If only a standard electrocardiogram (ECG) is available, at least 25 % of patients with long QT syndrome (LQTS) may be missed. Our goal is to quantify abnormal electrical activity and to develop an ECG decision rule for the patients with LQTS.
Methods
One hundred forty-one subjects were included in this study (71 patients with LQTS and 70 healthy subjects). A 12-lead digital ECG was recorded for each subject and analyzed using the CAVIAR (comparative analysis of ECG-VCG and their interpretation with auto-reference to the patient) method.
Results
A decision tree involving criteria based on 3 spatiotemporal ECG measurements—the QT interval and the maximum amplitude of the T wave, both corrected from heart rate, and the loss of planarity of the end of QRS—identified patients with LQTS from healthy subjects with a sensitivity of 89 % , a specificity of 96 % , and a total accuracy of 92 % .
Conclusions
This study suggests that 3-dimensional ECG analysis may improve the detection of patients with LQTS.
