Genotype- and Sex-Specific QT-RR Relationship in the Type-1 Long-QT Syndrome

Heart rate and autonomic biomarkers distinguish convulsive epileptic vs. functional or dissociative seizures

OBJECTIVE

20-40% of individuals whose seizures are not controlled by anti-seizure medications exhibit manifestations comparable to epileptic seizures (ES), but there are no EEG correlates. These events are called functional or dissociative seizures (FDS). Due to limited access to EEG-monitoring and inconclusive results, we aimed to develop an alternative diagnostic tool that distinguishes ES vs. FDS. We evaluated the temporal evolution of ECG-based measures of autonomic function (heart rate variability, HRV) to determine whether they distinguish ES vs. FDS.

METHODS

The prospective study includes patients admitted to the University of Rochester Epilepsy Monitoring Unit. Participants are 18-65 years old, without therapies or co-morbidities associated with altered autonomics. A habitual ES or FDS is recorded during admission. HRV analysis is performed to evaluate the temporal changes in autonomic function during the peri‑ictal period (150-minutes each pre-/post-ictal). We determined if autonomic measures distinguish ES vs. FDS.

RESULTS

The study includes 53 ES and 46 FDS. Temporal evolution of HR and autonomics significantly differ surrounding ES vs. FDS. The pre-to-post-ictal change (delta) in HR differs surrounding ES vs. FDS, stratified for convulsive and non-convulsive events. Post-ictal HR, total autonomic (SDNN & Total Power), vagal (RMSSD & HF), and baroreflex (LF) function differ for convulsive ES vs. convulsive FDS. HR distinguishes non-convulsive ES vs. non-convulsive FDS with ROC>0.7, sensitivity>70%, but specificity<50%. HR-delta and post-ictal HR, SDNN, RMSSD, LF, HF, and Total Power each distinguish convulsive ES vs. convulsive FDS (ROC, 0.83-0.98). Models with HR-delta and post-ictal HR provide the highest diagnostic accuracy for convulsive ES vs. convulsive FDS: 92% sensitivity, 94% specificity, ROC 0.99).

SIGNIFICANCE

HR and HRV measures accurately distinguish convulsive, but not non-convulsive, events (ES vs. FDS). Results establish the framework for future studies to apply this diagnostic tool to more heterogeneous populations, and on out-of-hospital recordings, particularly for populations without access to epilepsy monitoring units.

Dynamic QT response to cold-water face immersion in long-QT syndrome type 3

BACKGROUND

Abnormal dynamics of QT intervals in response to sympathetic nervous system stimulation are used to diagnose long-QT syndrome (LQTS). We hypothesized that parasympathetic stimulation with cold-water face immersion following exercise would influence QT dynamics in patients with LQTS type 3 (LQT3).

METHODS

Study participants (n = 42; mean age = 11.2 years) comprised 20 genotyped LQTS children and 22 healthy children. The LQTS group was divided into LQT3 (n = 12) and non-LQT3 (n = 8) subgroups. Provocative testing for assessing QT dynamics comprised a treadmill exercise followed by cold-water face immersion. The QT intervals were automatically measured at rest and during exercise, recovery, and cold-water face immersion. The QT/heart rate (HR) relationship was visualized by plotting beat-to-beat confluence of the data.

RESULTS

The QT/HR slopes, determined by linear regression analysis, were steeper in the LQTS group than in the control group during exercise and immersion tests: -2.16 ± 0.63 versus -1.21 ± 0.28, P < 0.0001, and -2.02 ± 0.76 vs -0.75 ± 0.24, P < 0.0001, respectively. The LQT3 patients had steeper slopes in the immersion test than did non-LQT3 and control individuals: -2.42 ± 0.52 vs -1.40 ± 0.65, P < 0.0001, and vs -0.75 ± 0.24, P < 0.0001.

CONCLUSIONS

The QT dynamics of LQT3 patients differ from those of other LQTS subtypes during the post-exercise cold-water face immersion test in this study. Abnormal QT dynamics during the parasympathetic provocative test are concordant with the fact that cardiac events occur when HRs are lower or during sleep in LQT3 patients.

Individualized corrected QT interval is superior to QT interval corrected using the Bazett formula in predicting mutation carriage in families with long QT syndrome

BACKGROUND

Long QT syndrome (LQTS) is characterized by reduced penetrance and variable QT prolongation over time, resulting in an estimate of 25% carriers of a pathogenic mutation with a normal corrected QT (QTc) interval on the resting electrocardiogram (ECG).

OBJECTIVE

The purpose of this study was to test the hypothesis that an individualized corrected QT interval derived from 24-hour Holter data more accurately predicts carriage of a pathogenic LQTS mutation than did QT derived from a standard 12-lead ECG and corrected using the Bazett formula (QTc interval).

METHODS

Carriers of a pathogenic LQTS mutation and their genotype-negative family members who had both resting ECG and Holter recordings available were included. Automated and manual measurements of QTc were performed. QTi was derived from 24-hour Holter recordings and defined as the QT value at the intersection of an RR interval of 1000 ms, with the linear regression line fitted through QT-RR data points of each individual patient.

RESULTS

In total, 69 patients with LQTS (23 long QT type 1, 39 long QT type 2, and 7 long QT type 3) and 55 controls were selected. Demographic characteristics were comparable. A comparison of the receiver operating characteristic curves indicates that the test added diagnostic value compared to manual measurement (P = .02) or automated measurement (P = .005). The diagnostic accuracy of manually measured QTc using conventional cutoff criteria was 72%, while it was 92% using a sex-independent QTi cutoff of 445 ms. This was caused by a 39% increase in sensitivity without compromising the specificity.

CONCLUSION

QTi derived from Holter recordings is superior to conventional QTc measured from a standard 12-lead ECG in predicting the mutation carrier state in families with LQTS.

Population-based beat-to-beat QT analysis from Holter recordings in the long QT syndrome

The increasing dissemination of wearable ECG recorders (e.g. Holter, patches, and strap sensors) enables the acquisition of large amounts of data during long periods of time. However, the clinical value of these long-term continuous recordings is hindered by the lack of automatic tools to extract clinically relevant information (other than non-sinus and life-threatening rhythms) from such long-term data, particularly when targeting population-based research. In this work, we propose and test a new tool for analyzing beat-to-beat interval measurements and extracting features from Holter ECGs. Specifically, we assess the adaptation of the QT interval following sudden changes in heart rate in the primary long QT types (1 & 2). We find that in long QT syndrome type 2, certain QT adaptation patterns can indicate a higher risk for cardiac events.

Effect of age and gender on the QTc-interval in healthy individuals and patients with long-QT syndrome

Age- and gender-related differences in QTc-interval are most likely the result of changes in sex-specific hormones. Although the exact mechanisms and pathophysiology of sex hormones on the QTc-interval are not known, testosterone appears to shorten the QTc-interval. In females, however, there is a more complex interaction between progesterone and estrogen. In patients with an impaired repolarization, such as long-QT syndrome (LQTS), the effect of these sex hormones on the QTc-interval is more pronounced with a differing sensitivity between the LQTS genotypes.

Electro-mechanical dysfunction in long QT syndrome: Role for arrhythmogenic risk prediction and modulation by sex and sex hormones

Long QT syndrome (LQTS) is a congenital arrhythmogenic channelopathy characterized by impaired cardiac repolarization. Increasing evidence supports the notion that LQTS is not purely an "electrical" disease but rather an "electro-mechanical" disease with regionally heterogeneously impaired electrical and mechanical cardiac function. In the first part, this article reviews current knowledge on electro-mechanical (dys)function in LQTS, clinical consequences of the observed electro-mechanical dysfunction, and potential underlying mechanisms. Since several novel imaging techniques - Strain Echocardiography (SE) and Magnetic Resonance Tissue Phase Mapping (TPM) - are applied in clinical and experimental settings to assess the (regional) mechanical function, advantages of these non-invasive techniques and their feasibility in the clinical routine are particularly highlighted. The second part provides novel insights into sex differences and sex hormone effects on electro-mechanical cardiac function in a transgenic LQT2 rabbit model. Here we demonstrate that female LQT2 rabbits exhibit a prolonged time to diastolic peak - as marker for contraction duration and early relaxation - compared to males. Chronic estradiol-treatment enhances these differences in time to diastolic peak even more and additionally increases the risk for ventricular arrhythmia. Importantly, time to diastolic peak is particularly prolonged in rabbits exhibiting ventricular arrhythmia - regardless of hormone treatment - contrasting with a lack of differences in QT duration between symptomatic and asymptomatic LQT2 rabbits. This indicates the potential added value of the assessment of mechanical dysfunction in future risk stratification of LQTS patients.

QT/RR curvatures in healthy subjects: sex differences and covariates

Data of a large clinical study were used to investigate how much are the QT/RR patterns in healthy subjects curved and whether these curvatures differ between women and men. Daytime drug-free 12-lead Holter recordings were repeated 4 times in each of 176 female healthy subjects and 176 male healthy subjects aged 32.7 ± 9.1 yr. In each of the subjects, up to 1,440 carefully verified QT interval measurements were obtained with QT/RR hysteresis-corrected RR intervals. Individual subject data were used to fit the following regression equation: QT = χ + (δ/γ)(1 - RR(γ)) + ε, where QT and RR are QT and RR measurements (in s), χ is regression intercept, δ is the QT/RR slope, γ is the QT/RR curvature and provides the lowest regression residual, and ε represents normally distributed zero-centered errors. The bootstrap technique showed the intrasubject reproducibility of QT/RR slopes and curvatures. In women and men, QT/RR curvatures were 0.544 ± 0.661 and 0.797 ± 0.706, respectively (P = 0.0006). The corresponding QT/RR slopes were 0.158 ± 0.030 and 0.139 ± 0.023, respectively (P < 0.0001). QT/RR curvatures were related to QT/RR slopes but not to individually corrected mean QTc intervals or individual QT/RR hysteresis profiles. The individual heart rate correction formula derived from the curvilinear regression provided a significantly lower intrasubject variability of QTc interval than individual optimisation of linear or log-linear QT/RR heart rate corrections. The QT/RR curvature can be reliable measured and expressed numerically. The corresponding heart rate correction formula provides more compact data than the previously proposed approaches. There are substantial sex differences in QT/RR patterns. Women have a QT/RR pattern that is not only steeper than men but also more curved.

The Telemetric and Holter ECG Warehouse (THEW): the first three years of development and research

The Telemetric and Holter ECG Warehouse (THEW) hosts more than 3700 digital 24-Holter ECG recordings from 13 independent studies. In addition to the ECGs, the repository includes patient information in separate clinical database with content varying according to the study focus. In its third year of activities, the THEW database has been accessed by researchers from 37 universities and 16 corporations located in 16 countries worldwide. Twenty publications were released primarily focusing on the development and validation of ECG-based technologies. This communication describes the content of the databases of the repository with brief summary of the research and development projects completed using these data.

Selection of high-risk patients for device intervention with the new advances in technology

The recent clinical therapeutic studies involving high-risk cardiac patients with genetic or acquired heart disease provide valuable insights into the potential for new advances in the technology for improving risk stratification to identify patients who can benefit from device therapy.