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)     

Electrocardiographic Identification of Drug‐Induced QT Prolongation: Assessment by Different Recording and Measurement Methods

Background: Careful assessment of QT interval prolongation is required before novel drugs are approved by regulatory authorities. The choice of the most appropriate method of electrocardiogram (ECG) acquisition and QT/RR interval measurement in clinical trials requires better understanding of the differences among currently available approaches. This study compared standard and Holter‐derived 12‐lead ECGs for utility in detecting sotalol‐induced QT/QTc and RR changes. Manual methods (digitizing pad and digital on‐screen calipers) were compared for precision of QT and RR interval measurement. Methods and Results: Sixteen hundred pairs of serial 12‐lead digital ECGs were recorded simultaneously by standard resting ECG device and by continuous 12‐lead digital Holter over 3 days in 39 healthy male and female volunteers. No therapy was given on the 1st day followed by 160 mg and 320 mg of sotalol on the 2nd and 3rd day, respectively. Holter‐derived and standard ECGs produced nearly identical sotalol‐induced QT/QTc and RR changes from baseline, as did the manual digipad and on‐screen caliper measurements. The variability of on‐screen QT measurement in this study was greater than that of digipad. Conclusions: Digital 12‐lead Holter and standard 12‐lead ECG recorders, as well as the manual digitizing pad and digital on‐screen calipers, are of equal utility for the assessment of drug‐induced change from baseline in QT and RR interval, although the variability of the on‐screen method in this study was greater than of the digipad.     

A Study of the Association between the Prolongation of the QT Interval in the Resting ECG and Myocardial Infarction

ABSTRACT The relationship between the incidence of myocardial infarction in the 10 year follow-up period and the length of the QT interval and its two components (the time elapsing between the Q wave and the beginning of the T wave, and the duration of the T wave) was investigated in a study of the records of a group of men drawn from a random sample of all 55-year-old men living in Göteborg, Sweden. A significant association was found between the incidence of myocardial infarction and the first component but not with the second component or the QT interval itself. The two components were found to be independent and thus to have the potential to act as confounding factors if the QT interval is examined alone. Further, our results suggest that correcting the QT interval for heart rate needs careful reassessment.     

Correction for QT/RR Hysteresis in the Assessment of Drug‐Induced QTc Changes—Cardiac Safety of Gadobutrol

Background: The so‐called thorough QT/QTc (TQT) studies required for every new pharmaceutical compound are negative if upper single‐sided 95% confidence interval (CI) of placebo and baseline corrected QTc prolongation is <10 ms. This tight requirement has many methodological implications. If the investigated drug has a fast action and ECGs cannot be obtained at stable heart rates, QT/RR hysteresis correction is needed. Methods: This was used in a TQT study of gadobutrol. The TQT study was a randomized double‐blind five‐times crossover study of three doses of gadobutrol (0.1, 0.3, and 0.5 mmol/kg) that was placebo and positive effect controlled (moxifloxacin 400 mg). The study enrolled 50 healthy subjects with data of all periods. QT/RR hysteresis was assessed from prestudy exercise test ECGs. Among others, comparisons were made between population heart rate correction without hysteresis considerations and combined population heart rate and hysteresis correction. Results: The highest heart rate increase (placebo and baseline controlled) of 13.1 beats per minute (90% CI 9.9–16.4) occurred 1 minute after the administration of the highest dose of gadobutrol. Without hysteresis consideration, the highest ΔΔQTc were 9.91 ms (90% CI 8.01–11.81) while with hysteresis correction, these values were 7.62 ms (90% CI 6.37–8.87), thus turning a marginally positive TQT study into a negative finding. Conclusion: Hence, omitting hysteresis correction from episodes of fast heart rate changes may lead to incorrect conclusions. Despite substantial rate acceleration, accurate hysteresis correction confirms that gadobutrol does not have any effects on cardiac repolarization that would be within the limits of regulatory relevance.     

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.     

Reproducibility of QT Parameters Derived from 24‐hour Ambulatory ECG Recordings in Healthy Subjects

Aim: To estimate the reproducibility of QT parameters derived from 24‐hour ambulatory ECG recordings. Method: Ten healthy volunteers aged 25 to 41 years participated. In two 24‐hour ambulatory ECG recordings obtained 1 day apart, the QT interval was measured manually at stable heart rates in approximately 16 periods during daytime and 6 periods during nighttime. The association between the QT and RR interval was described by linear regression for day and nighttime separately and the following QT parameters were calculated: the QT interval at heart rate 60 beats/min during daytime (QT(60)day), slope(day), slope(night), and the difference in QT(60) between day and nighttime (ΔQT(60)). The QT parameters were assessed four times for each participant to discriminate method inaccuracy from day to day variation. The reproducibility was estimated as the coefficient of repeatability, the relative error, and the ratio between within‐subject variability and between‐subject variability. Results: The coefficient of repeatability, the relative error and the ratio, respectively, were 19 ms, 1.8% and 0.5 for QT(60)day, 0.076, 21% and 0.68 for slope(day), 0.116, 43% and 1.37 for slope(night), and 37 ms, 325% and 1.19 for ΔQT(60) when estimating the overall day to day reproducibility. Inaccuracy of QT measurement accounted for approximately 40% of this variation, whereas the error caused by selecting segments was small. Conclusion: QT(60)day has a high reproducibility and may with advantage replace the conventional QT interval measured on a resting ECG. To assess QT dynamics, the slope of the regression line during daytime is suitable and the short term reproducibility acceptable for clinical trials. Regarding slope(night) and ΔQT(60), the variation is high and the parameters should be used with caution. A.N.E. 2001;6(1):24–31     

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.     

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.     

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.     

Automated versus Manual Measurement of the QT Interval and Corrected QT Interval

Background: The International Conference on Harmonization E14 Guideline specifies detailed assessment of QT interval or corrected QT interval prolongation when developing new drugs. We recently devised new software to precisely measure the QT interval. Methods and Results: The QT intervals of all leads for a selected single heart beat were compared between automated measurement with the new software from Fukuda Denshi and manual measurement. With both automated and manual measurement, QT intervals obtained by the tangent method were shorter than those obtained by the differential threshold method, but the extent of correction was smaller. QT interval data obtained by the differential threshold method were more similar to values obtained by visual measurement than were data obtained by the tangent method, but the extent of correction was larger. Variability was related to the T‐wave amplitude and to setting the baseline and tangent in the tangent method, while skeletal muscle potential noise affected the differential threshold method. Drift, low‐amplitude recordings, and T‐wave morphology were problems for both methods. Among the 12 leads, corrections were less frequent for leads II and V₃–V₆. Conclusion: We conclude that, for a thorough assessment of the QT/QTc interval, the tangent method or the differential threshold method appears to be suitable because of smaller interreader differences and better reproducibility. Correction of data should be done by readers who are experienced in measuring the QT interval. It is also important for electrocardiograms to have little noise and for a suitable heart rate and appropriate leads to be selected. Ann Noninvasive Electrocardiol 2011;16(2):156–164     

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 Head‐Up Tilt‐Table Test on the QT Interval

Background. The QT interval shortens in response to sympathetic stimulation and its response to epinephrine infusion (in healthy individuals and patients with long QT syndrome) has been thoroughly studied. Head‐up tilt‐table (HUT) testing is an easy way to achieve brisk sympathetic stimulation. Yet, little is known about the response of the QT interval to HUT. Methods. We reviewed the electrocardiograms of HUT tests performed at our institution and compare the heart rate, QT, and QTc obtained immediately after HUT with the rest values. Results. The study group consisted of 41 patients (27 females and 14 males) aged 23.9 ± 8.4 years. Head‐up tilting led to a significant shortening of the RR interval (from 825 ± 128 msec at rest phase to 712 ± 130 msec in the upward tilt phase, P < 0.001) but only to a moderate shortening of the QT interval (from 363.7 ± 27.9 msec during rest to 355 ± 30.3 msec during upward tilt, P = 0.001). Since the RR interval shortened more than the QT interval, the QTc actually increased (from 403 ± 21.5 msec during rest phase to 423.2 ± 27.4 msec during upward tilt, P < 0.001). The QTc value measured for the upward tilt position was longer than the resting QTc value in 33 of 41 patients. Of those, 4 male patients and 2 female patients developed upward‐tilt QTc values above what would be considered abnormal at rest. Conclusions. During HUT the QT shortens less than the RR interval. Consequently, the QTc increases during head‐up tilt. Ann Noninvasive Electrocardiol 2010;15(3):245–249     

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     

Relation between Beat‐to‐Beat QT Interval Variability and T‐Wave Amplitude in Healthy Subjects

Objectives: Elevated beat‐to‐beat QT interval variability (QTV) has been associated with increased cardiovascular morbidity and mortality.The aim of this study was to investigate interlead differences in beat‐to‐beat QTV of 12‐lead ECG and its relationship with the T wave amplitude. Methods: Short‐term 12‐lead ECGs of 72 healthy subjects (17 f, 38 ± 14 years; 55 m, 39 ± 13 years) were studied. Beat‐to‐beat QT intervals were extracted separately for each lead using a template matching algorithm. We calculated the standard deviation of beat‐to‐beat QT intervals as a marker of QTV as well as interlead correlation coefficients. In addition, we measured the median T‐wave amplitude in each lead. Results: There was a significant difference in the standard deviation of beat‐to‐beat QT intervals between leads (minimum: lead V₃ (2.58 ± 1.36 ms), maximum: lead III (7.2 ± 6.4 ms), ANOVA: P < 0.0001). Single measure intraclass correlation coefficients of beat‐to‐beat QT intervals were 0.27 ± 0.18. Interlead correlation coefficients varied between 0.08 ± 0.33 for lead III and lead V₁ and 0.88 ± 0.09 for lead II and lead aVR. QTV was negatively correlated with the T‐wave amplitude (r =–0.62, P < 0.0001). There was no significant affect of mean heart rate, age or gender on QT variability (ANOVA: P > 0.05). Conclusions: QTV varies considerably between leads in magnitude as well as temporal patterns. QTV is increased when the T wave is small.     

Computer‐Based Analysis of Dynamic QT Changes: Toward High Precision and Individual Rate Correction

Background: New strategies are needed to improve the results of automatic measurement of the various parts of the ECG signal and their dynamic changes. Methods: The EClysis software processes digitally‐recorded ECGs from up to 12 leads at 500 Hz, using strictly defined algorithms to detect the PQRSTU points and to measure ECG intervals and amplitudes. Calculations are made on the averaged curve of each sampling period (beat group) or as means ± SD for beat groups, after being analyzed at the individual beat level in each lead. Resulting data sets can be exported for further statistical analyses. Using QT and R‐R measured on beat level, an individual correction for the R‐R dependence can be performed. Results: EClysis assigns PQRSTU points and intervals in a sensitive and highly reproducible manner, with coefficients of variation in ECG intervals corresponding to ca. 2 ms in the simulated ECG. In the normal ECG, the CVs are 2% for QRS, 0.8% for QT, and almost 6% for PQ intervals. EClysis highlights the increase in QT intervals and the decrease of T‐wave amplitudes during almokalant infusion versus placebo. Using the observed linear or exponential relationships to adjust QT for R‐R dependence in healthy subjects, one can eliminate this dependence almost completely by individualized correction. Conclusions: The EClysis system provides a precise and reproducible method to analyze ECGs. A.N.E. 2002;7(4):289–301     

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.