A013 Advanced Electrocardiography Accurately identifies Long QT Syndrome and Genetic Subtype

Abstract

Diagnosis of congenital LQTS can be challenging if the QT interval is normal on conventional 12-lead ECG. Advanced-ECG (A-ECG) analysis uses pattern recognition of both conventional and advanced-ECG parameters, measures from derived vectorcardiography, and waveform complexity from singular value decomposition, to generate probabilistic scores for disease. We aim to validate an A-ECG score for LQTS in a case-control study. Conventional ECG digital files were retrieved from hospital database for LQTS cases (n=21) and age- and sex-matched controls (n=29). A-ECG analysis was performed using conventional and advanced-ECG parameters using logistic regression and linear discriminant analysis applying previously validated LQTS scores. Blinded A-ECG diagnoses were compared with a “crowd” average of three cardiologists. A-ECG had a sensitivity of 81% and specificity of 90% (AUC [95%CI] 0.87 [0.75–0.97]) compared to a single cardiologist (0.74 [0.6-0.86], p = 0.001) or crowd (0.80 [0.67–0.9], p<0.001) and QTc (0.76 [0.61–0.87], p<0.001) in discriminating LQTS from controls (Table 1). 67% of both carriers (n=15) and probands (n=6) had QTc<470ms. A-ECG diagnoses were provided for 3 of 4 asymptomatic gene carriers, labelled false negatives, providing a sensitivity of 95% for detecting cardiac pathology. Average LQTS probability in true versus false positives was 90% and 52% respectively, (95%CI 0.56 to -0.20, p<0.001). False positives had significant alternative cardiac pathology. 80% of A-ECG positive diagnoses of LQTS subtypes (1, 2 and 3), concurred with genetic results in 94% of cases. A-ECG is not only highly sensitive and specific for LQTS but also accurate in identifying genetic subtypes.