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

[This corrects the article DOI: 10.3389/fphys.2018.00424.].

Normal Values of QT Variability in 10-s Electrocardiograms for all Ages.

Aims: QT variability is a promising electrocardiographic marker. It has been studied as a screening tool for coronary artery disease and left ventricular hypertrophy, and increased QT variability is a known risk factor for sudden cardiac death. Considering that comprehensive normal values for QT variability were lacking, we set out to establish these in standard 10-s electrocardiograms (ECGs) covering both sexes and all ages. Methods: Ten-second, 12-lead ECGs were provided by five Dutch population studies (Pediatric Normal ECG Study, Leiden University Einthoven Science Project, Prevention of Renal and Vascular End-stage Disease Study, Utrecht Health Project, Rotterdam Study). ECGs were recorded digitally and processed by well-validated analysis software. We selected cardiologically healthy participants, 46% being women. Ages ranged from 11 days to 91 years. After quality control, 13,828 ECGs were available. We assessed three markers: standard deviation of QT intervals (SDqt), short-term QT variability (STVqt), and QT variability index (QTVI). Results: For SDqt and STVqt, the median and the lower limit of normal remained stable with age. The upper limit of normal declined until around age 45, and increased strongly in the elderly, notably so in women. This implies that a subset of the population, small enough not to have appreciable effect on the median, shows a high degree of QT variability with a possible risk of arrhythmias or worse, especially in women. Otherwise, sex differences were negligible in all three measurements. For QTVI, median, and normal limits decreased until age 20, and steadily went up afterwards except for the lower limit of normal, which flattens off after age 65. Conclusion: We report the first set of normal values for QT variability based on 10-s ECGs, for all ages and both sexes.

Comparison of automated interval measurements by widely used algorithms in digital electrocardiographs.

BACKGROUND: Automated measurements of electrocardiographic (ECG) intervals by current-generation digital electrocardiographs are critical to computer-based ECG diagnostic statements, to serial comparison of ECGs, and to epidemiological studies of ECG findings in populations. A previous study demonstrated generally small but often significant systematic differences among 4 algorithms widely used for automated ECG in the United States and that measurement differences could be related to the degree of abnormality of the underlying tracing. Since that publication, some algorithms have been adjusted, whereas other large manufacturers of automated ECGs have asked to participate in an extension of this comparison. METHODS: Seven widely used automated algorithms for computer-based interpretation participated in this blinded study of 800 digitized ECGs provided by the Cardiac Safety Research Consortium. All tracings were different from the study of 4 algorithms reported in 2014, and the selected population was heavily weighted toward groups with known effects on the QT interval: included were 200 normal subjects, 200 normal subjects receiving moxifloxacin as part of an active control arm of thorough QT studies, 200 subjects with genetically proved long QT syndrome type 1 (LQT1), and 200 subjects with genetically proved long QT syndrome Type 2 (LQT2). RESULTS: For the entire population of 800 subjects, pairwise differences between algorithms for each mean interval value were clinically small, even where statistically significant, ranging from 0.2 to 3.6milliseconds for the PR interval, 0.1 to 8.1milliseconds for QRS duration, and 0.1 to 9.3milliseconds for QT interval. The mean value of all paired differences among algorithms was higher in the long QT groups than in normals for both QRS duration and QT intervals. Differences in mean QRS duration ranged from 0.2 to 13.3milliseconds in the LQT1 subjects and from 0.2 to 11.0milliseconds in the LQT2 subjects. Differences in measured QT duration (not corrected for heart rate) ranged from 0.2 to 10.5milliseconds in the LQT1 subjects and from 0.9 to 12.8milliseconds in the LQT2 subjects. CONCLUSIONS: Among current-generation computer-based electrocardiographs, clinically small but statistically significant differences exist between ECG interval measurements by individual algorithms. Measurement differences between algorithms for QRS duration and for QT interval are larger in long QT interval subjects than in normal subjects. Comparisons of population study norms should be aware of small systematic differences in interval measurements due to different algorithm methodologies, within-individual interval measurement comparisons should use comparable methods, and further attempts to harmonize interval measurement methodologies are warranted.

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

Purpose: Heart-rate variability (HRV) measured on standard 10-s electrocardiograms (ECGs) has been associated with increased risk of cardiac and all-cause mortality, but age- and sex-dependent normal values have not been established. Since heart rate strongly affects HRV, its effect should be taken into account. We determined a comprehensive set of normal values of heart-rate corrected HRV derived from 10-s ECGs for both children and adults, covering both sexes. Methods: Five population studies in the Netherlands (Pediatric Normal ECG Study, Leiden University Einthoven Science Project, Prevention of Renal and Vascular End-stage Disease Study, Utrecht Health Project, Rotterdam Study) provided 10-s, 12-lead ECGs. ECGs were stored digitally and analyzed by well-validated analysis software. We included cardiologically healthy participants, 42% being men. Their ages ranged from 11 days to 91 years. After quality control, 13,943 ECGs were available. Heart-rate correction formulas were derived using an exponential model. Two time-domain HRV markers were analyzed: the corrected standard deviation of the normal-to-normal RR intervals (SDNNc) and corrected root mean square of successive RR-interval differences (RMSSDc). Results: There was a considerable age effect. For both SDNNc and RMSSDc, the median and the lower limit of normal decreased steadily from birth until old age. The upper limit of normal decreased until the age of 60, but increased markedly after that age. Differences of the median were minimal between men and women. Conclusion: We report the first comprehensive set of normal values for heart-rate corrected 10-s HRV, which can be of value in clinical practice and in further research.

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.

Normal values of the electrocardiogram for ages 16-90 years.

INTRODUCTION: To establish an up-to-date and comprehensive set of normal values for the clinically current measurements in the adult ECG, covering all ages for both sexes. METHODS: The study population included 13,354 individuals, taken from four population studies in The Netherlands, ranging in age from 16 to 90 years (55% men) and cardiologically healthy by commonly accepted criteria. Standard 12-lead ECGs were available for all participants. The ECGs were processed by a well-validated computer program. Normal limits were taken as the 2nd and 98th percentiles of the measurement distribution per age group. RESULTS: Our study corroborates many findings of previous studies, but also provides more differentiated results, in particular for the older age groups. Age trends were apparent for the QTc interval, QRS axis, and indices of left ventricular hypertrophy. Amplitudes in the left precordial leads showed a substantial increase in the older age groups for women, but not for men. Sex-dependent differences were apparent for most ECG parameters. All results are available on the Website www.normalecg.org, both in tabular and in graphical format. CONCLUSIONS: We determined age- and sex-dependent normal values of the adult ECG. Our study distinguishes itself from other studies by the large size of the study population, comprising both sexes, the broad range of ages, and the exhaustive set of measurements. Our results emphasize that most diagnostic ECG criteria should be age- and sex-specific.

Short-term QT variability markers for the prediction of ventricular arrhythmias and sudden cardiac death: a systematic review.

Sudden cardiac death (SCD) is a major health burden and is primarily caused by ventricular arrhythmias. Currently, the most well-known marker for the risk of ventricular arrhythmias is QT/QTc prolongation. Animal studies indicate that QT variability might be a better indicator. Our objective was to give an overview of the literature on QT variability in humans, therefore we performed a free-text search in PubMed and Embase from inception through February 2013. We identified nine QT variability markers in 109 studies reporting on QT variability markers, measured on the surface ECG. QT variability can be distinguished using two characteristics: heart rate normalisation and whether QT interval is measured on consecutive beats. Most study populations were small (median 48 subjects, range 1-805) and different methods, time intervals and leads for measurement were used. QT variability markers were determinants for the risk of ventricular arrhythmias, (sudden) cardiac death and total mortality. Few studies compared the predictive value of QT variability with that of QT/QTc prolongation. A study comparing all different QT variability markers is lacking. In conclusion, QT variability markers are potential determinants of ventricular arrhythmias and cardiac mortality. However, it is unclear which marker and methodology are clinically most useful as well as what reference values are reliable. More studies on larger datasets are needed to find the most accurate marker for the prediction of arrhythmias and SCD to assess its value in addition to QT/QTc duration and its role in drug-induced arrhythmia and sudden death.

Professor Herman Burger (1893-1965), eminent teacher and scientist, who laid the theoretical foundations of vectorcardiography--and electrocardiography.

Einthoven not only designed a high quality instrument, the string galvanometer, for recording the ECG, he also shaped the conceptual framework to understand it. He reduced the body to an equilateral triangle and the cardiac electric activity to a dipole, represented by an arrow (i.e. a vector) in the triangle's center. Up to the present day the interpretation of the ECG is based on the model of a dipole vector being projected on the various leads. The model is practical but intuitive, not physically founded. Burger analysed the relation between heart vector and leads according to the principles of physics. It then follows that an ECG lead must be treated as a vector (lead vector) and that the lead voltage is not simply proportional to the projection of the vector on the lead, but must be multiplied by the value (length) of the lead vector, the lead strength. Anatomical lead axis and electrical lead axis are different entities and the anatomical body space must be distinguished from electrical space. Appreciation of these underlying physical principles should contribute to a better understanding of the ECG. The development of these principles by Burger is described, together with some personal notes and a sketch of the personality of this pioneer of medical physics.

Comparison of prognosis in unrecognized versus recognized myocardial infarction in men versus women >55 years of age (from the Rotterdam Study).

Unrecognized myocardial infarction (MI) is frequent in the general population. Its prognosis is reported to be at least as unpropitious as that of recognized MI, particularly in men. However, contemporary data with long follow-up are lacking. The aims of this study were to investigate the long-term prognosis of unrecognized MI with respect to all-cause and cause-specific mortality and to investigate possible differences in prognosis by gender. In the population-based Rotterdam Study (2,672 men and 3,862 women), the presence of unrecognized MI and recognized MI was determined at baseline (1990 to 1993). The cohort was followed for nearly 2 decades for all-cause and cause-specific mortality. During 82,268 patient-years of follow-up (median 15.6 years) 3,412 patients died (1,300 from cardiovascular causes). Men and women with recognized and unrecognized MIs had increased total mortality rates compared with those without MIs. Hazard ratios (HRs) for men and women were 1.57 (95% confidence interval [CI] 1.36 to 1.81) and 1.89 (95% CI 1.56 to 2.30) for recognized MI and 1.72 (95% CI 1.43 to 2.07) and 1.36 (95% CI 1.14 to 1.61) for unrecognized MI. Unrecognized MI was associated with increased risks for cardiovascular mortality (men: HR 2.19, 95% CI 1.66 to 2.91; women: HR 1.36, 95% CI 1.03 to 1.81) and noncardiovascular mortality (men: HR 1.47, 95% CI 1.14 to 1.89; women: HR 1.39, 95% CI 1.10 to 1.75). In conclusion, the long-term prognosis of patients with unrecognized MIs is worse compared with those without MIs and applies not only to cardiovascular mortality but also to noncardiovascular mortality. In men, the prognosis is as unfavorable as that of patients with recognized MIs.

Domperidone and ventricular arrhythmia or sudden cardiac death: a population-based case-control study in the Netherlands.

BACKGROUND: Recently, a 4-fold increase in risk of sudden cardiac death (SCD) was reported for domperidone in a study that focused on corrected QT interval (QTc)-prolonging drugs as a class and their association with SCD. OBJECTIVE: To evaluate the association between the use of domperidone and serious non-fatal ventricular arrhythmia (VA) and SCD in the general population. METHODS: We performed a population-based, case-control study during 1996-2007 in the Integrated Primary Care Information (IPCI) database, a longitudinal general practice research database in the Netherlands. We included all patients aged ≥18 years without cancer in the source population. We studied the association between the use of domperidone by recency of use (current, past and none) and daily dose, and the risk of serious non-fatal VA or SCD. Cases were defined as a natural death due to cardiac causes heralded by abrupt loss of consciousness within 1 hour after the onset of acute symptoms or an unwitnessed, unexpected death of someone seen in a stable medical condition <24 hours previously with no evidence of a non-cardiac cause. Controls were randomly drawn from the source population and matched to cases on age, sex, practice and index date. We compared the exposure odds for SCD alone and VA plus SCD by means of conditional logistic regression while adjusting for all available confounders. In addition, we stratified by insurance type. RESULTS: The study population comprised 1366 cases (62 VA and 1304 SCD) and 14114 matched controls. Of all cases, ten patients were current domperidone users at the index date, all with SCD. The matched unadjusted odds ratio of domperidone and SCD was 3.72 (95% CI 1.72, 8.08). Daily doses >30 mg were associated with a significant increased risk of SCD (adjusted odds ratio [OR(adj)] 11.4 [95% CI 1.99, 65.2]). Since there was a near interaction with health insurance (p = 0.050), all analyses were stratified by insurance. In publicly insured patients, seven cases were current users at the index date. Current use was associated with a significant increased risk of SCD (OR(adj) 4.17 [95% CI 1.33, 13.1]). Amongst privately insured patients there was one domperidone-exposed case, and amongst non-insured there were two. CONCLUSIONS: Current use of domperidone, especially high doses, is associated with an increased risk of SCD. We could not demonstrate an effect of domperidone on non-fatal VA due to absence of exposed cases.

Local depolarization abnormalities are the dominant pathophysiologic mechanism for type 1 electrocardiogram in brugada syndrome a study of electrocardiograms, vectorcardiograms, and body surface potential maps during ajmaline provocation.

OBJECTIVES: We sought to obtain new insights into the pathophysiologic basis of Brugada syndrome (BrS) by studying changes in various electrocardiographic depolarization and/or repolarization variables that occurred with the development of the signature type 1 BrS electrocardiogram (ECG) during ajmaline provocation testing. BACKGROUND: BrS is associated with sudden cardiac death. Its pathophysiologic basis, although unresolved, is believed to reside in abnormal cardiac depolarization or abnormal repolarization. METHODS: Ajmaline provocation was performed in 269 patients suspected of having BrS with simultaneous recording of ECGs, vectorcardiograms, and 62-lead body surface potential maps. RESULTS: A type 1 ECG was elicited in 91 patients (BrS patients), 162 patients had a negative test result (controls), and 16 patients had an abnormal test result. Depolarization abnormalities were more prominent in BrS patients and were mapped to the right ventricle (RV) by longer right precordial filtered QRS complex durations (142 +/- 23 ms vs. 125 +/- 14 ms, p < 0.01) and right terminal conduction delay (60 +/- 11 ms vs. 53 +/- 9 ms, p < 0.01). Repolarization abnormalities remained concordant with depolarization abnormalities as indicated by steady low nondipolar content (12 +/- 8% vs. 8 +/- 4%, p = NS), lower spatial QRS-T integrals (33 +/- 12 mV.ms vs. 40 +/- 16 mV.ms, p < 0.05), similar spatial QRS-T angles (92 +/- 39 degrees vs. 87 +/- 31 degrees , p = NS), similar T(peak)-T(end) interval (143 +/- 36 ms vs. 138 +/- 25 ms, p = NS), and similar T(peak)-T(end) dispersion (47 +/- 37 ms vs. 45 +/- 27 ms, p = NS). CONCLUSIONS: The type 1 BrS ECG is characterized predominantly by localized depolarization abnormalities, notably (terminal) conduction delay in the RV, as assessed with complementary noninvasive electrocardiographic techniques. We could not define a separate role for repolarization abnormalities but suggest that the typical signs of repolarization derangements seen on the ECG are secondary to these depolarization abnormalities.