Analysis of transient ST events is considerably more complex than was believed before the development of the ESC DB. The publication of the ESC DB has given researchers a tantalizing view of temporal patterns in ST change that are as yet poorly understood but are likely to be of future clinical interest. At the same time, the ESC DB shows us examples of ST changes that confound most automated analysis techniques. These events appear to have the principal characteristics of ischemic ST episodes, yet on closer examination are clearly non-ischemic in nature.
We are developing a new long-term ST database as a complement to the ESC DB. It is important to observe that the LTST DB is not intended as a replacement for the ESC DB; its goals are different, and (because of its far greater size) it is not practical to annotate the LTST DB beat-by-beat as was done with the ESC DB. What we hope to accomplish is to better represent the wide variety of ``real-world'' data, including many more examples of mixed and non-ischemic episodes, and to permit researchers to study lengthy examples of quasi-periodic and other temporal patterns in ST change . The LTST DB is intended to support the development of improved algorithms to differentiate ischemic from non-ischemic ST events, and (by its size) to permit more reliable prediction of clinical performance from first-order performance statistics.