Velislav Batchvarov

Measurement, interpretation and clinical potential of QT dispersion.

QT dispersion was originally proposed to measure spatial dispersion of ventricular recovery times. Later, it was shown that QT dispersion does not directly reflect the dispersion of recovery times and that it results mainly from variations in the T loop morphology and the error of QT measurement. The reliability of both automatic and manual measurement of QT dispersion is low and significantly lower than that of the QT interval. The measurement error is of the order of the differences between different patient groups. The agreement between automatic and manual measurement is poor. There is little to choose between various QT dispersion indices, as well as between different lead systems for their measurement. Reported values of QT dispersion vary widely, e.g., normal values from 10 to 71 ms. Although QT dispersion is increased in cardiac patients compared with healthy subjects and prognostic value of QT dispersion has been reported, values are largely overlapping, both between healthy subjects and cardiac patients and between patients with and without adverse outcome. In reality, QT dispersion is a crude and approximate measure of abnormality of the complete course of repolarization. Probably only grossly abnormal values (e.g. > or =100 ms), outside the range of measurement error may potentially have practical value by pointing to a grossly abnormal repolarization. Efforts should be directed toward established as well as new methods for assessment and quantification of repolarization abnormalities, such as principal component analysis of the T wave, T loop descriptors, and T wave morphology and wavefront direction descriptors.

Relation between QT and RR intervals is highly individual among healthy subjects: implications for heart rate correction of the QT interval

Objective: To compare the QT/RR relation in healthy subjects in order to investigate the differences in optimum heart rate correction of the QT interval. Methods: 50 healthy volunteers (25 women, mean age 33.6 (9.5) years, range 19–59 years) took part. Each subject underwent serial 12 lead electrocardiographic monitoring over 24 hours with a 10 second ECG obtained every two minutes. QT intervals and heart rates were measured automatically. In each subject, the QT/RR relation was modelled using six generic regressions, including a linear model (QT = β + α × RR), a hyperbolic model (QT = β + α/RR), and a parabolic model (QT = β × RRα). For each model, the parallelism and identity of the regression lines in separate subjects were statistically tested. Results: The patterns of the QT/RR relation were very different among subjects. Regardless of the generic form of the regression model, highly significant differences were found not only between the regression lines but also between their slopes. For instance, with the linear model, the individual slope (parameter α) of any subject differed highly significantly (p < 0.000001) from the linear slope of no fewer than 21 (median 32) other subjects. The linear regression line of 20 subjects differed significantly (p < 0.000001) from the linear regression lines of each other subject. Conversion of the QT/RR regressions to QTc heart rate correction also showed substantial intersubject differences. Optimisation of the formula QTc = QT/RRα led to individual values of α ranging from 0.234 to 0.486. Conclusion: The QT/RR relation exhibits a very substantial intersubject variability in healthy volunteers. The hypothesis underlying each prospective heart rate correction formula that a “physiological” QT/RR relation exists that can be mathematically described and applied to all people is incorrect. Any general heart rate correction formula can be used only for very approximate clinical assessment of the QTc interval over a narrow window of resting heart rates. For detailed precise studies of the QTc interval (for example, drug induced QT interval prolongation), the individual QT/RR relation has to be taken into account.

COMPARISON OF DIFFERENT METHODS FOR MANUAL P WAVE DURATION MEASUREMENT IN 12-LEAD ELECTROCARDIOGRAMS

To determine whether different methods for the manual measurement of P wave duration are mutually consistent, we evaluated the intraobserver and interobserver errors of P wave measurements obtained in three different ways: (1) by cursor on a high resolution computer screen (on screen), (2) by calipers and a magnifying glass (on paper), and (3) by a high resolution digitizing board (on board). The agreement between the methods was assessed in 30 normal subjects and 30 patients with a history of atrial fibrillation. The maximum P wave duration (P maximum), the minimum P wave duration (P minimum), mean P wave duration (P mean), P wave dispersion (P dispersion = P maximum ‐ P minimum), and the standard deviation of the P wave duration in all measured leads (P SD) were calculated from a 12‐lead electrocardiogram in each subject. Only P maximum, P mean, and P dispersion were significantly higher in patients than in controls with all three methods. Intraobserver and interobserver relative errors were significantly different among the three methods; the lowest errors were associated with the on‐screen measurement. The agreement between the three different methods was acceptable for P maximum, P mean, and P SD and rather poor for P minimum and P dispersion in both groups. The differences of the measurement by different methods did not consistently differ between the two groups. Hence, the on‐screen measurements are consistent with other manual methods and provide more stable results. Manual measurement of ECG patterns should be preferably performed with digital ECG recordings displayed on a high resolution computer screen.

Sex differences in the rate dependence of the T wave descending limb

OBJECTIVE The interval from the peak to the end of the T wave (TpTe) has been proposed to reflect the heterogeneity of action potential durations within the ventricular wall. Several studies have previously described TpTe to be independent of heart rate, which contradicts the in vitro observation of marked changes in transmural repolarisation heterogeneity due to cycle length changes. Because of this inconsistency, we investigated heart rate related changes of TpTe interval. METHODS During 24-h recordings (SEER MC, Marquette GE) in healthy young women (n=25, 26+/-7 years) and men (n=25, 27+/-8 years), a 10-s 12-lead ECG was obtained every 30 s. Recordings were repeated after 1 day, 1 week, and 1 month and results in each subject were pooled together and grouped for women and men. The QT and QT(peak) intervals were obtained automatically using QT Guard software (Marquette) and TpTe was computed as the difference between QT and QT(peak). In each subject TpTe values were averaged over 10-ms RR interval bands from 550 to 1150 ms. RESULTS In both sexes, TpTe interval showed marked rate dependence with prolongation at long RR intervals. TpTe intervals in men were significantly longer over the entire range of investigated RR intervals (P=1.4x10(-25)). However, whereas the difference between sexes was marked at short cycle length (RR interval bin 540-550 ms: women 87+/-5 vs. men 95+/-9, P=5.1x10(-4)) it decreased at long cycle lengths (RR interval bin 1140-1150 ms: women 99+/-5 vs. men 106+/-6, P=9.3x10(-4)). CONCLUSION There is a marked rate dependence of TpTe interval, which differs between women and men. The finding is consistent with the TpTe interval being an approximate surrogate of the intraventricular repolarisation gradient. The rate dependent increase in transmural repolarisation heterogeneity might be one of the reasons for the increased propensity of torsades de pointes in women.

Sample Size, Power Calculations, and Their Implications for the Cost of Thorough Studies of Drug Induced QT Interval Prolongation

Regulatory authorities require new drugs to be investigated using a so‐called “thorough QT/QTc study” to identify compounds with a potential of influencing cardiac repolarization in man. Presently drafted regulatory consensus requires these studies to be powered for the statistical detection of QTc interval changes as small as 5 ms. Since this translates into a noticeable drug development burden, strategies need to be identified allowing the size and thus the cost of thorough QT/QTc studies to be minimized. This study investigated the influence of QT and RR interval data quality and the precision of heart rate correction on the sample sizes of thorough QT/QTc studies. In 57 healthy subjects (26 women, age range 19–42 years), a total of 4,195 drug‐free digital electrocardiograms (ECG) were obtained (65–84 ECGs per subject). All ECG parameters were measured manually using the most accurate approach with reconciliation of measurement differences between different cardiologists and aligning the measurements of corresponding ECG patterns. From the data derived in this measurement process, seven different levels of QT/RR data quality were obtained, ranging from the simplest approach of measuring 3 beats in one ECG lead to the most exact approach. Each of these QT/RR data‐sets was processed with eight different heart rate corrections ranging from Bazett and Fridericia corrections to the individual QT/RR regression modelling with optimization of QT/RR curvature. For each combination of data quality and heart rate correction, standard deviation of individual mean QTc values and mean of individual standard deviations of QTc values were calculated and used to derive the size of thorough QT/QTc studies with an 80% power to detect 5 ms QTc changes at the significance level of 0.05. Irrespective of data quality and heart rate corrections, the necessary sample sizes of studies based on between‐subject comparisons (e.g., parallel studies) are very substantial requiring >140 subjects per group. However, the required study size may be substantially reduced in investigations based on within‐subject comparisons (e.g., crossover studies or studies of several parallel groups each crossing over an active treatment with placebo). While simple measurement approaches with ad‐hoc heart rate correction still lead to requirements of >150 subjects, the combination of best data quality with most accurate individualized heart rate correction decreases the variability of QTc measurements in each individual very substantially. In the data of this study, the average of standard deviations of QTc values calculated separately in each individual was only 5.2 ms. Such a variability in QTc data translates to only 18 subjects per study group (e.g., the size of a complete one‐group crossover study) to detect 5 ms QTc change with an 80% power. Cost calculations show that by involving the most stringent ECG handling and measurement, the cost of a thorough QT/QTc study may be reduced to approximately 25%‐30% of the cost imposed by the simple ECG reading (e.g., three complexes in one lead only).

Differences Between Study-Specific and Subject-Specific Heart Rate Corrections of the QT Interval in Investigations of Drug Induced QTc Prolongation

A computational study was designed to investigate the differences between the so‐called study‐specific and subject‐specific heart rate corrections of QT interval. In 53 healthy subjects (25 women, mean age 26.7 ± 8.7 years), serial 10‐second electrocardiograms (ECG) were obtained during daytime hours. In each subject, 200 ECGs were selected representative of the individual QT/RR relationship. Of the population of 53 subjects, 30,000 different subgroups of 16 subjects were considered and their data used to model drug induced QT interval prolongation by 0, 5, 10, and 20 ms combined with drug induced heart rate acceleration and deceleration. In each modeled study, QTc changes were assessed by: (1) Six study‐specific heart rate corrections designed by regression modeling of the baseline QT/RR data pooled from all subjects; (2) Six subject‐specific heart rate corrections designed by the same regression modeling of the baseline QT/RR data in each subject separately; (3) subject optimized correction that selected the best fitting regression model for each individual; and (4) by Bazett and Fridericia corrections. In each modeled study, the errors of the correction approaches were estimated and statistically summarized over all modeled studies. The subject‐specific corrections led to maximum errors in single milliseconds (error range of 2.4, 5.7, and 2.6 ms with linear, log/log linear, and exponential models, respectively) while the study‐specific corrections led to substantially greater errors (error range of 17.8, 19.4, and 16.9 ms with linear, log/log linear, and exponential models, respectively). Both Bazett and Fridericia corrections led not only to substantial errors (error range of 28.3 and 16.9 ms) but also to regular bias with systematically false negative and false positive conclusions dependent on modeled heart rate acceleration and deceleration. Thus, subjects‐specific corrections should be used in the intensive and definite studies aimed at providing the final answer on the ability of a drug to prolong the QT interval. (PACE 2004; 27[Pt. I]:791–800)

Utility of high and standard right precordial leads during ajmaline testing for the diagnosis of Brugada syndrome

Aims The authors sought to assess the value of the high right precordial leads (RPL) to detect the Type I Brugada ECG pattern in patients suspected of carrying Brugada syndrome (BrS). Methods Ajmaline testing using 15-lead ECGs was performed in 183 patients suspected of carrying BrS. Standard 12-lead ECG with V1–V3 recorded from the fourth intercostal space and an additional three leads placed over V1–V3 recorded from the third intercostal space were analysed. ECGs were analysed for a Type I ECG pattern in either the standard or high RPLs. Results Of the 183 tests, 31 (17%) were positive, and 152 were negative. In all positive studies, at least one high RPL became positive. In 13/31 (42%) cases, the Type I ECG pattern could be observed only in the high RPLs. Standard or high V3 were never positive before standard or high V1–V2. In seven patients, a Type I pattern was seen in one standard and one high RPL (vertical relationship). Conclusions The high RPLs are more sensitive than the conventional 12-lead ECG alone and initial observations suggest that they remain specific for BrS, while standard and high lead V3 offer redundant data. A vertical relationship of type 1 patterns may have a similar diagnostic value to that of a horizontal pair.

Circadian Rhythm of the Corrected QT Interval: Impact of Different Heart Rate Correction Models

SMETANA, P., et al.: Circadian Rhythm of the Corrected QT Interval: Impact of Different Heart Rate Correction Models. A reduced circadian pattern in the QTc interval has been repeatedly reported to provide prognostic information in cardiac patients. However, the results of studies in healthy subjects in which different heart rate correction formulas were used are inconsistent regarding the presence and extent of diurnal variations in QTc. This study compared the diurnal variations in QTc obtained with four frequently used heart rate correction models with those based on individually optimized heart rate correction. In 53 subjects (25 men aged 27 ± 7 years and 28 women aged 27 ± 9 years) 12‐lead digital ECGs were obtained every 30 seconds during 24 hours. The QT interval was measured automatically by six different algorithms provided by a commercially available device. The QT/RR relation was estimated by four common heart rate correction models and by an individually optimized correction model, QTc = QT/RRα. In each 24‐hour recording, RR, QT, and QTc intervals of separate ECG samples were averaged over 10‐minute intervals. Marked differences were found in the extent of the circadian pattern of QTc obtained with different formulas for heart rate correction. Under and overcorrection of the QT interval resulted in significant over‐ or underestimation of the circadian pattern. Thus, the extent of circadian variation in QTc depends highly on the heart rate correction formula used. To obtain proper insight regarding diurnal variation in QTc prolongation during pharmacologic therapy and/or to assess higher risk due to impaired autonomic regulation of ventricular repolarization, individualized heart rate correction is necessary. (PACE 2003; 26[Pt. II]:383–386)

The effect of mental stress on the non-dipolar components of the T wave: Modulation by hypnosis

Objective: Mental or emotional stress-induced ventricular arrhythmias and sudden cardiac death are thought to be mediated by the autonomic nervous system and ischemia. In the absence of ischemia, increased inhomogeneity of repolarization is thought to be important. We tested the hypotheses that in the absence of ischemia, mental stress may modulate repolarization by changing autonomic balance; and mental relaxation induced by hypnosis may offset the potentially adverse effects of stress on the cardiac electrophysiology. Methods: Twelve healthy volunteers (6 male, age 18–35, mean 25 years) experienced a series of different emotions intended to induce a wide range of autonomic response (42 test epochs) on two separate occasions, with and without hypnosis, with continuous electrocardiogram recording. Low- (LF) and HF (high-frequency) heart rate variability was measured and ventricular repolarization was assessed using the relative T-wave residua (proportion of nondipolar components of the T wave) calculated for the T-onset – T peak (TWR-peak T), T peak –T end (TWR-end T), and the whole T wave (TWR). Results: Emotionally induced changes in LF and LF/HF ratio correlated with changes in TWR, e.g., (R = 0.51, p < .001; R = 0.59, p < .0001; and R = 0.59, p < .0003, for LF/HF versus TWR, TWR-Peak T, and TWR-end T, respectively. Mental relaxation induced by hypnosis increased LF power (1,205 ms2) versus 624 ms2, p < .003 for hypnotized versus nonhypnotized state), HF power (1,619 ms2 versus 572 ms2), p < .0004), and reduced LF/HF ratio (1.0 versus 1.5, p = .052) and was associated with a marked reduction in the changes in repolarization in response to emotion, e.g., 10.7 × 10−6 versus 5.0 ×10−6, p < .03 for TWR. Conclusions: a) Mental stress in the absence of ischemia altered repolarization inhomogeneity via change in the autonomic balance. b) Mental relaxation induced by hypnosis greatly reduced the effect of mental stress on repolarization. c) These findings may have implications for arrhythmogenesis. EKG = electrocardiogram; LF = low frequency; HF = high frequency; LF/HF = low frequency/high frequency ratio; TWR = T-wave residua.

Increased QT dispersion in patients with Prinzmetal's variant angina and cardiac arrest

OBJECTIVES We sought to compare QT dispersion in patients presenting with Prinzmetals variant angina complicated by cardiac arrest or syncope and patients with uncomplicated variant angina. BACKGROUND Despite the usually benign course of treated Prinzmetals variant angina, a proportion of vasospastic angina patients develop ventricular arrhythmias and sudden death in association with coronary spasm. Increased QT dispersion has been suggested to increase susceptibility to ventricular arrhythmias in patients with coronary artery spasm. METHODS We studied 25 consecutive patients (mean age 58 years; 14 men) with classical Prinzmetals variant angina and documented coronary artery spasm. None of the patients had coronary artery stenoses < or =40%. Five patients had suffered a documented cardiac arrest, two had recurrent syncope and 18 had no arrhythmic events or syncopal episodes. In all patients QT dispersion (QT maximum-QT minimum in every ECG lead) was measured on the baseline 12-lead electrocardiogram at study entry using a digitising board. RESULTS Mean (+/-S.D.) QT dispersion of study patients was 62.3+/-19.5 ms. QT dispersion in patients with cardiac arrest and syncope (79.4+/-17.3 ms) was significantly higher compared to patients with no such events (56.3+/-16.9 ms), (95% CI 7.5-38.8, P=0.005). No significant clinical, biochemical or angiographic differences were found between patients with and those without cardiac arrest or syncope. CONCLUSION QT dispersion is increased in patients with Prinzmetals variant angina complicated by cardiac arrest and syncope compared to patients without such events. Increased QT dispersion may be both a substrate for sudden cardiac death and a marker of risk in patients with Prinzmetals variant angina.