Reproducibility of Minimum,Maximum and Median QT Intervals in the 12‐Lead Resting ECG

Background: Heterogeneity in the recovery of ventricular refractory periods is an important factor in the development of ventricular arrhythmia. The QT dispersion (QTD) is increasingly used to measure this heterogeneity but its clinical value is limited due to methodological problems. QTD is defined as the maximum minus the minimum QT intervals that are suspected to be the least reproducible of the QT measurements. Objective: To analyze the reproducibility of the minimum, maximum and median QT intervals. Material: One database consisted of 356 subjects: 169 with diabetes and 187 nondiabetic control persons. The other database consisted of 110 subjects with remote myocardial infarction: 55 with no history of arrhythmia, and 55 with a recent history of ventricular tachycardia or fibrillation. Methods: 12‐lead surface ECGs were recorded with an amplification of 10 millimeters per millivolt at a paper speed of 50 mm/s. QT was measured manually by the tangent‐method. The reproducibility was calculated from measurements of QT in successive beats. Results: The standard deviation (SD) of QTs reproducibility was 9 ms for the arrhythmia data and 8 ms for the diabetes data. The reproducibility of QT_max and QT_min were on average 30% and 15% worse than for QT_median. The SD of QT_max was significantly higher than for QT_median in both database (P < 0.001), whereas SD of QT_min was only significantly higher than for QT_median for the diabetes data (P < 0.001). Conclusions: The reproducibility of QT_min and in particular QTmax was significantly lower than for QT_median. This indicates that the QT dispersion is based on the least reproducible of the QT measurements. A.N.E. 2000;5(4):354–357     

Spatial Properties of QT and the T‐Wave Morphology

Objective: To describe the relation between the QT interval and the T‐wave morphology. Material and methods: Frank orthogonal leads X, Y, Z of one subject and resting 12‐lead ECG of 40 subjects. QT was measured by the tangent method. The QT values are organized according to the anatomic orientation of the leads: I, ‐aVR, II, aVF, III, ‐aVL, ‐I, aVR, ‐II, ‐aVF, ‐III, aVL. and: V₁, V₂, V₃, V₄, V₅, V₆, ‐V₁ ‐V₂, ‐V₃, ‐V₄, ‐V₅, ‐V₆. The T‐wave amplitudes and QT were categorized according to QT into four groups with increasing mean QT. Results: Kruskal‐Wallis nonparametric test showed that the shortest and longest QT values are measured on the T wave with the smallest amplitudes (P < 0.001). Inspection of plots of QT and T waves reveals that the shortest and longest QT values are usually measured in leads with a small difference in orientation (neighbor leads). The mechanism behind these characteristics is mainly that the shortest and longest QT values are measured on T waves that are close to a lead orientation, whereas the T waves are flat or biphasic. We also observed an almost significant (P = 0.057) decrease in the T‐wave amplitude with increasing dispersion. Conclusion: The relation between T‐wave morphology and QT in the same cardiac plane is highly organized. The shortest and longest QT values are measured on the T wave with the smallest amplitudes (P < 0.001).     

运动试验QT离散度变化与心肌缺血或T波改变相关性的研究

目的 :探讨运动试验QT离散度 (QTd)变化与心肌缺血和T波变化的相关性及评价QTd的临床应用价值。方法 :2 4 2例经冠脉造影证实冠心病而静息心电图正常 ,平板运动试验阳性 (冠心病组 )和 16 8例静息心电图有T波低平、双向、倒置或有u波 ,平板运动试验心电图正常 ,并经冠脉造影及其他检查排除器质性心脏病 (非器质性心脏病组 )。观察两组平板运动试验QTd的变化与心肌缺血和T波变化的相关性。结果 :设QTd >5 0ms为异常 ,冠心病组运动前QTd异常率为18% ,运动后为 80 % ;非器质性心脏病组运动前QTd异常率为 84 % ,运动后为 12 %。QTd的变化与T波改变相关 ,r=0 .86 ,P <0 .0 1;与冠心病运动后单纯缺血性ST段下移无相关性。结论 :运动试验QTd变化与心肌缺血无相关性 ,QTd异常不能判断心肌复极不均一性进而预测恶性心律失常或心脏猝死 ,而只是反映T波非特异性异常的一个粗浅的量化指标     

T环形态与QT离散度的关系研究

目的　探讨心向量图的T环形态与体表心电图出现QT离散度 (QTd)的关系。方法　使用中卫瑞德SCA Ⅱ型立体心电图仪 ,对确诊的陈旧心肌梗死患者和正常对照健康人各 10 0例进行 2 4条通道同步、实时、连续采样描记 12导联心电图、普通心向量图、9导联时间心向量图及连续心向量图检测 ,分析病例和对照组最大QT间期、最小QT间期在体表心电图各导联的分布特点以及在心向量图上T环的形态差异同QTd的关系。结果　 (1)病例和对照组从体表心电图测得的最大QT间期、最小QT间期几乎均集中在相同的导联 ;(2 )从心电向量额面 (F)、横面 (H)的T环形态来看 :病例组T环以圆小型比例大 (43% ) ,狭长型比例小 (16 % ) ,而对照组以狭长型为主 (6 8% ) ,圆小型最少 (4% )。综合分析发现狭长型T环所对应的体表QTd、校正QT离散度 (QTcd)最小 [(0 0 2 5± 0 0 0 9)s ,(0 0 2 5±0 0 0 9)s],圆小型T环所对应的体表QTd、QTcd最大 [(0 0 4 1± 0 0 17)s,(0 0 4 2± 0 0 18)s,P <0 0 1]。结论　QTd值的大小与额面和横面向量上T环的形态有关。最大QT间期、最小QT间期所集中的导联不会因梗死部位的出现而发生改变     

QT的空间特征与T波的形态的相关研究

目的 探讨QT间期的空间特征及其与T波形态之间的关系。方法 描记40名正常人静息时间的同步12导联心电图，计算QT间期及T波的幅度。并根据导联的解剖方向重新将肢体导联排列成Ⅰ,-aVR,Ⅱ,aVF,Ⅲ,-aVL,-Ⅰ,aVR,-Ⅱ,-aVF,-Ⅲ,aVL，将胸前导联排列成V1，V2，V3，V4，V5，V6，－V1，－V2，－V3,－V4，－V5，－V6。以分析QT间期的空间特征及其与T波形态之间的关系。结果 均在较低幅度的T波上测得最短和最长的QT值，并通常在方向有微小差异的导联（即相邻导联）上测得，而且此导联的T波通常是扁平或是双向的。结论 T波的形态和QT之间有着密切的关系。     

Reproducibility and automatic measurement of QT dispersion

This study investigated interobserver (two observers) and intrasubject(two measurements) reproducibility of QT dispersion from abnormalelectrocardiograms in patients with previous myocardial infarction,and compared a user-interactive with an automatic measurementsystem. Standard 12-lead electrocardiograms, recorded at 25mm. s^–1, were randomly chosen from 70 patients followingmyocardial infarction. These were scanned into a personal computer,and specially designed software skeletonized and joined eachimage. The images were then available for user-interactive (mouseand computer screen), or automatic measurements using a speciallydesigned algorithm. For all methods reproducibility of the RRinterval was excellent (mean absolute errors 3–4 ms, relativeerrors 0·3–0·5%). Reproducibility of themean QT interval was good; intrasubject error was 6 ms (relativeerror 1·4%), interobserver error was 7 ms (1·8%),and observers' vs automatic measurement errors were 10 and 11ms (2·5, 2·8%). However QTc dispersion measurementshad large errors for all methods; intrasubject error was 12ms (17·3%), interobserver error was 15 ms (22·1%),and observers' vs automatic measurement were errors 30 and 28ms (35·4, 31·9%). QT dispersion measurements relyon the most difficult to measure QT intervals, resulting ina problem of reproducibility. Any automatic system must notonly recognize common T wave morphologies, but also these moredifficult T waves, if it is to be useful for measuring QT dispersion.The poor reproducibility of QT dispersion limits its role asa useful clinical tool, particularly as a predictor of events.     

Interobserver Reproducibility of QT Interval Measurement and QT Dispersion in Patients After Acute Myocardial Infarction

Background: The study evaluated interobserver differences in the classification of the T-U wave repolarization pattern, and their influence on the numerical values of manual measurements of QT interval duration and dispersion in standard predischarge 12-lead ECGs recorded in survivors after acute myocardial infarction. Methods: Thirty ECGs recorded at 25 mm/s were measured by six independent observers. The observers used an adopted scheme to classify the repolarization pattern into 1 of 7 categories, based on the appearance of the T wave, and/or the presence of the U wave, and the various extent of fusion between these. In each lead with measurable QRST(U) pattern, the RR, QJ, QT-end, QT-nadir (i.e., interval between Q onset and the nadir or transition between T and U wave) and QU interval were measured, when applicable. Based on these measurements, the mean RR interval, the maximum, minimum, and mean QJ interval, QT-end and/or QT-nadir interval, and QU interval, the difference between the maximum and minimum QT interval (QT dispersion [QTD]), and the coefficient of variation of QT intervals was derived for each recording. The agreement of an individual observer with other observers in the selection of a given repolarization pattern were investigated by an agreement index, and the general reproducibility of repolarization pattern classification was evaluated by the reproducibility index. The interobserver agreement of numerical measurements was assessed by relative errors. To assess the general interobserver reproducibility of a given numerical measurement, the coefficient of variance of the values provided by all observers was computed for each ECG. Statistical comparison of these coefficients was performed using a standard sign test. Results: The results demonstrated the existence of remarkable differences in the selection of classification patterns of repolarization among the observers. More importantly, these differences were mainly related to the presence of more complex patterns of repolarization and contributed to poor interobserver reproducibility of QTD parameters in all 12 leads and in the precordial leads (relative error of 31%–35% and 34%–43%, respectively) as compared with the interobserver reproducibility of both QT and QU interval duration measurements (relative error of 3%–6%, P < 0.01). This observation was not explained by differences in the numerical order between QT interval duration and QTD, as the reproducibility of the QJ interval (i.e., interval of the same numerical order as QTD was significantly better (relative error of 7.5%–13%, P < 0.01) than that of QTD. Conclusions: Poor interobserver reproducibility of QT dispersion related to the presence of complex repolarization patterns may explain, to some extent, a spectrum of QT dispersion values reported in different clinical studies and may limit the clinical utility in this parameter.     

T‐Wave Morphology in Short QT Syndrome

Background: Short QT syndrome (SQTS) is an inherited disorder characterized by a short QT interval and vulnerability to ventricular tachyarrhythmias. The diagnostic criteria for this syndrome are not well defined, since there is uncertainty about the lowest normal limits for the corrected QT (QTc) interval. Objective: The aim of this study was to determine whether T‐wave morphology parameters are abnormal in short QT subjects and whether those parameters can help in the diagnosis of SQTS. Methods and Results: We describe three families (10 patients) with short QT intervals (QTc 310 ± 32 ms). Seven subjects had suffered serious arrhythmic events and three were asymptomatic. T‐wave morphology was assessed using the principal component analysis (PCA). QTc was significantly shorter and T‐wave amplitude in lead V₂ higher in the short QT subjects compared to healthy controls (n = 149), (P < 0.001 for both). The total cosine of the angle between the main vectors of the QRS and T‐wave loops (TCRT) was markedly abnormal among the symptomatic patients with short QT syndrome (n = 7) (TCRT –0.14 ± 0.55 vs 0.36 ± 0.51, P = 0.019). None of the three asymptomatic patients with short QT but without a history of arrhythmic events had an abnormally low TCRT. Conclusion: Our observations suggest that patients with a short QT interval and a history of arrhythmic events have abnormal T‐wave loop parameters. These electrocardiogram (ECG) features may help in the diagnosis of SQTS in addition to the measurement of the duration of QT interval from the 12‐lead ECG.     

Bias of QT Dispersion

Background: Prolonged QT dispersion (QID) is associated with an increased risk of arrhythmic death but its accuracy varies substantially between otherwise similar studies. This study describes a new type of bias that can explain some of these differences. Material: One dataset (DiaSet) consisted of 356 subjects: 169 with diabetes, 187 nondiabetic control persons. Another dataset (ArrSet) consisted of 110 subjects with remote myocardial infarction: 55 with no history of arrhythmia and 55 with a recent history of ventricular tachycardia or fibrillation. Methods: 12‐lead surface ECGs were recorded with an amplification of 10 mm/mV at a paper speed of 50 mm/s. The QT interval was measured manually by the tangent‐method. The bias depends on the magnitude of the measurement errors and the measurable part of the bias increases with the number of the repeated measurements of QT. Results: The measurable bias was significant for both datasets and decreased for increasing QTD in the DiaSet (P < 0.001) and in the ArrSet (P = 0.11). The bias was 2.5 ms and 1.9 ms at QTD = 38 ms and 68 ms, respectively, in the ArrSet, and 7.5 ms and 2.8 ms at QTD = 19 ms and 55 ms, respectively, in the DiaSet. Conclusions: This study shows that random measurement errors of QT introduces a type of bias in QTD that decreases as the dispersion increases, thus reducing the separation between patients with low versus high dispersion. The bias can also explain some of the differences in the mean QTD between studies of healthy populations. Averaging QT over three successive beats reduces the bias efficiently. A.N.E. 2001;6(1):38–42     

Identify drug-induced T wave morphology changes by a cell-to-electrocardiogram model and validation with clinical trial data

Background

Increase of repolarization heterogeneity has been identified as a major factor for drug-induced arrhythmia event like torsade de pointes. In recent years, there have been quite a few efforts for studying T wave morphology changes, hoping to identify more sensitive proarrhythmia electrocardiogram (ECG) biomarkers than QT interval. However, the associations among ECG morphologies and the repolarization heterogeneities are still not clear.

Method

A cell-to-ECG model has been built by our group to study relationship between multiple factors of ion channels on the heart tissue and ECG morphology changes measured on the torso. More specifically, we varied both transmural (from Epi to Endo myocardium layers) and apex-to-base heterogeneities by blocking rapid delayed rectifier potassium current (Ikr), slow delayed rectifier potassium current (Iks), and late sodium current (InaL) with different extents on Epi, M, and Endo myocardium. On ECG measurement part, the study was focused on some new morphology-related features including T-peak to T-end (TpTe) interval, T wave flatness, T wave symmetric, and T wave notch. Two types of transmural dispersion of repolarization (TDR) were created: global and localized heterogeneities. Vector magnitude and principal component-based composite leads were formed from multiple chest leads for robustness against large variation of individual lead due to placement and noise issues. Cross-correlation methods were used to determine the relationship of the new ECG morphology features with the heterogeneities. All the ECG morphology measurements were first analyzed with the cell-to-ECG model and then validated with previously acquired clinical trial ECG data (d-sotalol).

Results

The results based on our cell-to-ECG model showed that the new TpTe interval of the composite signal based on V2, V3, and V4 leads has the correlation coefficients of 0.99 and 0.98 with the simulated global and localized TDR, respectively, highest among other tested ECG parameters. The combined T wave morphology score has the correlation coefficients of 0.98 and 0.92 with the simulated global and localized TDR, respectively. The validation results of d-sotalol show that new TpTe measurement has a correlation coefficient of 0.90 with plasma concentration, and the parameter's correlation with heart rate is 0.02.

Conclusions

The study provided preliminary results showing the usefulness of the cell-to-ECG model for studying relationship between multiple ion-channel factors with ECG morphology changes. The global and localized TDR generate very different T wave morphologies. The newly identified T wave morphology parameters are highly correlated with transmural dispersion and are heart rate independent.     

QT dispersion does not represent electrocardiographic interlead heterogeneity of ventricular repolarization

INTRODUCTION: QT dispersion (QTd, range of QT intervals in 12 ECG leads) is thought to reflect spatial heterogeneity of ventricular refractoriness. However, QTd may be largely due to projections of the repolarization dipole rather than "nondipolar" signals. METHODS AND RESULTS: Seventy-eight normal subjects (47+/-16 years, 23 women), 68 hypertrophic cardiomyopathy patients (HCM; 38+/-15 years, 21 women), 72 dilated cardiomyopathy patients (DCM; 48+/-15 years, 29 women), and 81 survivors of acute myocardial infarction (AMI; 63+/-12 years, 20 women) had digital 12-lead resting supine ECGs recorded (10 ECGs recorded in each subject and results averaged). In each ECG lead, QT interval was measured under operator review by QT Guard (GE Marquette) to obtain QTd. QTd was expressed as the range, standard deviation, and highest-to-lowest quartile difference of QT interval in all measurable leads. Singular value decomposition transferred ECGs into a minimum dimensional time orthogonal space. The first three components represented the ECG dipole; other components represented nondipolar signals. The power of the T wave nondipolar within the total components was computed to measure spatial repolarization heterogeneity (relative T wave residuum, TWR). QTd was 33.6+/-18.3, 47.0+/-19.3, 34.8+/-21.2, and 57.5+/-25.3 msec in normals, HCM, DCM, and AMI, respectively (normals vs DCM: NS, other P < 0.009). TWR was 0.029%+/-0.031%, 0.067%+/-0.067%, 0.112%+/-0.154%, and 0.186%+/-0.308% in normals, HCM, DCM, and AMI (HCM vs DCM: NS, other P < 0.006). The correlations between QTd and TWR were r = -0.0446, 0.2805, -0.1531, and 0.0771 (P = 0.03 for HCM, other NS) in normals, HCM, DCM, and AMI, respectively. CONCLUSION: Spatial heterogeneity of ventricular repolarization exists and is measurable in 12-lead resting ECGs. It differs between different clinical groups, but the so-called QT dispersion is unrelated to it.     

Sildenafil Citrate Does Not Affect QT Intervals and QT Dispersion: An Important Observation for Drug Safety

Background: Sildenafil is an effective and widely used therapeutic agent for erectile dysfunction. Deaths have been reported due to sildenafil use and most of them are attributed to concurrent use of nitrates. However, the effects of sildenafil on QT intervals, QT dispersion, and the possible risk of ventricular arrhythmia have not been studied before. Our aim in this study was to evaluate the effect of sildenafil citrate on QT intervals and QT dispersion. Methods: Thirty‐six patients with erectile dysfunction were included in this study. Twenty‐one patients had coronary artery disease whereas 12 of them also had accompanying diabetes mellitus. Standard 12‐lead electrocardiograms (ECG) were recorded three times: before, and at the first and fourth hours of 50 mg sildenafil citrate ingestion. All QT parameters were corrected for heart rate. Results: Mean age of the patients was 54 ± 12 years. The mean heart rate did not differ significantly between the three ECG examinations. The corrected and uncorrected maximum and minimum QT intervals were not significantly different between the three ECG examinations. The QT dispersion and corrected QT dispersion before and 1 hour and 4 hours after sildenafil ingestion were 31 ± 9 ms, 36 ± 10 ms; 32 ± 11 ms, 37 ± 14 ms; 27 ± 8 ms, 32 ± 9 ms, respectively (P > 0.05) . Conclusions: Sildenafil does not prolong QT intervals or increase QT dispersion in patients with erectile dysfunction. Our results suggest that the risk of ventricular arrhythmia does not increase with ingestion of 50 mg sildenafil.     

Dispersion of Repolarization: Time to Move Beyond QT Dispersion

Background: Over the last few years, the concept of dispersion of repolarization, evaluated as interlead variability of QT interval duration in surface ECG, emerged as a possible tool to identify patients at high‐risk for cardiac arrhythmias. Despite substantial progress in understanding of the electrophysiological basis for dispersion of repolarization, the question remains whether interlead differences in ECG‐ recorded T‐wave duration and morphology (QT dispersion) indicate heterogeneity in ventricular recovery time and pattern. Methods and Results: Several studies investigated the prognostic significance of QT dispersion for predicting all‐cause mortality, sudden cardiac, and arrhythmic deaths. Some of those studies indicated significant and independent predictive value of QT dispersion whereas others negated such an association. Despite these controversial results, there is concern that substantial overlap in QT dispersion values between patients with and without cardiac events limits or even precludes clinical usefulness of QT dispersion for predicting future cardiac events. The methodological and conceptual limitations of QT dispersion measurements further discourage the bedside use of this noninvasive ECG parameter. Ionic channel phenomena determine the voltage and time components of the T‐wave, the T‐loop, and the QT interval duration. Since the ST‐T area is more representative of recovery times than QT interval duration, future efforts should be focused on developing and testing new automatically quantified parameters describing abnormalities of the T‐wave configuration and/or T‐loop morphology. Electrophysiologic meaning and prognostic significance of these ECG parameters remain to be studied. Conclusion: In light of conceptual and methodological limitations of QT dispersion analysis, bedside use of this method should be discouraged and the time has come to move beyond QT dispersion and focus on evaluating clinical usefulness of repolarization morphology in risk‐stratification. studies. A.N.E. 2000;5(4):373‐381     

T-wave patterns associated with the hereditary long QT syndrome

Mutations involving 6 different ion-channel genes have been identified in subjects with the hereditaryLong QT Syndrome. These gene mutations result in structural and functional changes in ion-channel proteins withresultant alterations in potassium and sodium repolarization currents that affect the morphologic features ofelectrocardiographic repolarization. This review highlights the genotype-phenotype associations related toventricular repolarization that have been reported in the LQTS literature, with particular focus on ECG T-wavepatterns in LQT1, LQT2, and LQT3 genotypes.     

The diagnostic role of T wave morphology biomarkers in congenital and acquired long QT syndrome: A systematic review

Introduction

QTc prolongation is key in diagnosing long QT syndrome (LQTS), however 25%–50% with congenital LQTS (cLQTS) demonstrate a normal resting QTc. T wave morphology (TWM) can distinguish cLQTS subtypes but its role in acquired LQTS (aLQTS) is unclear.

Methods

Electronic databases were searched using the terms “LQTS,” “long QT syndrome,” “QTc prolongation,” “prolonged QT,” and “T wave,” “T wave morphology,” “T wave pattern,” “T wave biomarkers.” Whole text articles assessing TWM, independent of QTc, were included.

Results

Seventeen studies met criteria. TWM measurements included T-wave amplitude, duration, magnitude, Tpeak-Tend, QTpeak, left and right slope, center of gravity (COG), sigmoidal and polynomial classifiers, repolarizing integral, morphology combination score (MCS) and principal component analysis (PCA); and vectorcardiographic biomarkers. cLQTS were distinguished from controls by sigmoidal and polynomial classifiers, MCS, QTpeak, Tpeak-Tend, left slope; and COG x axis. MCS detected aLQTS more significantly than QTc. Flatness, asymmetry and notching, J-Tpeak; and Tpeak-Tend correlated with QTc in aLQTS. Multichannel block in aLQTS was identified by early repolarization (ERD_30%) and late repolarization (LRD_30%), with ERD reflecting hERG-specific blockade. Cardiac events were predicted in cLQTS by T wave flatness, notching, and inversion in leads II and V₅, left slope in lead V₆; and COG last 25% in lead I. T wave right slope in lead I and T-roundness achieved this in aLQTS.

Conclusion

Numerous TWM biomarkers which supplement QTc assessment were identified. Their diagnostic capabilities include differentiation of genotypes, identification of concealed LQTS, differentiating aLQTS from cLQTS; and determining multichannel versus hERG channel blockade.