
