The Measurement of the QT Interval

The evaluation of every electrocardiogram should also include an effort to interpret the QT interval to assess the risk of malignant arrhythmias and sudden death associated with an aberrant QT interval. The QT interval is measured from the beginning of the QRS complex to the end of the T-wave, and should be corrected for heart rate to enable comparison with reference values. However, the correct determination of the QT interval, and its value, appears to be a daunting task. Although computerized analysis and interpretation of the QT interval are widely available, these might well over- or underestimate the QT interval and may thus either result in unnecessary treatment or preclude appropriate measures to be taken. This is particularly evident with difficult T-wave morphologies and technically suboptimal ECGs. Similarly, also accurate manual assessment of the QT interval appears to be difficult for many physicians worldwide. In this review we delineate the history of the measurement of the QT interval, its underlying pathophysiological mechanisms and the current standards of the measurement of the QT interval, we provide a glimpse into the future and we discuss several issues troubling accurate measurement of the QT interval. These issues include the lead choice, U-waves, determination of the end of the T-wave, different heart rate correction formulas, arrhythmias and the definition of normal and aberrant QT intervals. Furthermore, we provide recommendations that may serve as guidance to address these complexities and which support accurate assessment of the QT interval and its interpretation.     

QT间期及其离散度测定的方法学研究和正常值

报告１００例健康成人同步体表１２导联心电图的ＱＴ间期和ＱＴ间期离散度（ＱＴｄ）：（１）各参数测量结果（±ｓ）：ＱＴｄ、ＱＴｃｄ（矫正ＱＴｄ）、ＪＴｄ（ＪＴ离散度）、ＱＴｐｄ（ＱＴ顶点离散度）、ＪＴｐｄ（ＪＴｐ离散度）、Ｔｐ－ＴＥｄ（Ｔ波顶点至Ｔ波终点间期离散度）、ＱＲＳｄ（ＱＲＳ间期离散度）和Ｏ－Ｑｄ（ＱＲＳ起始时间离散度）分别为２５．６±１１．２，２６．８±１２．６，２６．１±１２．５，２４．６±１４．７，３２．０±１５．６，３１．０±１４．６，２０．６±８．８和１２．５±７．３ｍｓ，其范围均在５～５０ｍｓ以内，与国际上研究结果一致。笔者认为ＱＴｄ的正常值可暂定为＜５０ｍｓ；（２）体表１２导联心电图同步记录方法，比常规非同步记录更能反映ＱＴｄ的实际情况，并且可测量同步１２导联ＱＲＳ起始部时间（Ｑ－ＱＴ）及其离散度（Ｑ－ＱＴｄ）；（３）本文资料由国内和国外三组不同人员测量结果相同，表明ＱＴ、ＱＴｄ测定的可重复性好；（４）性别差异，ＱＴ间期女性比男性长，而ＱＲＳ间期男性比女性长，其机理尚待进一步研究探讨。     

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.     

Effects of Orthotopic Liver Transplantation on the Corrected QT Interval in Patients with End-Stage Liver Disease

Autonomic dysfunction is a recognized complication of end-stage liver disease (ESLD) associated with a poor prognosis. The corrected QT interval (QTc) on electrocardiogram is a marker of autonomic function. A few small studies have suggested that QTc may normalize with the return of liver function after orthotopic liver transplantation. We sought to determine how transplantation affects the QTc in patients with ESLD. The QTc from the pretransplantation evaluation of 46 patients with ESLD was compared with the QTc at 4-month posttransplantation follow-up. Other factors that can influence autonomic function also were evaluated. Most patients with ESLD (54%) showed a prolonged QTc (440 msec) at the pretransplantation evaluation (451± 45 msec) that improved to within the normal range at posttransplantation follow-up (418± 18 msec; P < 0.001). There was no relationship between QTc prolongation and Child–Turcotte–Pugh score, Model for End-Stage Liver Disease score, diabetes mellitus, age, or etiology of liver disease. Most patients with ESLD and a prolonged QTc will have a significant improvement in QTc after transplantation; however, 6.5% of patients in our study had a worsening of QTc after transplantation.     

Corrected QT Interval in Severe Aortic Stenosis: Clinical and Hemodynamic Correlates and Prognostic Impact

BackgroundThe role of the electrocardiogram for risk stratification in patients with severe aortic stenosis is not established. We assessed the hemodynamic correlates and the prognostic value of the corrected QT interval (QTc) in patients with severe aortic stenosis undergoing aortic valve replacement.MethodsThe QT interval was measured in a 12-lead electrocardiogram in 485 patients (age 74 ± 10 years, 57% male) with severe aortic stenosis (indexed aortic valve area 0.41 ± 0.13 cm²/m², left ventricular ejection fraction 58 ± 12%) the day prior to cardiac catheterization. Prolonged QTc was defined as QTc >450 ms in men and QTc >470 ms in women. The outcome parameter was all-cause mortality.ResultsPatients with prolonged QTc (n = 100; 77 men, 23 women) had similar indexed aortic valve area but larger left ventricular and left atrial size, lower left ventricular ejection fraction, more severe mitral regurgitation, lower cardiac index, and higher mean pulmonary artery pressure, mean pulmonary artery wedge pressure, and pulmonary vascular resistance, as compared with patients with normal QTc (n = 385). After a median follow-up of 3.7 years (interquartile range, 2.6-5.2) after surgical (n = 349) or transcatheter (n = 136) aortic valve replacement, patients with prolonged QTc had higher mortality than those with normal QTc (hazard ratio 2.81 [95% confidence interval, 1.51-5.20]; P < .001). Prolonged QTc was an independent predictor of death along with more severe mitral regurgitation and higher pulmonary vascular resistance.ConclusionsIn patients with severe aortic stenosis, prolonged QTc is a marker of an advanced disease stage associated with an adverse hemodynamic profile and increased long-term mortality after aortic valve replacement.     

Association of Corrected QT and QT Dispersion with Echocardiographic and Laboratory Findings in Uremic Patients under Chronic Hemodialysis

Introduction:

Cardiovascular disease is the most common cause of mortality in dialysis patients. Chronic renal failure and hemodialysis (HD) patients may have longer corrected QT (QTc) interval compared with the normal population. Long QTc interval may be a predictor of ventricular arrhythmia and cardiovascular mortality in these patients and hence the aim of this study was the evaluation of the relationship between QTc interval and some echocardiographic findings and laboratory exam results in HD patients.

Materials and Methods:

In a cross-sectional study, 60 HD patients with age >18 years and the dialysis duration >3 months were enrolled. Blood samples were taken, and electrocardiography and echocardiography were done before the dialysis session in the patients.

Results:

Mean age of the patients was 56.15 ± 14.6 years. QTc interval of the patients was 0.441 ± 0.056 s and QT dispersion (QTd) was 64.17 ± 25.93 ms. There was no statistically significant relationship between QTc interval and QTd with duration of dialysis, body mass index, age, and gender (P > 0.05). There was also no significant relationship between QTc interval and QTd with mitral regurgitation, tricuspid regurgitation and aortic insufficiency (P > 0.05). In addition, QTc interval and QTd of the patients had not any correlation with serum parathormon and serum Ca, K, HCO₃ (P > 0.05).

Conclusion:

Based on our results, in HD patients, QTc interval and QTd were not correlated with echocardiographic findings or laboratory exam results. Therefore, it can be concluded that QTc interval prolongation probably has not any correlation with cardiac mortality of the HD patients.     

QT Interval Length and Diabetic Autonomic Neuropathy

QT interval length was measured in ECG recordings from three groups of age-matched male subjects: 36 normal subjects, 41 diabetic patients without (DAN-ve), and 34 with (DAN+ve) autonomic neuropathy. ECG samples were selected from previously recorded 24-h ECGs on the basis of a clearly defined T wave and a steady RR interval over 2 min of around 750 ms (80 beats min^?1). There were no significant differences in RR interval between the groups. The two diabetic groups had slightly longer QT measurements (normal 365 ± 14 (±SD) ms, DAN-ve 373 ± 18 ms, DAN+ve 375 ± 23 ms, p = 0.05), and corrected QT (QTc) values (normal 423 ± 15 ms, DAN-ve 430 ± 20 ms, DAN+ve 435 ± 24 ms, p = 0.05). Ten diabetic patients fell above our defined upper limit of normal for QTc (>mean + 2SD). There was a significant correlation in the DAN-ve group between the QT indices and 24-h RR counts (QT r = ?0.38, p < 0.01; QTc r = ?0.40, p < 0.01). We conclude that there are some small alterations in QT interval length in the steady state in diabetic autonomic neuropathy. The changes appear to be due to autonomic impairment, rather than diabetes per se.     

Highly Automated QT Measurement Techniques in 7 Thorough QT Studies Implemented under ICH E14 Guidelines

Thorough QT (TQT) studies are designed to evaluate potential effect of a novel drug on the ventricular repolarization process of the heart using QTc prolongation as a surrogate marker for torsades de pointes. The current process to measure the QT intervals from the thousands of electrocardiograms is lengthy and expensive. In this study, we propose a validation of a highly automatic‐QT interval measurement (HA‐QT) method. We applied a HA‐QT method to the data from 7 TQT studies. We investigated both the placebo and baseline‐adjusted QTc interval prolongation induced by moxifloxacin (positive control drug) at the time of expected peak concentration. The comparative analysis evaluated the time course of moxifloxacin‐induced QTc prolongation in one study as well. The absolute HA‐QT data were longer than the FDA‐approved QTc data. This trend was not different between ECGs from the moxifloxacin and placebo arms: 9.6 ± 24 ms on drug and 9.8 ± 25 ms on placebo. The difference between methods vanished when comparing the placebo‐baseline‐adjusted QTc prolongation (1.4 ± 2.8 ms, P = 0.4). The differences in precision between the HA‐QT and the FDA‐approved measurements were not statistically different from zero: 0.1 ± 0.1 ms (P = 0.7). Also, the time course of the moxifloxacin‐induced QTc prolongation adjusted for placebo was not statistically different between measurements methods. Ann Noninvasive Electrocardiol 2011;16(1):13–24     

QT间期与风湿结缔组织疾病

风湿病中QT相关指标的延长是相当常见的,多与疾病本身的免疫和炎症相关,常常预示着复杂的室性心律失常和心源性猝死。因此,对于这些病人,行12导联心电图、24小时心电监测及心脏彩超检查是很有必要的。     

QT Measurement: A Comparison of Three Simple Methods

Background: QT interval and QT dispersion are useful noninvasive measurements in clinical cardiology and can be measured by several methods. The comparative variability of these methods, however, is not well defined. Methods: We evaluated the intra- and interobserver variability of three simple methods of QT measurement: (1) ruler method: use of a 0.5-mm scale precision ruler to measure QT with end of T wave determined by extrapolating its slope to baseline; (2) caliper method: use of a standard electrocardiogram (ECG) caliper and the standard ECG paper scale with QT determined by visual inspection; (3) computer method: use of a digitized computer software program with QT determined by cursor set manually by the user. QT intervals from 11 patients (total 44 ECG leads) in sinus rhythm without conduction defect were measured by five blinded, trained observers at two time points (a week apart) in a crossover manner. Results: The mean difference in intraobserver measurements were 6 ± 2, 12 ± 12, and 27 ± 2 ms by the ruler, caliper, and computer methods, respectively (P > 0.01, ruler vs caliper or computer). The mean differences in interobserver measurements were 13 ± 3, 16 ± 4, and 29 ± 3 ms for the same methods, respectively (P > 0.01, ruler vs caliper, computer). Enlargement of the ECG to 200% did not reduce the measurement variability. Conclusion: The ruler method as described yielded the lowest variability in QT measurement.     

Measurement error as a source of QT dispersion: a computerised analysis

Objective—To establish a general method to estimate the measuring error in QT dispersion (QTD) determination, and to assess this error using a computer program for automated measurement of QTD.
Subjects—Measurements were done on 1220 standard simultaneous 12 lead electrocardiograms.
Design—The computer program was validated against two observers on a random subset of 100 electrocardiograms. Simple laws of physics require that at least five of the six extremity leads have the same QT duration. This allows the direct assessment of the error in measuring QTD derived from five extremity leads (QTD₅). It also enables ST-T amplitude dependent distributions of measurement error in determining QT duration to be established. These QT error distributions were then used to estimate the error in measuring QTD from all 12 leads (QTD₁₂).
Main outcome measures—Mean and standard deviation of error in measuring QT duration, QTD₅, and QTD₁₂.
Results—Performance of the program was comparable to that of observers. Errors in measuring QT duration (measured QT minus reference QT) fell from a mean (SD) of 6.9 (17.1) ms for ST-T amplitudes < 50 µV to −1.4 (6.3) ms for amplitudes > 350 µV. Measurement errors of QTD₅ and QTD₁₂ were 20.4 (11.5) ms and 29.4 (14.9) ms.
Conclusions—The fact that no QTD can exist between five of the six extremity leads provides a means of estimating QTD measurement error. Measuring error of QT duration is dependent on ST-T amplitude. QTD measurement error is large compared with typical QTD values reported.

Keywords: automated ECG analysis;  QT measurement;  QT dispersion;  measurement error     

Comparing Methods of Measurement for Detecting Drug‐Induced Changes in the QT Interval: Implications for Thoroughly Conducted ECG Studies

Background: The aim of this study was to compare the reproducibility and sensitivity of four commonly used methods for QT interval assessment when applied to ECG data obtained after infusion of ibutilide. Methods: Four methods were compared: (1) 12‐lead simultaneous ECG (12‐SIM), (2) lead II ECG (LEAD II), both measured on a digitizing board, (3) 3‐LEAD ECG using a manual tangential method, and (4) a computer‐based, proprietary algorithm, 12SL? ECG Analysis software (AUT). QT intervals were measured in 10 healthy volunteers at multiple time points during 24 hours at baseline and after single intravenous doses of ibutilide 0.25 and 0.5 mg. Changes in QT interval from baseline were calculated and compared across ECG methods, using Bland–Altman plots. Variability was studied using a mixed linear model. Results: Baseline QT values differed between methods (range 376–395 ms), mainly based on the number of leads incorporated into the measurement, with LEAD II and 3‐LEAD providing the shortest intervals. The 3‐LEAD generated the largest QT change from baseline, whereas LEAD II and 12‐SIM generated essentially identical result within narrow limits of agreement (0.4 ms mean difference, 95% confidence interval ± 20.5 ms). Variability with AUT (standard deviation 15.8 ms for within‐subject values) was clearly larger than with 3‐LEAD, LEAD II, and 12‐SIM (9.6, 10.0, and 11.3 ms). Conclusion: This study demonstrated significant differences among four commonly used methods for QT interval measurement after pharmacological prolongation of cardiac repolarization. Observed large differences in variability of measurements will have a substantial impact on the sample size required to detect QT prolongation in the range that is currently advised in regulatory guidance.     

Preferred QT Correction Formula for the Assessment of Drug‐Induced QT Interval Prolongation

Drug‐Induced QTc Interval Assessment. Introduction: There is debate on the optimal QT correction method to determine the degree of the drug‐induced QT interval prolongation in relation to heart rate (ΔQTc). Methods: Forty‐one patients (71 ± 10 years) without significant heart disease who had baseline normal QT interval with narrow QRS complexes and had been implanted with dual‐chamber pacemakers were subsequently started on antiarrhythmic drug therapy. The QTc formulas of Bazett, Fridericia, Framingham, Hodges, and Nomogram were applied to assess the effect of heart rate (baseline, atrial pacing at 60 beats/min, 80 beats/min, and 100 beats/min) on the derived ΔQTc (QTc before and during antiarrhythmic therapy). Results: Drug treatment reduced the heart rate (P < 0.001) and increased the QT interval (P < 0.001). The heart rate increase shortened the QT interval (P < 0.001) and prolonged the QTc interval (P < 0.001) by the use of all correction formulas before and during antiarrhythmic therapy. All formulas gave at 60 beats/min similar ΔQTc of 43 ± 28 ms. At heart rates slower than 60 beats/min, the Bazett and Framingham methods provided the most underestimated ΔQTc values (14 ± 32 ms and 18 ± 34 ms, respectively). At heart rates faster than 60 beats/min, the Bazett and Fridericia methods yielded the most overestimated ΔQTc values, whereas the other 3 formulas gave similar ΔQTc increases of 32 ± 28 ms. Conclusions: Bazett's formula should be avoided to assess ΔQTc at heart rates distant from 60 beats/min. The Hodges formula followed by the Nomogram method seem most appropriate in assessing ΔQTc. (J Cardiovasc Electrophysiol, Vol. 21, pp. 905‐913, August 2010)     

健康人不同导联QT变异及QT变异指数

探讨健康人不同导联的QT变异(QTV)及QT变异指数(QTVI)。55例健康人在保持日常工作和生活起居的情况下佩戴12导联动态心电图监测仪,计算机辅助下自动测量12导联QT间期,计算每个导联每小时、24h、白天(6:00～22:00)和夜间(22:00～6:00)QT间期均值及其标准差、HR间期均值及其标准差,它们分别代表相应时间段的QT间期均值(QTm)、QTV、HR间期均值(HRm)和HR间期变异(HRV)。计算QTVI。同时运用心率变异时域指标SDNN观察自主神经活性。结果:不同导联间的QTV、QTVI比较具有显著性差异,P<0.05。不同导联24hQTV、QTVI与SDNN均存在负相关,P<0.05。结论:在使用QTV、QTVI来评价不同人群的心室复极离散时,要考虑到不同导联之间的可比性和一致性。QTVI是一种能更直接地反映心室复极逐波变化的新指标。     

Evaluation of QT Interval Dispersion in a Multiple Electrodes Recording System versus 12‐Lead Standard ECG in an In Vitro Model

Background: QT interval dispersion (QTID) as assessed on conventional surface electrocardiogram (ECG) has been used as a clinical tool to identify patients at high risk of ventricular arrhythmia. However, the results obtained have been controversial. The main purpose of this study was to compare QTID measured from an array of 5 × 6 electrodes homogeneously distributed against the values found when the 12‐lead standard ECG was used. Methods: QTID was calculated in a modified Langendorff‐perfused rabbit heart model immersed in a cylindrical chamber. Dispersion in ventricular repolarization was artificially increased by d‐sotalol (60 μ;m) perfusion. Results: All the duration variables measured from any of the lead systems used were significantly increased after d‐sotalol perfusion. The most commonly used variables in clinical studies, such as QTID (maximum ‐ minimum), do not reach a level of statistical significance, except when measured from the 30‐electrodes array or 15 electrodes covering the left or right side of the heart. The standard deviation of the QT interval (QTI) hardly reached a significant level (P = 0.0499) when calculated from the 12‐lead standard ECG. QTID measured at the peak of the T wave exhibited the highest level of significance when calculated from any of the lead systems used. Conclusion: Thirty electrodes homogeneously distributed on the body surface can better discriminate changes in heterogeneity of repolarization. These data further support the importance of multiple recording systems for the evaluation of QTID and may help to provide an understanding of the discrepancies found in clinical applications.     

Beat‐to‐Beat QT Interval Variability Is Primarily Affected by the Autonomic Nervous System

Background : Beat‐to‐beat QT interval variability is associated with life‐threatening arrhythmias and sudden death, however, its precious mechanism and the autonomic modulation on it remains unclear. The purpose of this study was to determine the effect of drugs that modulate the autonomic nervous system on beat‐to‐beat QT interval. Method : RR and QT intervals were determined for 512 consecutive beats during fixed atrial pacing with and without propranolol and automatic blockade (propranolol plus atropine) in 11 patients without structural heart disease. Studied parameters included: RR, QTpeak (QRS onset to the peak of T wave), QTend (QRS onset to the end of T wave) interval, standard deviation (SD) of the RR, QTpeak, and QTend (RR‐SD, QTpeak‐SD, and QTend‐SD), coefficients of variation (RR‐ CV, QTpeak‐CV, and QTend‐CV) from time domain analysis, total power (TP; RR‐TP, QTpeak‐TP, and QTend‐TP), and power spectral density of the low‐frequency band (LF; RR‐LF, QTpeak‐LF, and QTend‐LF) and the high‐frequency band (HF; RR‐HF, QTpeak‐HF and QTend‐HF). Results : Administration of propranolol and infusion of atropine resulted in the reduction of SD, CV, TP, and HF of the QTend interval when compared to controlled atrial pacing (3.7 ± 0.6 and 3.5 ± 0.5 vs 4.8 ± 1.4 ms, 0.9 ± 0.1 and 0.9 ± 0.1 vs 1.2 ± 0.3%, 7.0 ± 2.2 and 7.0 ± 2.2 vs 13.4 ± 8.1 ms², 4.2 ± 1.4 and 4.2 ± 1.2 vs 8.4 ± 4.9 ms², respectively). Administration of propranolol and atropine did not affect RR interval or QTpeak interval indices during controlled atrial pacing. Conclusions : Beat‐to‐beat QT interval variability is affected by drugs that modulate the autonomic nervous system.     

Comparison of the Four Formulas of Adjusting QT Interval for the Heart Rate in the Middle‐Aged Healthy Turkish Men

Objective: The aim of this study was to evaluate the QT intervals at different rest heart rates in healthy middle‐aged Turkish men and to compare the known four QT adjusting methods for heart rate. Methods and Results: The QT intervals were measured in electrocardiograms of 210 healthy men (mean age = 35–60 years). A curve relating QT intervals and heart rates from 45 to 135 beats/min was constructed for study population. Based on the formula of Bazett, Fridericia, and Framingham, adjusted QT intervals in these range of heart rates were separately estimated. An adjusting nomogram for different heart rates was created using a reference value, which was the measured QT interval at heart rate of 60 beats/min (QT_No= QT + correcting number). These four QT correction methods were compared with each other. The reference value of QT interval at heart rate of 60 beats/min was 382 ms. The relationship between QT and RR interval was linear (r = 0.66, P < 0.001). Nomogram method corrected QT interval most accurately for all the heart rates compared with other three adjusting methods. At heart rates of 60–100 beats/min, the equation of linear regression was QT = 237 + 0.158 × RR (P < 0.001). Bazett's formula gave the poorest results at all the heart rates. The formulas of Fridericia and Framingham were superior to Bazett's formula; however, they overestimated QT interval at heart rate of 60–110 beats/min (P < 0.01). At lower rates (<60 beats/min), all methods except nomogram method, underestimated QT interval (P = 0.03). Conclusion: Among four QT correction formulas, the nomogram method provides the most accurately adjusted values of QT interval for all the heart rates in healthy men. Bazett's formula fails to adjust the QT interval for all the heart rates.