The added diagnostic value of automated QT-dispersion measurements and automated ST-segment deviations in the electrocardiographic diagnosis of acutecardiac ischemia

The purpose of this study was to determine the added value of automated QT dispersion and ST-segment measurements to physician interpretation of 12-le ad electrocardiograms (ECGs) in patients with chest pain. To date, poor rep roducibility of manual measurements and lack of shown added value have limi ted the clinical use of QT dispersion. Twelve-lead ECGs (n = 1,161) from th e Milwaukee Prehospital Chest Pain Database were independently classified b y 2 physicians into 3 groups (acute myocardial infarction (AMI), acute card iac ischemia (ACI), or nonischemic), and their consensus was obtained. QT-e nd and QT-peak dispersions were measured by a computerized system. The comp uter also identified ST-segment deviations. Sensitivity, specificity, and p ositive predictive values (PPVs) and negative predictive values (NPV) for A MI and ACI were evaluated independently and in combinations. For AMI, physi cians' consensus classification was remarkably good (sensitivity, 48%, spec ificity, 99%). Independent classification by QT-end and QT-peak dispersions or ST deviations was not superior to the physicians' consensus. Optimal cl assification occurred by combining automated QT-end dispersion and ST devia tions with physicians' consensus. This combination increased sensitivity fo r the diagnoses of AMI by 35% (65% vs 48%, P <.001) and ACI by 55% (62% vs 40%, P <.001) compared with physicians' consensus, while maintaining compar able specificity. This study supports a potential clinical role for automat ed QT dispersion when combined with other diagnostic methods for detecting AMI and ACI.