The novacode criteria for classification of ECG abnormalities and their clinically significant progression and regression

Abstract

Electrocardiographic (ECG) manifestations of clinical and subclinical cardiovascular disease are used as an important component in the evaluation of clinical trials, and there is an increasing demand for well-defined criteria for clinically significant evolution of ECG abnormalities. The Novacode ECG classification system provides a comprehensive hierarchical set of criteria for prevalent ECG abnormalities and for clinically significant serial ECG changes, both adverse and favorable, as a response to pharmacologic, surgical, and other interventions. These criteria are used to grade Q wave and ischemic abnormalities in order to achieve stable classification of both prevalent and incident myocardial infarctions by minimizing false classifications due to clinically insignificant ECG variations. This approach differs from the traditional Minnesota Code classification system, in which incident events are determined by changes in classification categories, with the application of additional elaborate validation rules to exclude frequent false classifications. Novacode hierarchy is so structured that for each abnormality, a general class is first determined with the simplest possible classification criteria and more specific abnormality subgroups are then classified with more elaborate criteria. This approach will satisfy differing needs of clinical trials for detail in classification. Explicit definition of ECG variables and condition statements for the classification criteria facilitate implementation of the Novacode with computer ECG programs.