Background and purpose: 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.