The usefulness of QT interval measurement as a screening tool for cascade testing in asymptomatic patients at risk of long QT syndrome

Abstract Background Long QT syndrome (LQTS), an inherited arrhythmic syndrome, remains a public health concern with up to 3000 unexpected deaths in the US annually. A simple 12-lead ECG is the most easily accessible tool for initial screening. Purpose To describe the diagnostic utility of the standard QT correction techniques in 12-Lead ECGs, in a screening population of first-degree relatives of persons with LQTS of known genotype. Methods In this single centre study, data were included on consecutive patients undergoing cascade clinical and genetic testing for LQTS, who had a first degree relative with genotype-positive LQTS, from the years 2019 to 2022. Patient demographics, baseline ECG and genetic results were obtained. The QT interval was manually calculated between three independent readers using the tangent method and corrected using the 4 most commonly used formulae: Bazett (BQTc), Fridericia (FreQTc), Framingham (FraQTc) and Hodges (HQTc). The Mean QT was calculated by taking the average of four consecutive QT measurements in lead II or V5. The QT dispersion (QTd), was also calculated by using the formula: QTd = QT max – QT min. Results Data was available on 97 patients from 14 families. The mean age at screening was 44 years, and 51.5% were males. Two-thirds of patients were asymptomatic (n = 74, 76.3%). Fifteen patients had syncopal events. 72.2% (n = 70) of patients had a family history of arrhythmic death. After clinical screening and genotyping, 46.4% (n = 45) patients were gene positive for either KCNQ1 (75.5%) or KCNH2 (24.5%). Patients with prior syncope were more likely to be gene positive (72.7% vs 39.2%, p = 0.005). The 12-Lead ECG derived QTc result is listed in Table 1, with all correction modalities showing a higher corrected QT in the genotype-positive group (p <0.001). The diagnostic performance of BQTc was similar to that of the newer formulae (FreQTc, FraQTc and HQTc) when correcting for heart rate within the range of 60 – 100bpm as listed in Table 2. At a cut-off value of 440ms, BQTc formula had a sensitivity of 51% and a specificity of 84% for predicting genotype pathogenicity as listed in Table 3. The QT dispersion was higher in patients with KCNH2 compared to those with KCNQ1 (122msec, SD 30.5 vs 74.2 msec, SD 30.4, p value <0.001). Patients with KCNH2 were more likely to require an ICD (83.3% vs 16.7%, p <0.001). The mean Schwartz score in gene positive patient was 2.6 compared to 1.9 (p <0.003). Conclusion Formula correction of QT interval to heart rate had good overall diagnostic performance. Both FreQT and FraQT had high AUROC across different heart rates, though there was no statistically significant difference seen between correction formulae. The ECG remains a good preliminary screening tool method for identifying patients with increased risk LQTS in this population. Larger studies are needed to power for comparisons between QT correction methods.