| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|
|
|
|||||||
|
|||||||||
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
CLINICAL STUDIES |
From Lariboisière University Hospital—APHP—Paris 7 University, France (Dr Extramiana, Dr Leenhardt, Dr Maison-Blanche); AMPS LLC, New York (Dr Badilini); and Daiichi Sankyo Pharma Development, Edison, New Jersey (Dr Sarapa).
Address for correspondence: Fabrice Extramiana, MD, PhD, Cardiology Department—Lariboisière University Hospital, 2 rue Ambroise Parè—75010, Paris, France; e-mail: Fabrice.extramiana{at}lrb.aphp.fr.
 |
ABSTRACT |
|---|
 TOP ABSTRACT METHODSRESULTSDISCUSSIONACKNOWLEDGEMENTSREFERENCES |
|---|
coefficients increased from placebo (0.309 ± 0.052) to sotalol (0.454 ± 0.136), P < .0001. When the placebo individual coefficients were applied to correct the QT interval on sotalol, the changes were >5 ms smaller than those obtained using the ON drug coefficients. The "rate"-averaging process leads to a complete loss of the time course of drug effect. In conclusion, the individual correction formula calculated from the placebo condition cannot always be used for QT correction on the drug.
Key Words: QT interval • sotalol • Holter ECG
The characterization of drugs' effects on QT interval in pre-approval trials is therefore essential to prevent rare but serious adverse events for a drug potentially occurring in more vulnerable individuals in a large population exposed to the drug in post-marketing practice.5 Accordingly, regulatory agencies issued recommendations concerning the design, the analysis, and the interpretation of clinical studies to assess the potential of a drug on the QT/QTc interval duration.6-8
Thorough QT studies have to deal with complex sources of variations, which include heart rate-dependent and heart rate-independent factors.9-13 In this regard, the Critical Path Initiative, launched by the US Food and Drug Administration, is an attempt to improve the use of science in drug evaluation.14
Although heart rate changes are the main source of variation of the QT interval, the management of heart rate influences on QT duration is so far not resolved. Two different approaches are conceivable. Most of the data submitted by pharmaceutical companies normalize the QT duration to a 60-bpm heart rate (HR), and "universal" (Bazett and Fridericia) rate correction is still used instead of the state-of-the-art subject-specific correction formula.15 The comparison of the QT interval at identical HR has recently been proposed to avoid the need for any HR correction formula.16-18
The debates on these fundamentally different approaches are not only academic discussions.19 Indeed, thorough QT studies are intended to detect a threshold level of regulatory concern as low as 5 to 10 ms.7 Thus, any potential methodological confounding factor may induce a bias that, although quantitatively small, may have major implications for drug safety.
The aim of this article is to highlight the relative advantages and disadvantages and potential biases of different validated methods used for the assessment of drugs' effect on QT interval duration. Hence, we evaluated the effect of sotalol, a well-known torsadogen drug that also has an effect on heart rate and on QT duration in healthy subjects, using 2 different approaches: the QT correction and the comparison at identical heart rate.
|
METHODS |
|---|
|
TOPABSTRACTMETHODSRESULTSDISCUSSIONACKNOWLEDGEMENTSREFERENCES |
|---|
Electrocardiogram Recording and Analysis
We report the results from the analysis of continuous digital 12-lead Holter ECG recordings (H12 recorders, Mortara Instrument, Inc, Milwaukee, Wisconsin; 180 samples per second) obtained at baseline (day 0) and after a single dose of sotalol 160 mg (day 1). The on-treatment data were compared to baseline data during a 4-hour time window centered around tmax (±2 hours from the plasma tmax of sotalol) in each subject and the chronologically matching part of the Holter trace at baseline.
Electrocardiogram recordings were edited (H-Scribe, Mortara Instrument, Inc) to ensure that cardiac beats of sinus origin were accurately identified and that nonsinus beats as well as artifacts had been excluded for quantitative analysis. Electrocardiogram recordings were then transferred to a dedicated software (WinAtrec 8.00, AMPS LLC, New York) used to perform a beat-averaging approach that has been called the "bin" method.17,21-23
Two separate binning/averaging approaches were applied to the 4-hour analysis window. The first is time binning, and it is aimed to assess the drug effect on the QT interval duration at different time points. Within the 4-hour analysis window, 1 template every minute is constructed, thus generating 240 time bins for each recording.
The QT interval duration obtained in each individual time bin template was corrected using Bazett's formula (QTcB = QT/RR1/2), Fridericia's formula (QTcF = QT/RR1/3), and the subject-specific correction formula based on a power-law (log-log) model (QTcNi = QT/RRNi), using the 1-minute averaged RR interval.
The computation of QTcNi was applied separately on baseline and on sotalol measurements. We will thus refer to QTcNi-OFF to indicate heart rate corrections using power-law best fit from the baseline data and QTcNi-ON to indicate heart rate corrections using the power-law best fit from the sotalol data.
The second averaging method applied was the so-called RR-bin approach, also commonly referred to as rate binning. With this method, QT duration is evaluated at fixed RR interval levels (the RR bins), with 10-ms resolution between adjacent RR bins.
Individual cardiac complexes of sinus origin are stratified according to the value of the preceding RR interval (RR-1). The cardiac complexes are subsequently accepted for averaging (ie, included in the RR bin) only when they are preceded by stable heart rate. Heart rate stability was defined by the following formula:
 |
where RR[observation period] is the mean RR interval of the period considered for heart rate stability, and thr is a tolerance threshold. In this study, the observation period was fixed to 60 seconds (R60)24 and the threshold to 20 ms.
Comparisons of QT interval durations at the same heart rate (ie, from same RR bins from baseline and sotalol templates), and thus without the implantation of a correction formula, were performed. In addition, we also calculated the individual power-law log/log model coefficients at baseline and on sotalol from the rate-binning data.
As an alternative rate-independent method, 
QT/RR plots were constructed from the time bins series. The intercept (ie, RR = 0) of the linear relationship describing the data was used as the rate-independent point estimate of drug-induced QT change. This approach was performed on both populations (ie, by pooling all the QT/RR pairs from all the study population) and on an individual basis.
QT measurements on both time and rate bins were blindly performed by a single reader (Pierre Maison-Blanche). The analysis was carried out on a single preferred lead in each subject. The endpoints of the study were as follows:
the change in QT or QTc interval duration on sotalol versus placebo at an identical time point (the change in QT interval duration on sotalol versus placebo at identical heart rate for the rate-binning approach and the point estimate.
Statistical Analysis
Data are presented as mean ± SD. Comparisons between placebo and sotalol were performed using a 2-tail paired Student test. A P value <.05 was considered significant. Statistical analysis was performed using Statview 5.0 (SAS Institute, Inc, Cary, North Carolina).
|
RESULTS |
|---|
|
TOPABSTRACTMETHODSRESULTSDISCUSSIONACKNOWLEDGEMENTSREFERENCES |
|---|
Sotalol Effect on QT Duration
Time Bin Analysis
The individual coefficient from power-law best-fit analysis significantly increased from placebo (0.309 ± 0.052; range, 0.197-0.416) to sotalol (0.454 ± 0.136; range, 0.208-0.783), P < .0001 (Table I).
|
The time course of sotalol-induced QTcNi prolongation from the 240 time points is shown in Figure 1.
|
QT, QTc (Bazett, Fridericia), and QTcNi (QTcNi-ON) are depicted. The Emax for the effect of sotalol was delayed approximately 60 minutes after the tmax for sotalol concentration in plasma (Figures 1 and 2). The change in uncorrected QT was overtly larger than the changes in heart rate-corrected QT. The smallest QT was observed when using Bazett's correction formula (Figure 2). Conversely, both Fridericia and the individual correction formulas provided a larger similar significant 30- to 40-ms QT prolongation around Emax (Figure 3 and Table II). For instance, at T180, QTcB was 21.4 IC95% [12.9-30.0] and QTcNi 35.0 IC95%[24.7-45.3].
|
|
|
In Figure 3, the differences between the QTcNi-OFF and the QTcNi-ON are highlighted. When the placebo individual coefficients were applied to correct the QT interval on sotalol (QTcNi-OFF), the changes were smaller than those obtained using the ON drug coefficient (QTcNi-ON). For instance, at T120, the differences were a 6.5-ms decrease and at T180 a 5-ms decrease (Table II and Figure 3).
The drug-induced increase in individual coefficients was not homogeneous after sotalol administration. Indeed, the individual coefficients calculated from the first 120 ECGs (0-2 hours) were significantly higher than the coefficients calculated from the last 120 ECGs (2-4 hours; P < .05 on both placebo and sotalol; Table I).
Rate Bin Analysis
Figure 4 and Table III show the prolonging effect of sotalol on QT interval duration, as assessed using the rate-binning approach, and exemplify the reverse rate dependence of sotalol-induced QT prolongation.
|
|
With rate binning, the individual coefficients were not used for heart rate correction because this method allows QT duration comparisons at the same heart rate without using any heart rate correction formula. However, the individual coefficients were also calculated with this approach. The coefficients were 0.315 ± 0.049 (range, 0.197-0.432) on placebo and 0.419 ± 0.097 (range, 0.231-0.718) on sotalol, P < .0001.
The Point Estimate From QT/RR Plots Analysis
In Table IV, the intercept of the QT/RR regression analysis (the point estimates), computed from the overall population and from a subject-specific basis and repeated over the entire 4-hour analysis and over the 2-hour subperiods, is reported.
|
The point estimate calculated from the 4 hours of the recordings is different from the two 2-hour periods. The point estimate of sotalol-induced QT prolongation was larger over the second time window.
|
DISCUSSION |
|---|
|
TOPABSTRACTMETHODSRESULTSDISCUSSIONACKNOWLEDGEMENTSREFERENCES |
|---|
The Time-Binning Approach
Thorough QT studies are usually based on the serial recording of 10-second 12-lead surface ECG recordings. The assessment of the time course of the drug's effects together with parmakokinetic data is a useful tool to evaluate the drug concentration-response. In addition, thorough QT studies need to be placebo controlled,7 and because the duration of the QT interval at baseline has been shown to follow a circadian rhythm,11,25 serial time-matched measurements are mandatory for any placebo-corrected evaluation. Therefore, all of the thorough QT studies are based on numerous ECG recordings. The ICHE14 document expresses a concern about using data from ambulatory ECG recordings because QT interval durations from Holter ECG might not quantitatively correspond to those from standard ECG.7 In the present study, we made use of long-term ambulatory ECG recordings from which 12-lead ECGs were extracted every minute. This method is referred to as the time bin approach. We could obtain a much larger number of data points than what is normally available from the standard thorough QT design using serial ECG recordings. The sotalol-induced QTc prolongation reported in the present study is very similar to those published on the same database but uses the "conventional" approach based on serial resting 10-second ECG recordings.20
|
Using the optimum HR correction strategy (ie, a different HR correction formula for each subject on placebo and on drug) is associated with different pit-falls. The relationship between HR and QT duration not only is subject specific but also shows circadian (day/night) variations32,33 where even hourly changes have been reported.25 In the present study, the QT values derived by the HR correction formula on placebo were significantly different between the first 2-hour period versus the subsequent 2-hour period. As a consequence, applying the same HR correction at different time points for a given subject may result in bias. Moreover, on top of physiologic variations, pharmacokinetic/pharmacodynamic considerations may also have detrimental consequences in a single-dose trial. In our study, the effect of sotalol on ventricular repolarization was not constant through the 4-hour observation period, despite having defined the period according to pharmacokinetic data. This problem was worsened by a delayed Emax from tmax. Again, using a unique "on-drug" HR correction formula while the drug's concentration changes may induce a potential bias.
Repeated assessment of the QT/RR relationship from appropriately short observation periods may overcome these drawbacks. However, narrowing the observation period is associated with a decrease in the number of QT/RR pairs available from each period, leading to a less precise evaluation of the QT/RR relationship. On the same data as reported in the present study, Couderc et al34 have shown that a large number of QT/RR pairs, together with a wide range of RR intervals, are required for a reliable individual correction model. The use of a moving time window for QT/RR relationship assessment may be a solution to get a better time definition for the coefficient but again keeping in mind the need for a sufficient range of RR intervals.
In summary, even the best currently known strategies for detecting the time course of drug-induced QT prolongation are inherently associated with an imprecision in the HR correction process.
The Rate-Binning Approach
The Holter-based so-called rate bin approach had been originally developed by our group to better characterize the relationship between HR and QT duration.22,33,35,36 Subsequently, this method has been used as an alternative approach to measure rate-independent estimates of QT interval changes under treatment.17 The main benefit brought about by this method is to allow direct comparison of ECG samples at identical HR, thus avoiding the need for any QT correction formulas. Therefore, no mathematical models are required, and no assumptions on the properties and stability of the QT/RR relationship are necessary. In contrast to the time bin approach, the rate bin method is not hampered by the potential effect of the drug on the relationship between QT interval and heart rate. Although the calculation of the QT rate dependence is not required with the rate bin approach, it may easily be computed to provide similar results as those obtained with the time bin approach. The main advantage of the rate bin method is the capability of emphasizing the influence of heart rate on the drug's effect. Our data show that the sotalol-induced QT prolongation was more pronounced at slow than at fast HRs. This phenomenon, known as the "reverse rate-dependent effect," has been long recognized with class III antiarrhythmic drugs31,37 and has been demonstrated even with weak IKr blockers such as moxifloxacin using the rate bin method.24,38
Despite its conceptual advantages, the rate bin approach has been criticized.19 An intrinsic limitation of the method is represented by the impossibility of QT comparisons when there are no overlapped RR intervals. This might be the case with drugs that dramatically change HR, although it is very unlikely provided that the QT comparison might be performed at any heart rate (ie, not necessarily at RR = 1000 ms).
The second, more significant drawback is that the averaging process leads to a complete loss of the time course of drug effect. Consequently, the largest time-matched mean difference between the drug and placebo cannot be assessed.
A potential solution to improve the analysis of the time course of the drug's effect on QT prolongation would be to narrow the time window of rate binning. However, a shorter observation period might result in missing QT measurements at some heart rates (RR bins), thus making the comparison with placebo data difficult. The rate bin approach is therefore not perfect; on one side, it solves the HR correction problem, but the price paid is a loss of the precision of temporal assessment.
The QT/RR Plots
The intercept of the linear QT/RR relationship is a standard use of an analysis of covariance that has been proposed as the rate-independent point estimate of drug-induced QT change.17 Its simplicity has made this method attractive, yet it has been so far poorly evaluated and seldom used for thorough QT studies. One legitimate issue about this method is whether it should be calculated on a population- or a subject-specific basis. The population-based approach includes many QT/RR pairs and thus provides narrow confidence intervals. However, the pathophysiological meaning of such results is difficult to understand, whereas the calculation of the mean of individual point estimates is more intuitive. With the individual approach, the number of QT/RR pairs is dramatically decreased, and the accuracy of each individual point estimate might be questionable. So far, the minimum number of pairs required for a fair estimation of drug effect has not been determined. The present study included ECG data from 240 time points for each subject, and both population- and subject-specific approaches provided very similar point estimates of sotalol-induced QT prolongation, although their boundaries were quite different.
Because of the very large number of QT/RR pairs available with the population approach, it is easy to narrow the observation period. We could thus confirm with the 2-hour point estimates the hetero-geneity of the sotalol effect over the 4-hour period observed by using the time bin method. However, further narrowing of the observation period would lead to a loss of accuracy as a consequence of reducing the number of QT/RR pairs mainly with the subject-specific approach. Therefore, as with the rate bin method, the time course of drug effect is lost by using the point estimate approach.
In addition, the point estimate method represents a mix of the drug's effect at various heart rates and cannot always be compared to an effect at the corrected QT interval or at a 1000-ms RR interval.
Finally, the point estimate approach combines the disadvantages of the loss of time track of rate binning, and as with the time bin approach, it provides no data on rate influences on the drug's effect.
Study Limitations
The main limitation is represented by the potent IKr block effect of sotalol. The magnitude of the potential disadvantages of each method described in the present study may not be the same with weaker potassium current blockers. Nevertheless, the limitations underlined in the present study are inherent to each method.
It should be recognized that some of the method-related discrepancies observed in single-dose trials may not be valid for repeated-dose trials. Our study does not include a pharmacokinetic/pharmacodynamic model, and some of sotalol's effects on QT duration as well as the QT/RR relationship may be dependent on its concentration. However, our placebo data underline that ventricular repolarization properties change within a few hours independently of the drug's concentration. Therefore, similar changes in the QT/RR relationship may be also observed at the drug's steady-state concentration. In addition, as discussed earlier, with fast-changing drug concentration, both the rate and time bin approaches would have been hampered by using short time windows.
Conclusion
The evaluation of drugs' influences on QT interval duration is a difficult process because of the complex properties of ventricular repolarization and its modulation by ionic channel-blocking drugs. No currently used ECG method can be considered free of pitfalls. The individual correction formula calculated from the placebo condition cannot always be used for QT correction on the drug. On the other hand, the rate bin approach is characterized by a loss of the precision of temporal assessment. In that respect, the combination of different approaches seems to be a reasonable strategy. The recording of long, continuous ECGs, as provided by digital 12-lead Holter technology, would be appropriate for a primary analysis in the thorough QT study or as a support for additional analyses.
|
ACKNOWLEDGEMENTS |
|---|
|
TOPABSTRACTMETHODSRESULTSDISCUSSIONACKNOWLEDGEMENTSREFERENCES |
|---|
|
REFERENCES |
|---|
|
TOPABSTRACTMETHODSRESULTSDISCUSSIONACKNOWLEDGEMENTSREFERENCES |
|---|
1. Ray WA, Murray KT, Meredith S, Narasimhulu SS, Hall K, Stein CM. Oral erythromycin and the risk of sudden death from cardiac causes. N Engl J Med. 2004;351: 1089-1096.
2. Crouch MA, Limon L, Cassano AT. Clinical relevance and management of drug-related QT interval prolongation. Pharmacotherapy. 2003;23: 881-908.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
3. Redfern WS, Carlsson L, Davis AS, et al. Relationships between preclinical cardiac electrophysiology, clinical QT interval prolongation and Torsade de Pointes for a broad range of drugs: evidence for a provisional safety margin in drug development. Cardiovasc Res. 2003;58: 32-45.
4. Vos MA, van Opstal JM, Leunissen JD, Verduyn SC. Electro-physiologic parameters and predisposing factors in the generation of drug-induced Torsade de Pointes arrhythmias. Pharmacol Ther. 2001;92: 109-122.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
5. Curtis LH, Ostbye T, Sendersky V, et al. Prescription of QT-prolonging drugs in a cohort of about 5 million outpatients. Am J Med. 2003;114: 135-141.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
6. Malik M, Camm AJ. Evaluation of drug-induced QT interval prolongation: implications for drug approval and labelling. Drug Saf. 2001;24: 323-351.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
7. International Conference on Harmonization (ICH). E14 Clinical Evaluation of QT/QTc Interval Prolongation and Proarrhythmic Potential for Non-Antiarrhythmic Drugs. Available at: http://www.fda.gov/cder/guidance/6922fnl.pdf. Accessed August 21, 2006.
8. Shah RR. Drugs, QTc interval prolongation and final ICH E14 guideline: an important milestone with challenges ahead. Drug Saf. 2005;28: 1009-1028.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
9. Bazett HC. An analysis of the time relationship of electrocardiograms. Heart. 1920;7: 353-370.[Web of Science]
10. Franz MR, Swerdlow CD, Liem LB, Schaefer J. Cycle length dependence of human action potential duration in vivo: effects of single extrastimuli, sudden sustained rate acceleration and deceleration, and different steady state frequency. J Clin Invest. 1988;82: 972-979.[Web of Science][Medline] [Order article via Infotrieve]
11. Browne KF, Prystowsky E, Heger JJ, Chilson DA, Zipes DP. Prolongation of the QT interval in man during sleep. Am J Cardiol. 1983;52: 55-59.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
12. Rautaharju PM, Zhou SH, Wong S, et al. Sex differences in the evolution of the electrocardiographic QT interval with age. Can J Cardiol. 1992;8: 690-695.[Web of Science][Medline] [Order article via Infotrieve]
13. Bexton R, Vallin HO, Camm AJ. Diurnal variation of the QT interval-influence of the autonomic nervous system. Br Heart J. 1986;55: 253-258.
14. Food and Drug Administration. Critical Path Initiative. Innovation or Stagnation? Challenge and Opportunity on the Critical Path to New Medical Products 2004. Available at: http://www.fda.gov.
15. Malik M, Farbom P, Batchvarov V, Hnatkova K, Camm AJ. Relation between QT and RR intervals is highly individual among healthy subjects: implications for heart rate correction of the QT interval. Heart. 2002;87: 220-228.
16. Rautaharju PM, Zhang ZM. Linearly scaled, rate-invariant normal limits for QT interval: eight decades of incorrect application of power functions. J Cardiovasc Electrophysiol. 2002;13: 1211-1218.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
17. Extramiana F, Maison-Blanche P, Cabanis MJ, Ortemann-Renon C, Beaufils P, Leenhardt A. Clinical assessment of drug-induced QT prolongation when associated with heart rate changes. Clin Pharmacol Ther. 2005;77: 247-258.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
18. Indik JH, Pearson EC, Fried K, Woosley RL. Bazett and Fridericia QT correction formulae interfere with measurement of drug-induced changes in QT interval. Heart Rhythm. 2006;3: 1003-1007.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
19. Malik M. Assessment of drug-induced QT prolongation: to bin or not to bin? Clin Pharmacol Ther. 2005;77: 241-246.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
20. Sarapa N, Morganroth J, Couderc JP, et al. Electrocardiographic identification of drug-induced QT prolongation: assessment by different recording and measurement methods. Ann Noninvasive Electrocardiol. 2004;9: 48-57.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
21. Badilini F, Maison-Blanche P, Childers R, Coumel P. QT interval analysis on ambulatory electrocardiogram recordings: a selective beat averaging approach. Med Biol Eng Comput. 1999;37: 71-79.[Web of Science][Medline] [Order article via Infotrieve]
22. Badilini F, Maison-Blanche P. Holter monitoring for QT: the RR bin method in depth. In: Morganroth J, Gussak I, eds. Cardiac Safety of Noncardiac Drugs: Practical Guidelines for Clinical Research and Drug Development. Totowa, NJ: Humana; 2004.
23. Extramiana F, Seitz J, Maison-Blanche P, et al. Quantitative assessment of ST segment elevation in Brugada patients. Heart Rhythm. 2006;3: 1175-1181.[Web of Science][Medline] [Order article via Infotrieve]
24. Extramiana F, Maison-Blanche P, Haggui A, Badilini F, Beaufils P, Leenhardt A. Control of rapid heart rate changes for ECG analysis: implications for thorough QT studies. Clin Cardiol. 2006;29: 534-539.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
25. Yi G, Guo XH, Reardon M, et al. Circadian variation of the QT interval in patients with sudden cardiac death after myocardial infarction. Am J Cardiol. 1998;81: 950-956.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
26. Funck-Brentano C, Jaillon P. Rate-corrected QT interval: techniques and limitations. Am J Cardiol. 1993;72: 17B-22B.[CrossRef][Medline] [Order article via Infotrieve]
27. Malik M. Problems of heart rate correction in assessment of drug-induced QT interval prolongation. J Cardiovasc Electrophysiol. 2001;12: 411-420.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
28. Hnatkova K, Malik M. "Optimum" formulae for heart rate correction of the QT interval. PACE. 1999;22: 1683-1687.[Medline] [Order article via Infotrieve]
29. Malik M. The imprecision in heart rate correction may lead to artificial observations of drug-induced QT interval changes. PACE. 2002;25: 209-216.[Medline] [Order article via Infotrieve]
30. Lande G, Maison-Blanche P, Fayn J, Ghadanfar M, Coumel P, Funck-Brentano C. Dynamic analysis of dofetilide-induced changes in ventricular repolarization. Clin Pharmacol Ther. 1998;64: 312-321.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
31. Funck-Brentano C, Kibleur Y, Le Coz F, Poirier JM, Mallet A, Jaillon P. Rate dependence of sotalol-induced prolongation of ventricular repolarization during exercise in humans. Circulation. 1991;83: 536-545.
32. Viitasalo M, Karjalainen J. QT Intervals at heart rates from 50 to 120 beats per minutes during 24-hour electrocardiographic recordings in 100 healthy men. Circulation. 1992;86: 1439-1442.
33. Extramiana F, Maison-Blanche P, Badilini F, Pinoteau J, Deseo T, Coumel P. Circadian modulation of QT rate dependence in healthy volunteers. J Electrocardiol. 1999;32: 33-43.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
34. Couderc JP, Xiaojuan X, Zareba W, Moss AJ. Assessment of the stability of the individual-based correction of QT interval for heart rate. Ann Noninvasive Electrocardiol. 2005;10: 25-34.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
35. Extramiana F, Neyroud N, Huikuri HV, Koistinen MJ, Coumel P, Maison-Blanche P. QT interval and arrhythmic risk assessment after myocardial infarction. Am J Cardiol. 1999;83: 266-269.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
36. Extramiana F, Maison-Blanche P, Tavernier R, Jordaens L, Leenhardt A, Coumel P. Cardiac effects of chronic oral beta-blockade: lack of agreement between heart rate and QT interval changes. Ann Noninvasive Electrocardiol. 2002;7: 379-388.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
37. Hondeghem LM, Snyders DJ. Class III antiarrhythmic agents have a lot of potential but a long way to go: reduced effectiveness and dangers of reverse use dependence. Circulation. 1990;81: 686-690.
38. Extramiana F, Maison-Blanche P, Badilini F, Beaufils P, Leenhardt A. Individual QT/RR relationship: average stability over time does not rule out an individual residual variability. Implication for the assessment of drug effect on the QT interval. Ann Noninv Electrocard. 2005;10: 169-178.[CrossRef]
CiteULike 
Connotea 
Del.icio.us 
Digg 
Reddit 
Technorati What's this?
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
