QT Variability and Other Electrocardiographic Predictors of Sudden Cardiac Death

This thesis investigates sudden cardiac death, focusing of QT variability, heart-rate variability and other electrocardiographic markers. Topics include: - Normal values for heart-rate variability - Normal values for QT variability - The association of QT variability with sudden cardiac death - The association of QT variability with Heart Failure - The association of thyroid function and Sudden cardiac death - The association of thyroid function with QT variability - The association of COPD with sudden cardiac deat

Validation of automatic measurement of QT interval variability

Background Increased variability of beat-to-beat QT-interval durations on the electrocardiogram (ECG) has been associated with increased risk for fatal and non-fatal cardiac events. However, techniques for the measurement of QT variability (QTV) have not been validated since a gold standard is not available. In this study, we propose a validation method and illustrate its use for the validation of two automatic QTV measurement techniques. Methods Our method generates artificial standard 12-lead ECGs based on the averaged P-QRS-T complexes from a variety of existing ECG signals, with simulated intrinsic (QT interval) and extrinsic (noise, baseline wander, signal length) variations. We quantified QTV by a commonly used measure, short-term QT variability (STV). Using 28,800 simulated ECGs, we assessed the performance of a conventional QTV measurement algorithm, resembling a manual QTV measurement approach, and a more advanced algorithm based on fiducial segment averaging (FSA). Results The results for the conventional algorithm show considerable median absolute differences between the simulated and estimated STV. For the highest noise level, median differences were 4±6 ms in the absence of QTV. Increasing signal length generally yields more accurate STV estimates, but the difference in performance between 30 or 60 beats is small. The FSA algorithm proved to be very accurate, with most median absolute differences less than 0.5 ms, even for the highest levels of disturbance. Conclusions Artificially constructed ECGs with a variety of disturbances allow validation of QTV measurement procedures. The FSA algorithm provides highly accurate STV estimates under varying signal conditions, and performs much better than traditional beat-by-beat analysis. The fully automatic operation of the FSA algorithm enables STV measurement in large sets of ECGs

Corrigendum: Normal Values of Corrected Heart-Rate Variability in 10-Second Electrocardiograms for All Ages

Cardiolog

Serum magnesium and the risk of death from coronary heart disease and sudden cardiac death

Background-Low serum magnesium has been implicated in cardiovascular mortality, but results are conflicting and the pathway is unclear. We studied the association of serum magnesium with coronary heart disease (CHD) mortality and sudden cardiac death (SCD) within the prospective population-based Rotterdam Study, with adjudicated end points and long-term follow-up. Methods and Results-Nine-thousand eight-hundred and twenty participants (mean age 65.1 years, 56.8% female) were included with a median follow-up of 8.7 years. We used multivariable Cox proportional hazard models and found that a 0.1 mmol/L increase in serum magnesium level was associated with a lower risk for CHD mortality (hazard ratio: 0.82, 95% CI 0.70-0.96). Furthermore, we divided serum magnesium in quartiles, with the second and third quartile combined as reference group (0.81-0.88 mmol/L). Low serum magnesium (=0.80 mmol/L) was associated with an increased risk of CHD mortality (N=431, hazard ratio: 1.36, 95% CI 1.09-1.69) and SCD (N=217, hazard ratio: 1.54, 95% CI 1.12-2.11). Low serum magnesium was associated with accelerated subclinical atherosclerosis (expressed as increased carotid intima-media thickness: +0.013 mm, 95% CI 0.005-0.020) and increased QT-interval, mainly through an effect on heart rate (RR-interval: -7.1 ms, 95% CI -13.5 to -0.8). Additional adjustments for carotid intima-media thickness and heart rate did not change the associations with CHD mortality and SCD. Conclusions-Low serum magnesium is associated with an increased risk of CHD mortality and SCD. Although low magnesium was associated with both carotid intima-media thickness and heart rate, this did not explain the relationship between serum magnesium and CHD mortality or SCD. Future studies should focus on why magnesium associates with CHD mortality and SCD and whether intervention reduces these risks

A Combined Linkage and Exome Sequencing Analysis for Electrocardiogram Parameters in the Erasmus Rucphen Family Study

Electrocardiogram (ECG) measurements play a key role in the diagnosis and prediction of cardiac arrhythmias and sudden cardiac death. ECG parameters, such as the PR, QRS, and QT intervals, are known to be heritable and genome-wide association studies of these phenotypes have been successful in identifying common variants; however, a large proportion of the genetic variability of these traits remains to be elucidated. The aim of this study was to discover loci potentially harboring rare variants utilizing variance component linkage analysis in 1547 individuals from a large family-based study, the Erasmus Rucphen Family Study (ERF). Linked regions were further explored using exome sequencing. Five suggestive linkage peaks were identified: two for QT interval (1q24, LOD = 2.63; 2q34, LOD = 2.05), one for QRS interval (1p35, LOD = 2.52) and two for PR interval (9p22, LOD = 2.20; 14q11, LOD = 2.29). Fine-mapping using exome sequence data identified a C > G missense variant (c.713C > G, p.Ser238Cys) in the FCRL2 gene associated with QT (rs74608430; P = 2.8 x 10(-4), minor allele frequency = 0.019). Heritability analysis demonstrated that the SNP explained 2.42% of the trait's genetic variability in ERF (P = 0.02). Pathway analysis suggested that the gene is involved in cytosolic Ca2+ levels (P = 3.3 x 10(-3)) and AMPK stimulated fatty acid oxidation in muscle (P = 4.1 x 10(-3)). Look-ups in bioinformatics resources showed that expression of FCRL2 is associated with ARHGAP24 and SETBP1 expression. This finding was not replicated in the Rotterdam study. Combining the bioinformatics information with the association and linkage analyses, FCRL2 emerges as a strong candidate gene for QT interval