Diagnostic Accuracy of the Standing Test in Adults Suspected for Congenital Long-QT Syndrome.

Background An elegant bedside provocation test has been shown to aid the diagnosis of long-QT syndrome (LQTS) in a retrospective cohort by evaluation of QT intervals and T-wave morphology changes resulting from the brief tachycardia provoked by standing. We aimed to prospectively determine the potential diagnostic value of the standing test for LQTS. Methods and Results In adults suspected for LQTS who had a standing test, the QT interval was assessed manually and automated. In addition, T-wave morphology changes were determined. A total of 167 controls and 131 genetically confirmed patients with LQTS were included. A prolonged heart rate-corrected QT interval (QTc) (men ≥430 ms, women ≥450 ms) at baseline before standing yielded a sensitivity of 61% (95% CI, 47-74) in men and 54% (95% CI, 42-66) in women, with a specificity of 90% (95% CI, 80-96) and 89% (95% CI, 81-95), respectively. In both men and women, QTc≥460 ms after standing increased sensitivity (89% [95% CI, 83-94]) but decreased specificity (49% [95% CI, 41-57]). Sensitivity further increased (P<0.01) when a prolonged baseline QTc was accompanied by a QTc≥460 ms after standing in both men (93% [95% CI, 84-98]) and women (90% [95% CI, 81-96]). However, the area under the curve did not improve. T-wave abnormalities after standing did not further increase the sensitivity or the area under the curve significantly. Conclusions Despite earlier retrospective studies, a baseline ECG and the standing test in a prospective evaluation displayed a different diagnostic profile for congenital LQTS but no unequivocal synergism or advantage. This suggests that there is markedly reduced penetrance and incomplete expression in genetically confirmed LQTS with retention of repolarization reserve in response to the brief tachycardia provoked by standing.

Growth of the aortic root in children and young adults with Marfan syndrome.

OBJECTIVES: The primary aim was to gain insight into the growth of the aortic root in children and young adults with Marfan syndrome (MFS). Furthermore, we aimed to identify a clinical profile of patients with MFS who require an aortic root replacement at a young age with specific interest in age, sex, height and fibrillin-1 (FBN1) genotype. METHODS: Aortic root dimensions of 97 patients with MFS between 0 year and 20 years and 30 controls were serially assessed with echocardiography. Trends were analysed using a linear mixed-effect model. Additionally, including only patients with MFS, we allowed trends to differ by sex, aortic root replacement and type of FBN1 mutation. RESULTS: Average aortic root dilatation in patients with MFS became more pronounced after the age of 8 years. In the MFS cohort, male patients had a significantly greater aortic root diameter than female patients, which was in close relationship with patient height. There was no difference in aortic root growth between children with dominant negative (DN) or haploinsufficient FBN1 mutations. However, DN-FBN1 variants resulting in loss of cysteine content were associated with a more severe phenotype. Eleven children needed an aortic root replacement. Compared with patients with MFS without aortic root surgery, these children had a significantly larger aortic root diameter from an early age. CONCLUSIONS: This study provides clinically useful longitudinal growth charts on aortic root growth in children and young adults with MFS. Children requiring prophylactic aortic root replacement during childhood can be identified at a young age. Our growth charts can help clinicians in decision making with regard to follow-up and prophylactic therapy. Loss of cysteine content in the FBN1 protein was associated with larger aortic root dimensions.

Diagnostic accuracy of the response to the brief tachycardia provoked by standing in children suspected for long QT syndrome.

BACKGROUND: Adult long QT syndrome (LQTS) patients have inadequate corrected QT interval (QTc) shortening and an abnormal T-wave response to the sudden heart rate acceleration provoked by standing. In adults, this knowledge can be used to aid an LQTS diagnosis and, possibly, for risk stratification. However, data on the diagnostic value of the standing test in children are currently limited. OBJECTIVE: To determine the potential value of the standing test to aid LQTS diagnostics in children. METHODS: In a prospective cohort including children (≤18 years) who had a standing test, comprehensive analyses were performed including manual and automated QT interval assessments and determination of T-wave morphology changes. RESULTS: We included 47 LQTS children and 86 control children. At baseline, the QTc that identified LQTS children with a 90% sensitivity was 435 ms, which yielded a 65% specificity. A QTc ≥ 490 ms after standing only slightly increased sensitivity (91%, 95% confidence interval [CI]: 80%-98%) and slightly decreased specificity (58%, 95% CI: 47%-70%). Sensitivity increased slightly more when T-wave abnormalities were present (94%, 95% CI: 82%-99%; specificity 53%, 95% CI: 42%-65%). When a baseline QTc ≥ 440 ms was accompanied by a QTc ≥ 490 ms and T-wave abnormalities after standing, sensitivity further increased (96%, 95% CI: 85%-99%) at the expense of a further specificity decrease (41%, 95% CI: 30%-52%). Beat-to-beat analysis showed that 30 seconds after standing, LQTS children had a greater increase in heart rate compared to controls, which was more evidently present in LQTS boys and LQTS type 1 children. CONCLUSION: In children, the standing test has limited additive diagnostic value for LQTS over a baseline electrocardiogram, while T-wave abnormalities after standing also have limited additional value. The standing test for LQTS should only be used with caution in children.

Improving long QT syndrome diagnosis by a polynomial-based T-wave morphology characterization.

BACKGROUND: Diagnosing long QT syndrome (LQTS) remains challenging because of a considerable overlap in QT interval between patients with LQTS and healthy subjects. Characterizing T-wave morphology might improve LQTS diagnosis. OBJECTIVE: The purpose of this study was to improve LQTS diagnosis by combining new polynomial-based T-wave morphology parameters with the corrected QT interval (QTc), age, and sex in a model. METHODS: A retrospective cohort consisting of 333 patients with LQTS and 345 genotype-negative family members was used in this study. For each patient, a linear combination of the first 2 Hermite-Gauss (HG) polynomials was fitted to the STT segments of an average complex of all precordial leads and limb leads I and II. The weight coefficients as well as the error of the best fit were used to characterize T-wave morphology. Subjects were classified as patients with LQTS or controls by clinical QTc cutoffs and 3 support vector machine models fed with different features. An external cohort consisting of 72 patients and 45 controls was finally used to check the robustness of the models. RESULTS: Baseline QTc cutoffs were specific but had low sensitivity in diagnosing LQTS. The model with T-wave morphology features, QTc, age, and sex had the best overall accuracy (84%), followed by a model with QTc, age, and sex (79%). The model with T-wave morphology features especially performed better in LQTS type 3 patients (69%). CONCLUSION: T-wave morphologies can be characterized by fitting a linear combination of the first 2 Hermite-Gauss polynomials. Adding T-wave morphology characterization to age, sex, and QTc in a support vector machine model improves LQTS diagnosis.

Support vector machine-based assessment of the T-wave morphology improves long QT syndrome diagnosis.

AIMS: Diagnosing long QT syndrome (LQTS) is challenging due to a considerable overlap of the QTc-interval between LQTS patients and healthy controls. The aim of this study was to investigate the added value of T-wave morphology markers obtained from 12-lead electrocardiograms (ECGs) in diagnosing LQTS in a large cohort of gene-positive LQTS patients and gene-negative family members using a support vector machine. METHODS AND RESULTS: A retrospective study was performed including 688 digital 12-lead ECGs recorded from genotype-positive LQTS patients and genotype-negative relatives at their first visit. Two models were trained and tested equally: a baseline model with age, gender, RR-interval, QT-interval, and QTc-intervals as inputs and an extended model including morphology features as well. The best performing baseline model showed an area under the receiver-operating characteristic curve (AUC) of 0.821, whereas the extended model showed an AUC of 0.901. Sensitivity and specificity at the maximal Youden's indexes changed from 0.694 and 0.829 with the baseline model to 0.820 and 0.861 with the extended model. Compared with clinically used QTc-interval cut-off values (>480 ms), the extended model showed a major drop in false negative classifications of LQTS patients. CONCLUSION: The support vector machine-based extended model with T-wave morphology markers resulted in a major rise in sensitivity and specificity at the maximal Youden's index. From this, it can be concluded that T-wave morphology assessment has an added value in the diagnosis of LQTS.

SCN5A mutations in 442 neonates and children: genotype-phenotype correlation and identification of higher-risk subgroups.

Aims: To clarify the clinical characteristics and outcomes of children with SCN5A-mediated disease and to improve their risk stratification. Methods and results: A multicentre, international, retrospective cohort study was conducted in 25 tertiary hospitals in 13 countries between 1990 and 2015. All patients ≤16 years of age diagnosed with a genetically confirmed SCN5A mutation were included in the analysis. There was no restriction made based on their clinical diagnosis. A total of 442 children {55.7% boys, 40.3% probands, median age: 8.0 [interquartile range (IQR) 9.5] years} from 350 families were included; 67.9% were asymptomatic at diagnosis. Four main phenotypes were identified: isolated progressive cardiac conduction disorders (25.6%), overlap phenotype (15.6%), isolated long QT syndrome type 3 (10.6%), and isolated Brugada syndrome type 1 (1.8%); 44.3% had a negative electrocardiogram phenotype. During a median follow-up of 5.9 (IQR 5.9) years, 272 cardiac events (CEs) occurred in 139 (31.5%) patients. Patients whose mutation localized in the C-terminus had a lower risk. Compound genotype, both gain- and loss-of-function SCN5A mutation, age ≤1 year at diagnosis in probands and age ≤1 year at diagnosis in non-probands were independent predictors of CE. Conclusion: In this large paediatric cohort of SCN5A mutation-positive subjects, cardiac conduction disorders were the most prevalent phenotype; CEs occurred in about one-third of genotype-positive children, and several independent risk factors were identified, including age ≤1 year at diagnosis, compound mutation, and mutation with both gain- and loss-of-function.

Left Ventricular Isovolumetric Relaxation Time Is Prolonged in Fetal Long-QT Syndrome.

BACKGROUND: Long-QT syndrome (LQTS), an inherited cardiac repolarization disorder, is an important cause of fetal and neonatal mortality. Detecting LQTS prenatally is challenging. A fetal heart rate (FHR) less than third percentile for gestational age is specific for LQTS, but the sensitivity is only ≈50%. Left ventricular isovolumetric relaxation time (LVIRT) was evaluated as a potential diagnostic marker for fetal LQTS. METHODS AND RESULTS: LV isovolumetric contraction time, LV ejection time, LVIRT, cycle length, and FHR were measured using pulsed Doppler waveforms in fetuses. Time intervals were expressed as percentages of cycle length, and the LV myocardial performance index was calculated. Single measurements were stratified by gestational age and compared between LQTS fetuses and controls. Receiver-operator curves were performed for FHR and normalized LVIRT (N-LVIRT). A linear mixed-effect model including multiple measurements was used to analyze trends in FHR, N-LVIRT, and LV myocardial performance index. There were 33 LQTS fetuses and 469 controls included. In LQTS fetuses, the LVIRT was prolonged in all gestational age groups (P<0.001), as was the N-LVIRT. The best cutoff to diagnose LQTS was N-LVIRT ≥11.3 at ≤20 weeks (92% sensitivity, 70% specificity). Simultaneous analysis of N-LVIRT and FHR improved the sensitivity and specificity for LQTS (area under the curve=0.96; 95% confidence interval, 0.82-1.00 at 21-30 weeks). N-LVIRT, LV myocardial performance index, and FHR trends differed significantly between LQTS fetuses and controls through gestation. CONCLUSIONS: The LVIRT is prolonged in LQTS fetuses. Findings of a prolonged N-LVIRT and sinus bradycardia can improve the prenatal detection of fetal LQTS.

The development and validation of an easy to use automatic QT-interval algorithm.

BACKGROUND: To 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. OBJECTIVE: To 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. METHODS: Additionally 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. RESULTS: After 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. CONCLUSION: Our automated algorithm provides reliable beat-to-beat QT-interval assessment, robust to heart axis and T-wave morphology.

Effect of Age and Sex on the QTc Interval in Children and Adolescents With Type 1 and 2 Long-QT Syndrome.

BACKGROUND: In congenital long-QT syndrome, age, sex, and genotype have been associated with cardiac events, but their effect on the trend in QTc interval has never been established. We, therefore, aimed to assess the effect of age and sex on the QTc interval in children and adolescents with type 1 (LQT1) and type 2 (LQT2) long-QT syndrome. METHODS AND RESULTS: QTc intervals of 12-lead resting electrocardiograms were determined, and trends over time were analyzed using a linear mixed-effects model. The study included 278 patients with a median follow-up of 4 years (interquartile range, 1-9) and a median number of 6 (interquartile range, 2-10) electrocardiograms per patient. Both LQT1 and LQT2 male patients showed QTc interval shortening after the onset of puberty. In LQT2 male patients, this was preceded by a progressive QTc interval prolongation. In LQT1, after the age of 12 years, male patients had a significantly shorter QTc interval than female patients. In LQT2, during the first years of life and from 14 to 26 years, male patients had a significantly shorter QTc interval than female patients. On the contrary, between 5 and 14 years, LQT2 male patients had significantly longer QTc interval than LQT2 female patients. CONCLUSIONS: There is a significant effect of age and sex on the QTc interval in long-QT syndrome, with a unique pattern per genotype. The age of 12 to 14 years is an important transitional period. In the risk stratification and management of long-QT syndrome patients, clinicians should be aware of these age-, sex-, and genotype-related trends in QTc interval and especially the important role of the onset of puberty.

Syncope in Brugada syndrome: prevalence, clinical significance, and clues from history taking to distinguish arrhythmic from nonarrhythmic causes.

BACKGROUND: Syncope in Brugada syndrome (BrS) patients is a sign of increased risk for sudden cardiac death and usually is ascribed to cardiac arrhythmias. However, syncope often occurs in the general population, mostly from nonarrhythmic causes (eg, reflex syncope). OBJECTIVE: The purpose of this study was to distinguish arrhythmic events from nonarrhythmic syncope in BrS and to establish the clinical relevance of nonarrhythmic syncope. METHODS: We reviewed the patient records of 342 consecutively included BrS patients and conducted systematic interviews in 141 patients with aborted cardiac arrest (ACA) or syncope. RESULTS: In total, 23 patients (7%) experienced ECG-documented ACA and 118 (34%) syncope; of these 118, 67 (57%) were diagnosed with suspected nonarrhythmic syncope. Compared to suspected nonarrhythmic syncope patients, ACA patients were older at first event (45 vs 20 years), were more likely to be male (relative risk 2.1) and to have urinary incontinence (relative risk 4.6), and were less likely to report prodromes. ACA was never triggered by hot/crowded surroundings, pain or other emotional stress, seeing blood, or prolonged standing. During follow-up (median 54 months), ACA rate was 8.7% per year among ACA patients and 0% per year among suspected nonarrhythmic syncope patients. CONCLUSION: Syncope, especially nonarrhythmic syncope, often occurs in BrS. The high incidence of nonarrhythmic syncope must be taken into account during risk stratification. Arrhythmic events and nonarrhythmic syncope may be distinguished by clinical characteristics (absence of prodromes and, particularly, specific triggers), demonstrating the importance of systematic history taking.