Abstract
BackgroundTo evaluate QT-interval dynamics in patients and in drug safety analysis, beat-to-beat QT-interval measurements are increasingly used. However, interobserver differences, aberrant T-wave morphologies and changes in heart axis might hamper accurate QT-interval measurements.ObjectiveTo develop and validate a QT-interval algorithm robust to heart axis orientation and T-wave morphology that can be applied on a beat-to-beat basis.MethodsAdditionally to standard ECG leads, the root mean square (ECGRMS), standard deviation and vectorcardiogram were used. QRS-onset was defined from the ECGRMS. T-wave end was defined per individual lead and scalar ECG using an automated tangent method. A median of all T-wave ends was used as the general T-wave end per beat.Supine-standing tests of 73 patients with Long-QT syndrome (LQTS) and 54 controls were used because they have wide ranges of RR and QT-intervals as well as changes in T-wave morphology and heart axis orientation. For each subject, automatically estimated QT-intervals in three random complexes chosen from the low, middle and high RR range, were compared with manually measured QT-intervals by three observers.ResultsAfter visual inspection of the randomly selected complexes, 21 complexes were excluded because of evident noise, too flat T-waves or premature ventricular beats. Bland-Altman analyses of automatically and manually determined QT-intervals showed a bias of <4ms and limits of agreement of ±25ms. Intra-class coefficient indicated excellent agreement (>0.9) between the algorithm and all observers individually as well as between the algorithm and the mean QT-interval of the observers.ConclusionOur automated algorithm provides reliable beat-to-beat QT-interval assessment, robust to heart axis and T-wave morphology.
Highlights
Prolongation of the QT-interval on the electrocardiogram (ECG) has been associated with Torsade de Pointes, a potentially lethal cardiac arrhythmia.[1,2] A prolonged QT-interval can be caused by Long-QT syndrome (LQTS), which can be either inherited or acquired due to an underlying medical condition or medication.[2]
Supine-standing tests of 73 patients with Long-QT syndrome (LQTS) and 54 controls were used because they have wide ranges of RR and QT-intervals as well as changes in T-wave morphology and heart axis orientation
In this article we present and validate an automatic QT-interval algorithm based on the tangent method [15] which is unaffected by heart axis orientation and that can be applied on a beat-to-beat basis regardless of the T-wave morphology
Summary
Prolongation of the QT-interval on the electrocardiogram (ECG) has been associated with Torsade de Pointes, a potentially lethal cardiac arrhythmia.[1,2] A prolonged QT-interval can be caused by Long-QT syndrome (LQTS), which can be either inherited or acquired due to an underlying medical condition or medication.[2]. The value of a prolonged QT-interval for risk assessment of future malignant arrhythmias is widely understood [1], most physicians, including cardiologists, have difficulties to correctly identify a prolonged QT-interval.[4] to measurement difficulties, diagnosing LQTS is challenging since there is a considerable overlap of the QT-interval between LQTS patients and healthy controls.[5,6] Because of this overlap in QT-intervals, additional measurements like QT dispersion [7,8] and QT variability [9] were introduced and assessed on their value to diagnose LQTS Because these relatively new parameters are used to study QT dynamics, they require evaluation of large numbers of RR- and QT-intervals. Interobserver differences, aberrant T-wave morphologies and changes in heart axis might hamper accurate QT-interval measurements
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