(Circulation. 1997;96:1557-1565.)
© 1997 American Heart Association, Inc.
Articles |
Beat-to-Beat QT Interval Variability
Novel Evidence for Repolarization Lability in Ischemic and Nonischemic Dilated Cardiomyopathy
From Johns Hopkins School of Medicine, Baltimore, Md.
Correspondence to Ronald D. Berger, MD, PhD, Carnegie 592, Johns Hopkins Hospital, 600 N Wolfe St, Baltimore, MD 21287. E-mail ron{at}tachy.cdisc.jhu.edu
 |
Abstract |
|---|
 Top Abstract IntroductionMethodsResultsDiscussionReferences |
|---|
Background Dilated cardiomyopathy (DCM) is associated with a high incidence of malignant ventricular arrhythmias and sudden death. Abnormalities in repolarization of ventricular myocardium have been implicated in the development of these arrhythmias. Spatial heterogeneity in repolarization has been studied in DCM, but temporal fluctuations in repolarization in this setting have been largely ignored. We sought to test the hypothesis that beat-to-beat QT interval variability is increased in DCM patients compared with control subjects.
Methods and Results Eighty-three patients with ischemic and nonischemic DCM and 60 control subjects served as the study population. Beat-to-beat QT interval variability was measured by automated analysis on the basis of 256-second records of the surface ECG. A QT variability index (QTVI) was calculated for each subject as the logarithm of the ratio of normalized QT variance to heart rate variance. The coherence between heart rate and QT interval fluctuations was determined by spectral analysis. In patients, ejection fractions were assessed by echocardiography or ventriculography, and spatial QT dispersion was determined from the standard 12-lead ECG. DCM patients had greater QT variance than control subjects (60.4±63.1 versus 25.7±24.8 ms2, P<.0001) despite reduced heart rate variance (6.7±7.8 versus 10.5±10.4 bpm2, P=.01). The QTVI was higher in DCM patients than in control subjects, with a high degree of significance (-0.43±0.71 versus -1.29±0.51, P<10-12). QTVI did not correlate with ejection fraction or spatial QT dispersion but did depend on New York Heart Association functional class. QTVI did not differ between DCM patients with ischemic and those with nonischemic origin. Coherence between heart rate and QT interval fluctuations at physiological frequencies was lower in DCM patients compared with control subjects (0.28±0.14 versus 0.39±0.18, P<.0001).
Conclusions DCM is associated with beat-to-beat fluctuations in QT interval that are larger than normal and uncoupled from variations in heart rate. QT interval variability increases with worsening functional class but is independent of ejection fraction. These data indicate that DCM leads to temporal lability in ventricular repolarization.
Key Words: cardiomyopathy • electrocardiography • repolarization • intervals
|
Introduction |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
Dilated cardiomyopathy (DCM) is a highly prevalent and lethal disease in the United States. When accompanied by congestive symptoms, DCM has been associated with annual mortality rates as high as 25% to 40%,1 2 regardless of origin. Roughly half of these deaths occur suddenly and unexpectedly.3 4 5 In patients with DCM who have not had a myocardial infarction, classic reentrant ventricular tachycardia (VT) is rare and not likely to be the dominant mechanism of sudden cardiac death (SCD). Even among patients with an ischemic cardiomyopathy and prior history of reentrant VT, malignant polymorphic ventricular arrhythmias frequently occur without antecedent monomorphic VT,6 suggesting again that SCD may be related to mechanisms other than excitable gap reentry.
There is growing evidence that myocardial repolarization is altered in the setting of heart failure.7 Cells isolated from failing animal and human hearts display significantly prolonged action potentials compared with those from normal hearts independent of the mechanism of the cardiomyopathy.8 9 10 In addition, several studies have demonstrated the presence of regional heterogeneity in repolarization in DCM patients on the basis of intracardiac monophasic action potential recordings11 and on measurements of the QT interval dispersion in the standard 12-lead surface ECG.12 13 14
We hypothesized that DCM also leads to abnormal beat-to-beat changes in ventricular repolarization. The action potential duration is normally closely coupled with the interbeat (or RR) interval through a variety of mechanisms. These mechanisms may be altered in the failing heart,7 leading to temporal as well as spatial variations in repolarization. Using a new robust algorithm to quantify beat-to-beat fluctuations in the QT interval, we compared QT interval variability in DCM patients with control subjects and analyzed the relations of QT variability with heart rate variability and with the spatial QT interval dispersion.
|
Methods |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
Patient Population and Data Acquisition
The study population included 83 patients with DCM referred to the Johns Hopkins Cardiomyopathy and Heart Transplant Service and 60 control subjects. The sex and age distributions of the group are presented in Table 1
. In this study, DCM refers
to left ventricular systolic dysfunction with
ventricular dilation (end-diastolic diameter
5.8 cm) of any origin. Twenty-nine patients had DCM of
ischemic origin on the basis of either angiographic evidence of
coronary artery disease sufficient to account for the
ventricular dysfunction, or history of myocardial
infarction. The remaining 54 patients had DCM of nonischemic
causes. Patients were excluded if their ECG rhythm was other than
normal sinus. The presence of atrial or ventricular ectopy
was allowed unless such beats represented >5% of all
beats over a 5-minute period. Patients taking class I or III
antiarrhythmic agents were excluded. New York Heart Association
functional class was assessed by the investigators, who were blinded to
the results of subsequent ECG analysis. Left
ventricular ejection fraction was assessed by either
radionuclide or contrast ventriculography or by two-dimensional
echocardiography with the use of Simpson's
rule.15
|
The control group was drawn from healthy volunteers, subjects
participating in the Baltimore Longitudinal Study on
Aging,16 and patients seen in the Johns Hopkins Preventive
Cardiology Clinic, all without a history or evidence of
heart disease and with a normal 12-lead surface ECG. Demographics for
this group are also presented in Table 1
. There was a greater
proportion of men in the DCM group than among control subjects, but age
was not different between groups.
Two unfiltered ECG limb leads (leads I and II) were acquired simultaneously, digitized with 12-bit precision at 1000 samples/s, and stored on removable magnetic media for off-line analysis, with a multichannel data acquisition system (Biopac Systems, Inc) connected to a 486-based computer. Two consecutive 256-second epochs of ECG data were obtained in each subject while supine and awake. Within 2 weeks of these recordings, a standard 12-lead ECG was also obtained (Marquette Medical Systems).
QT Variability Algorithm
A novel algorithm for QT interval measurement was implemented on
a workstation (Sun Microsystems) with a custom-designed graphical
interface. The approach is to let the operator define a template QT
interval by selecting the beginning of the QRS complex and the end of
the T wave for one beat. The algorithm then finds the QT interval of
all other beats by determining how much each beat must be stretched or
compressed in time to best match the template. In this way, changes in
QT interval are assessed using the entire T wave.
Specifically, the steps involved in analyzing a digitized ECG record involve (1) The operator selects which ECG lead to analyze (lead I or II) on the basis of signal quality. Baseline wander is removed by digital filtering, using a passband >0.3 Hz.
(2) The time of each R wave is identified with an automated peak detection algorithm. These time locations are denoted Ti.
(3) The operator selects the beginning and end of the QT interval for
any one beat, denoted beat k. This template is denoted
(n), where n is the sample number. Thus,
 | (1) |
t, where
t is the digitization interval (1 ms). For the purpose of
matching all other beats to the template, the algorithm ignores the
actual QRS complex and uses only the ST segment and T wave. Thus, only
the region of the template from
n=Tk+n
to
n=n1 is subsequently used, where
n represents a preset blanking period
of 50 ms.
(4) For each beat, an error function 
i (
)
is defined:
 | (2) |
is the time-stretching factor.
i () is thus the sum of squared
differences between the template T wave and the stretched or compressed
version of the T wave for beat i.
(5) A progressive search is performed to find the value of that
minimizes i() for that beat. This best
value of is denoted 
i and is
generally between 0.9 and 1.1. The search proceeds until the search
step size for is <0.0001.
(6) The QT interval for the ith beat is taken as
 | (3) |
t is the duration of
the template QT interval.
The algorithm thus finds the QT interval for each beat such that
the T-wave shape best matches the template T wave under the
time-stretch model. If the operator chooses the end point of the
template T wave well before or well after the true end of the T-wave,
all QT interval values computed will be biased proportionately low or
high, respectively, but the beat-to-beat variability in computed QT
intervals will be relatively unaffected. Furthermore, since much of the
repolarization lability may reside in the latter portion of the T wave,
or in the U wave if present, we include in the template all
deflections that may relate to repolarization. U waves do not have a
disproportionate effect on the QT interval determination because they
are generally of low amplitude and therefore have less influence than
the T wave on the sum of squared differences (in Equation 2).
The algorithm is demonstrated graphically in Fig 1. The top panel shows the
operator-selected template QT interval with the region used to
calculate the error function highlighted. A subsequent beat in the
analysis is shown in the next panel, with several
time-compressed versions of its T wave superimposed (dashed lines). The
third panel shows the rather large area of difference between the
template T wave and the uncompressed version of the index beat, while
the bottom panel shows the close match between the template T wave and
the optimally compressed version of this beat. The compression ratio,
, which minimizes the difference between the template and the
index beat in this case is 1.0984. The QT interval for this beat is
thus taken as 1.0984 times the template QT interval.
|
Time Series Analysis
An evenly sampled heart rate time series was constructed
from the sequence of RR intervals as described
previously,17 using a sampling frequency of 4 samples/s.
The QT interval series was similarly resampled. Large abrupt
deflections in the resampled instantaneous heart rate and QT interval
series resulting from ectopic beats were eliminated with a linear
spline approach.18 Linear trends found in the heart rate
and QT interval series over each 256-second epoch were removed by
subtraction of the best-fit line. The heart rate mean
(HRm) and variance (HRv)
and QT interval mean (QTm) and variance
(QTv) were computed from the respective time
series for each 256-second epoch. A normalized QT variability index
(QTVI) was then derived for each epoch according to the equation:
 | (4) |
Power spectra of the heart rate and QT interval time series and the
cross spectrum between the two processes were computed from 1024 point
(256 seconds) segments with the Blackman-Tukey
method.19 20 The coherence function 
(f) was
then computed according to the relation
 | (5) |
(f)
over the frequency band from 0 to 0.2 Hz.
QT Dispersion
Spatial variation in repolarization was assessed in each patient
by measurement of the QT dispersion (QT) from the 12-lead
ECG.12 22 QT was taken as the difference
between maximum and minimum QT interval measured manually among the 12
standard surface ECG leads. No correction was applied for heart rate or
the number of usable leads, although the QT measurement
obtained was excluded from further analysis if fewer than 6
leads had discernible T waves.
Statistical Analysis
All data are expressed as mean±SD. An unpaired t
test was used to compare variables between groups. ANOVA was used
to test for group effect when patients were subgrouped by NYHA class.
Post hoc subgroup comparisons were made with unpaired t
tests with Bonferroni correction. Correlation between continuous
variables was tested by linear regression. Statistical significance
for all tests was accepted at the P<.05 level.
|
Results |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
Temporal Variability
Heart rate and QT variability during a 256-second epoch in a normal subject are shown in Fig 2a
. The heart rate exhibits
substantial beat-to-beat variability, which is mirrored in the
instantaneous QT interval; that is, when heart rate rises QT falls and
vice versa. Heart rate and QT interval series from a DCM patient are
shown in Fig 2b. In this case, not surprisingly, heart rate variability
is small. However, in sharp contrast to the findings in the normal
subject, in the DCM patient the QT interval varies widely and
erratically, without any discernible relation with instantaneous heart
rate.
|
Summary data on heart rate and QT interval means and variances,
comparing DCM patients with control subjects, are shown in Fig 3 and
tabulated in Table 2.HRm was significantly higher among DCM patients
than control subjects (P<.0001). QTm
was slightly greater in control subjects than in DCM patients
(P=.04). However, QTm for each epoch
was dependent on the operator's choice for T-wave terminus, which was
somewhat subjective as described above. QTv was
higher in DCM patients compared with control subjects
(P<.0001). This excess QT interval variability appeared
despite lower HRv in DCM patients than in
control subjects (P=.01).
|
|
The QTVI was greater in DCM patients than in control subjects, with a
high degree of significance
(P<10-12), as shown in Fig 4. Thus, normalizing the
absolute QT interval variability by the degree of heart rate
variability that was present accentuated the excess repolarization
lability found in DCM patients compared with control subjects. There
were no differences in HRm,
HRv, QTm,
QTv, or QTVI between men and women in the entire
study population, control subjects, or DCM patients. Group differences
in these parameters between control subjects and DCM
patients, therefore, cannot be explained on the basis of sex
distribution differences.
|
In an effort to stratify DCM patients according to severity of disease,
we examined the relation between QTVI and ejection fraction among DCM
patients (Fig 5) but found no correlation
(P=.4). Patients
were then subgrouped according to NYHA functional class (Fig 6). There was a significant
group effect (P<.01) with this stratification. Post hoc
analysis demonstrated that the QTVI in class I patients was not
different from that in control subjects. The QTVIs for patients in
classes II, III, and IV were significantly different from control
levels and increased monotonically but were not significantly different
from each other. Thus most of the overlap in QTVI between DCM patients
and control subjects is attributable to those patients in NYHA class I
(without functional impairment).
|
|
The effect of disease origin on the QTVI is shown in Fig 7. In this graph, patients
with nonischemic DCM are compared against patients with
ischemic cardiomyopathy.
Nonischemic DCM patients were younger than those with
ischemic DCM (49.2±14.0 versus 64.8±9.4 years,
P<.0001), and nonischemics had lower NYHA class
(2.3±0.8 versus 2.9±0.9, P<.01) despite somewhat lower
ejection fraction (21.8±9.0% versus 26.6±10.7%, P=.03)
than their ischemic counterparts. However, no difference was
observed in the QTVI between the two subgroups (ischemic,
-0.44±0.74 versus nonischemic, -0.41±0.67;
P=.9).
|
Coherence
The heart rate and QT interval series obtained in a control
subject (shown in Fig 2a) were subjected to Fourier analysis to
yield the power spectra shown in Fig 8a. The heart rate spectrum
exhibits two peaks, one centered at 0.02 Hz and the other at the
respiratory frequency of 0.1 Hz, with significant power extending to
0.2 Hz. The QT interval spectrum is similar to the heart rate spectrum.
This suggests that variability in the two time series has a similar
distribution of power density in the frequency domain. This is not
unexpected, since fluctuations in the two waveforms observed in the
time domain mirror each other closely. The coherence spectrum is also
displayed in Fig 8a. Over most of the frequency band from 0 to 0.2 Hz,
the coherence approaches unity, indicating strong linear coupling
between heart rate and QT interval fluctuations. Beyond 0.2 Hz, there
is little power in either heart rate or QT interval variability, so
estimates of coherence are not meaningful in this region. The mean
coherence in the band from 0 to 0.2 Hz in this example is 0.83.
|
Power and coherence spectra for the heart rate and QT interval series
obtained in a DCM patient (Fig 2b) are shown in Fig 8b. In this case,
virtually all the heart rate variability is confined to a single peak
below 0.1 Hz. QT interval variability, on the other hand, is
distributed over a broad frequency band from 0 to roughly 0.3 Hz. The
coherence is low at almost all frequencies, particularly in the band in
which the coherence estimates are most reliable, from 0 to 0.2 Hz. The
mean coherence in this band for this patient is 0.17. Note that the
coherence remains low even at frequencies at which there is substantial
power density in both heart rate and QT interval variability, for
example, 0.05 Hz. This shows that fluctuations in QT interval occur
without any linear relation to those in heart rate.
Group distributions for mean coherence are shown in Fig 9 and
summarized in Table 2. While
there was considerable overlap in this parameter between
DCM patients and control subjects, it was lower in DCM patients, with a
high degree of significance (P<.0001). Thus, a coupling
between heart rate and QT interval variations exists in control
subjects and is reduced in patients with DCM.
|
QT Dispersion
The QT dispersion, QT, was determined from the
12-lead surface ECG in each patient, as described above.
QT was not significantly different between DCM patients
and control subjects (Table 2). No significant correlation was found
between QTVI and QT (P=.4).
|
Discussion |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
Effects of DCM on Heart Rate and QT Interval Variability
We found that patients with DCM had a higher mean heart rate and lower heart rate variability compared with control subjects. These data are consistent with the findings of prior studies18 23 24 and probably reflect withdrawal of parasympathetic tone accompanying heart failure. DCM patients in our study also had a slightly shorter mean QT interval than control subjects, although this difference barely met statistical significance and may have been secondary to the increased heart rate among these patients.
The major finding of this study is that patients with DCM demonstrated
an increase in QT interval variability. In control subjects, QT
interval fluctuations mirrored those in heart rate and became greater
in magnitude when heart rate fluctuations grew larger. The absolute QT
interval variance (QTv) was thus sometimes large
enough in normal subjects to be comparable to that observed in DCM
patients. However, when the QT interval variance was normalized by the
heart rate variance (HRv), as was done in the
QTVI calculation (see Equation 4), a consistently low value was
found among control subjects. In contrast, in DCM patients the
combination of a large absolute QT variance and a generally small heart
rate variance led to a high (less negative) QTVI value. The QTVI is a
logarithmic index, so an increase of one unit corresponds to a 10-fold
increase in the quotient that forms the argument of the logarithm.
When DCM patients were stratified by NYHA functional class, class II patients (mild impairment) had significantly greater QTVI than control subjects, and little further increase in QTVI was observed among class III and class IV patients. This suggests that on average, most of the repolarization lability develops as DCM patients become mildly symptomatic, with relatively less change as patients further decompensate. To the extent that altered control of repolarization may underlie the development of malignant ventricular arrhythmias, these data are consistent with the findings of Gradman et al25 that sudden death is just as prevalent among minimally symptomatic patients with congestive heart failure as it is among those with greater impairment. The fact that QTVI correlated with functional class but not with ejection fraction suggests that the neurohumoral response to ventricular dysfunction may be more important than the degree of dysfunction in the development of labile repolarization.
Our data also show that DCM leads to repolarization lability regardless of whether ischemic or nonischemic mechanisms underlie the cardiomyopathy. Prolongation of the action potential and abnormalities in calcium and potassium currents have been demonstrated in cells isolated from failing human hearts of ischemic and nonischemic origin.9 10 26 27 In particular, Beuckelmann et al26 have shown that the inward rectifier (IK1) and transient outward (Ito) potassium currents, both important in the repolarization process, are significantly reduced in both ischemic and nonischemic myopathic heart cells. It is unknown, however, whether there are abnormal beat-to-beat fluctuations in these or other ionic currents in such cells.
Heart Rate–QT Interval Coherence
In control subjects, heart rate and QT interval fluctuations had
similar frequency content and moderately high coherence. This suggests
either that the mechanisms driving heart rate changes also modulate QT
interval or that the heart rate fluctuations themselves secondarily
drive QT interval oscillations. The latter mechanism
relates to the well-known phenomenon of electrical restitution, that
is, the dependence of action potential duration on the
diastolic interval of the preceding beat,28 29 30 31
which has been shown to govern QT interval changes in the normal human
ventricle.32 33 On the other hand, mechanisms that drive
both heart rate and QT interval fluctuations primarily relate to the
autonomic nervous system. The effects of sympathetic and vagal
modulation on normal heart rate variability have been well
characterized,20 34 35 as has the marked reduction in
autonomically mediated heart rate variability associated with
congestive heart failure.18 Autonomic influences on
ventricular repolarization have also been studied and
recently reviewed.36 Given the multiple mechanisms
modulating repolarization that generally occur in association with
heart rate changes, it is not surprising that heart rate and QT
interval fluctuations are coherent among normal individuals, in whom
these mechanisms are intact.
Compared with the control subjects, DCM patients had significantly lower coherence between heart rate and QT interval. Examination of individual instantaneous heart rate and QT interval tracings and corresponding power spectra consistently demonstrated the presence of broad-band QT interval fluctuations in the face of nearly constant or slowly changing heart rates in these patients. These data suggest there is a loss in the normal coupling between heart rate and QT interval in the setting of DCM. If QT interval fluctuations reflect beat-to-beat changes in the cellular action potential duration of at least some of the ventricular myocardium, then these cells apparently exhibit fluctuating action potential durations despite little if any change in RR interval. Electrical restitution must therefore be altered in these cells since there is no longer a unique action potential duration for a given diastolic interval.
Relation Between QT Variability and QT Dispersion
Recently, spatial QT dispersion has been tested as a predictor of
arrhythmic risk in patients with heart failure.12 13 14 37 38
However, methodology to quantify QT dispersion has not been
standardized, and differences in technique can lead to disparate
results.39 40 Some studies concluded that increased QT
dispersion correlated with increased risk of
arrhythmias12 13 14 while others did
not.37 38 Furthermore, QT dispersion was increased in DCM
patients compared with control subjects in one report14
but did not correlate with the presence or severity of disease in
others.37 38
In our hands, QT dispersion was not different between DCM patients and control subjects. We also found no correlation between QTVI and QT dispersion. Thus, the mechanisms responsible for increases in spatial QT dispersion and temporal QT variability are not the same. These two measurements may provide independent pieces of information regarding ventricular electrical stability.
Relation to Prior Work on Repolarization Variability
While numerous studies have examined the
physiological and prognostic value of heart rate
variability, there is a paucity of literature regarding beat-to-beat QT
interval variability. Presumably, this is due in part to the technical
difficulties in developing a robust automated scheme for QT interval
determination. In assessing QT interval variability, determination of
absolute QT duration is relatively unimportant, but the method must be
sensitive to subtle changes in QT interval from one beat to the next
and relatively insensitive to signal noise.
Previously described techniques for automated beat-to-beat QT interval assessment are largely based on criteria to detect T-wave terminus. These methods search for a fall in either the ECG waveform itself41 42 43 or the differentiated ECG signal.43 44 Under these strategies, the QT measurement is highly dependent on waveform morphology near the end of the T wave, when the signal is low in amplitude and slope. Erroneous measurements are likely in the setting of signal artifacts or noise, even if the noise is low in amplitude.
Several recent studies have examined beat-to-beat fluctuations in ventricular repolarization by automated analysis of the interval from peak of the R wave to peak of the T wave (RT interval).45 46 47 Identifying the T-wave peak can be as problematic as finding the T-wave terminus. Since the T wave is a low-frequency event, locating the time of its peak is easily corrupted by artifacts that often cannot be distinguished from the true waveform. While this may have a relatively small effect on absolute RT interval determination, it may largely obscure subtle beat-to-beat changes in this measurement. Furthermore, this approach ignores fluctuations in repolarization that principally influence the latter part of the T wave or that give rise to U waves. These features may be of lesser importance in studying repolarization variability in normal subjects but are likely to be of increasing significance when considering individuals with structural heart disease or metabolic abnormalities in whom afterdepolarizations are common.7 48
The template-matching strategy presented in this report takes the entire T wave into consideration and thus tracks beat-to-beat timing shifts in T-wave peak and terminus without requiring any one point of the T wave to serve as a fiducial marker. In addition, timing fluctuations in U waves, if present, can be assessed by inclusion of the U wave in the template.
Diurnal variation in QT interval has been observed for some time.49 50 However, beat-to-beat fluctuations in repolarization duration have gone largely unnoticed. Merri et al46 studied RT variability and the coherence between heart rate and RT interval in 10 young, healthy subjects. The amplitude of heart rate and RT interval fluctuations they found were similar to those in heart rate and QT interval that we observed in our control population. In addition, power spectra that they obtained of the heart rate and RT interval traces showed similar frequency components, and there was generally high coherence between these waveforms. Sarma et al47 studied RT variability in 12 patients with stable angina. They specifically excluded patients with heart failure or conduction defects. Nonetheless, in this patient group, RT interval fluctuations were present over a broader frequency band than were heart rate fluctuations, and the coherence was poor except at very low frequencies (near 0.05 Hz). These studies reconcile with ours and suggest that heart disease of diverse origins, perhaps even if mild, leads to a loss of the normally high coherence between heart rate and repolarization duration.
Repolarization variability has also been examined in terms of T-wave alternans, particularly as a marker of ischemia-induced susceptibility to arrhythmias.51 52 53 54 Work in this area has concentrated on beat-to-beat changes in T-wave energy or morphology, not duration, and only at the alternans frequency (half the heart rate). Nonetheless, it is conceivable that the same destabilizing mechanisms that lead to T-wave alternans may be responsible for the increased QT variability that we observed in DCM patients. We did not attempt to measure subtle T-wave alternans in these patients, and none had visually obvious alternans. However, T-wave alternans may not become manifest without atrial pacing or some other chronotropic challenge.54
Clinical Implications
Patients with DCM may present with various
ventricular tachyarrhythmias, including
monomorphic VT, polymorphic VT, and ventricular
fibrillation. While monomorphic and polymorphic VT often occur in
the same patient, the mechanisms responsible for these
arrhythmias probably differ. Monomorphic VT is predominantly
due to reentry occurring in the presence of a zone of sufficiently
slowed conduction to enable an excitable gap to develop.55
A reentrant substrate can be demonstrated by induction of monomorphic
VT with programmed electrical stimulation.56
The mechanistic causes of polymorphic VT and ventricular fibrillation are less clear. Abnormalities in cellular repolarization, including triggered activity and spatial dispersion of refractoriness, have been implicated in these arrhythmias.7 48 57 The potential importance of temporal repolarization lability, such as we found among DCM patients, in the genesis of these arrhythmias remains unexplored. Conceivably, spatial and temporal heterogeneity in repolarization may each contribute to render the substrate arrhythmogenic. Patients included in the present study are being followed longitudinally to assess the clinical value of QT dispersion and QT variability measurements in predicting arrhythmia-free survival.
Study Limitations
Several important factors must be considered in interpreting our
results. First, many of the DCM patients were taking a variety of
medications for their heart failure. While patients taking class I or
class III antiarrhythmic agents were excluded from the study, some of
the medications taken by the patients could have influenced
ventricular repolarization. Even if the pharmacological
effect on mean QT interval was subtle, the influence of these drugs on
QT interval variability is unknown. Many of the patients with an
ischemic cardiomyopathy were taking
ß-adrenergic–blocking agents, which could have influenced the
QTVI measurement through their effect on mean heart rate and on heart
rate variability.
The second potentially confounding factor is the presence of bundle branch blocks and intraventricular conduction defects in a sizable proportion of the DCM patients. Altered depolarization is often associated with altered repolarization, and we made no effort to exclude patients with conduction defects from the study. However, at this point we see no reason to expect a conduction defect to either increase or decrease the degree of QT interval variability that would otherwise be present. This represents an important issue to be addressed in future research.
A third issue that remains to be resolved is the reproducibility of the QT variance and QTVI measurements. Data presented in this study are based on two 256-second epochs obtained in a single encounter with each patient. It is possible that repolarization lability itself varies over the course of the day or from one day to another. While these effects may render QT variability measurements in an individual less reliable, the finding that DCM patients as a group have a higher QTVI than control subjects cannot be explained on this basis.
Finally, we wish to point out that it is premature to consider measurements of QT interval variability, or the QTVI in particular, as a stratifier of clinical arrhythmia risk. At the present time, however, the presence of enhanced QT variability in the setting of DCM represents a previously unrecognized phenomenon. An understanding of its origin may lead to greater insights into the mechanisms that underlie malignant ventricular arrhythmias in this patient population.
|
Acknowledgments |
|---|
Dr Berger is the recipient of a FIRST Award (R29-HL-54584) from the National Heart, Lung, and Blood Institute and is a Solo Cup Clinician Scientist. This work was also supported by grant P50-HL-52307 of the National Heart, Lung, and Blood Institute. The authors wish to thank Renee Ferguson for her expert technical assistance in the data collection and analysis.
Received January 9, 1997; revision received March 6, 1997; accepted March 30, 1997.
|
References |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
1. CONSENSUS Trial Study Group. Effects of enalapril on mortality in severe congestive heart failure: results of the Cooperative North Scandinavian Enalapril Survival Study (CONSENSUS). N Engl J Med. 1987;316:1429-1435.[Abstract]
2. Cohn JN, Johnson G, Ziesche S, Cobb F, Francis G, Tristani F, Smith R, Dunkman WB, Loeb H, Wong M, Bhat G, Goldman S, Fletcher RD, Doherty J, Hughes V, Carson P, Cintron G, Shabetai R, Haakenson C. A comparison of enalapril with hydralazine-isosorbide dinitrate in treatment of chronic congestive heart failure: V-HeFT II. N Engl J Med. 1991;325:303-310.[Abstract]
3. Podrid PJ, Fogel RI, Fuchs TT. Ventricular arrhythmia in congestive heart failure. Am J Cardiol. 1992;69:82G-96G.[Medline] [Order article via Infotrieve]
4. Anderson KP, Freedman RA, Mason JW. Sudden death in idiopathic dilated cardiomyopathy. Ann Intern Med. 1987;107:104-106.
5.
Packer M. Sudden unexpected death in patients
with congestive heart failure: a second frontier.
Circulation. 1985;72:681-685.
6. Raitt MH, Dolack GL, Kudenchuk PJ, Poole JE, Jones GK, Bardy GH. What is the risk of primary ventricular fibrillation in patients with a history of only monomorphic ventricular tachycardia? Circulation. 1994;90(suppl I):I-454. Abstract.
7.
Tomaselli GF, Beuckelmann DJ, Calkins HG, Berger RD,
Kessler PD, Lawrence JH, Kass D, Feldman AM, Marban E. Sudden
cardiac death in heart failure: the role of abnormal
repolarization. Circulation. 1994;90:2534-2539.
8.
Aronson RS. Characteristics of action
potentials of hypertrophied myocardium from rats with renal
hypertension. Circ Res. 1980;47:443-454.
9.
Gwathmey JK, Copelas L, MacKinnon R, Schoen FJ,
Feldman MD, Grossman W, Morgan JP. Abnormal intracellular
calcium handling in myocardium from patients with end-stage
heart failure. Circ Res. 1987;61:70-76.
10.
Beuckelmann DJ, Nabauer M, Erdmann E.
Intracellular calcium handling in isolated ventricular
myocytes from patients with terminal heart failure.
Circulation. 1992;85:1046-1055.
11. Dinerman JL, Berger RD, Haigney MCP, Lawrence JH, Tomaselli GF, Calkins H. Dispersion of ventricular activation and recovery in patients with idiopathic dilated cardiomyopathy. Am J Cardiol. 1997;79:970–974.[Medline] [Order article via Infotrieve]
12. Barr CS, Naas A, Freeman M, Lang CC, Struthers AD. QT dispersion and sudden unexpected death in chronic heart failure. Lancet. 1994;343:327-329.[Medline] [Order article via Infotrieve]
13.
Pye M, Quinn AC, Cobbe SM. QT interval
dispersion: a non-invasive marker of susceptibility to
arrhythmia in patients with sustained ventricular
arrhythmias? Br Heart J. 1994;71:511-514.
14. Grimm W, Steder U, Menz V, Hoffmann J, Maisch B. QT dispersion and arrhythmic events in idiopathic dilated cardiomyopathy. Am J Cardiol. 1996;78:458-461.[Medline] [Order article via Infotrieve]
15.
Folland ED, Parisi AF, Moynihan PF. Assessment
of left ventricular ejection fraction and volumes by
real-time, two dimensional echocardiography: a
comparison of cineographic and radionuclide techniques.
Circulation. 1979;60:760–766.
16. Shock NW, Greulich RC, Andrews D, Arenberg D, Costa PT, Lakatta EG, Tobin JD. Normal Human Aging: The Baltimore Longitudinal Study on Aging. Bethesda, Md: NIH Publication No. 84-2450, 45-57; 1984.
17. Berger RD, Akselrod S, Gordon D, Cohen RJ. An efficient algorithm for spectral analysis of heart rate variability. IEEE Trans Biomed Eng BME. 1986;33:900-904.
18. Saul JP, Arai Y, Berger RD, Lilly LS, Colucci WS, Cohen RJ. Assessment of autonomic regulation in chronic congestive heart failure by heart rate spectral analysis. Am J Cardiol. 1988;61:1292-1299.[Medline] [Order article via Infotrieve]
19. Kay SM, Marple SL. Spectrum analysis: a modern perspective. Proc IEEE. 1981;69:1380-1419.
20. Berger RD, Saul JP, Cohen RJ. Transfer function analysis of autonomic regulation, I: the canine atrial rate response. Am J Physiol. 1989;25:H142-H152.
21. Jenkins GM, Watts DG. Spectral Analysis and Its Applications. Oakland, Calif: Holden-Day; 1968.
22.
Day CP, McComb JM, Campbell RWF. QT dispersion:
an indication of arrhythmia risk in patients with long QT
intervals. Br Heart J. 1990;63:342-344.
23. Casolo G, Bali E, Taddei T, Amuhasi J, Gori C. Decreased spontaneous heart rate variability in congestive heart failure. Am J Cardiol. 1989;64:1162-1167.[Medline] [Order article via Infotrieve]
24. Woo MA, Stevenson WG, Moser DK, Trelease RB, Harper RM. Patterns of beat-to-beat heart rate variability in advanced heart failure. Am Heart J. 1992;123:704-710.[Medline] [Order article via Infotrieve]
25. Gradman A, Deedwania P, Cody R, Massie B, Packer M, Pitt B, Goldstein S, for the Captopril-Digoxin Study Group, Predictors of total mortality and sudden death in mild to moderate heart failure. J Am Coll Cardiol. 1989;14:564-570.[Abstract]
26.
Beuckelmann DJ, Nabauer M, Erdmann E.
Alterations of K+ currents in isolated human ventricular
myocytes from patients with terminal heart failure. Circ
Res. 1993;73:379-385.
27.
Nabauer M, Beuckelmann DJ, Erdmann E.
Characteristics of transient outward current in human
ventricular myocytes from patients with terminal heart
failure. Circ Res. 1993;73:386-394.
28.
Gibbs CL, Johnson EA. Effect of changes in
frequency of stimulation upon rabbit ventricular action
potential. Circ Res. 1961;9:165-170.
29.
Edmands RE, Greenspan K, Fisch C. Effect of
cycle length alteration upon the configuration of the canine
ventricular action potential. Circ Res. 1966;19:602-610.
30. Elharrar V, Atarashi H, Surawicz B. Cycle length-dependent action potential duration in canine cardiac Purkinje fibers. Am J Physiol. 1984;247:H936-H945.
31. 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 frequencies. J Clin Invest. 1988;82:972-979.
32.
Attwell D, Cohen I, Eisner DA. The effects of
heart rate on the action potential of guinea-pig and human
ventricular muscle. J Physiol. 1981;313:439-461.
33. Arnold L, Page J, Attwell D, Cannell M, Eisner DA. The dependence on heart rate of the human ventricular action potential duration. Cardiovasc Res. 1982;16:547-551.[Medline] [Order article via Infotrieve]
34.
Akselrod S, Gordon D, Ubel FA, Shannon DC, Barger AC,
Cohen RJ. Power spectrum analysis of heart rate
fluctuations: a quantitative probe of beat-to-beat
cardiovascular control. Science. 1981;213:220-222.
35.
Pomeranz B, MaCaulay RJB, Caudill MA, Kutz I, Adam D,
Gordon D, Kilborn KM, Barger AC, Shannon DC, Cohen RJ, Benson H.
Assessment of autonomic function in humans by heart rate spectral
analysis. Am J Physiol. 1985;248:H151-H153.
36. Rosen MR, Jeck CD, Steinberg SF. Autonomic modulation of cellular repolarization and of the electrocardiographic QT interval. J Cardiovasc Electrophysiol. 1992;3:487-499.
37.
Davey PP, Bateman J, Mulligan IP, Forfar C, Barlow C,
Hart G. QT interval dispersion in chronic heart failure and left
ventricular hypertrophy: relation to autonomic
nervous system and Holter tape abnormalities. Br
Heart J. 1994;71:268-273.
38.
Fei L, Goldman JH, Prasad K, Keeling PJ, Reardon K,
Camm AJ, McKenna WJ. QT dispersion and RR variations on 12-lead
ECGs in patients with congestive heart failure secondary to idiopathic
dilated cardiomyopathy. Eur
Heart J. 1996;17:258-263.
39. Statters DJ, Malik M, Ward DE, Camm AJ. QT dispersion: problems of methodology and clinical significance. J Cardiovasc Electrophysiol. 1994;5:672-685.[Medline] [Order article via Infotrieve]
40. Surawicz B. Will QT dispersion play a role in clinical decision-making? J Cardiovasc Electrophysiol. 1996;7:777-784.[Medline] [Order article via Infotrieve]
41. Algra A, Le Brun H, Zeelenberg C. An algorithm for computer measurement of QT intervals in the 24 hour ECG. Comput Cardiol. 1987;13:117-119.
42. Critelli G, Marciano F, Mazzarella M, Migaux ML. QT interval measurements of long-term ECG recordings: application of an automatic Holter analysis system. Comput Cardiol. 1982;8:481-484.
43. Pisani E, Pellegrini F, Ansuini G, Di Noto G, Rimatori C, Russo P. Performance evaluation of algorithms for QT interval measurements in ambulatory ECG recordings. Comput Cardiol. 1985;11:459-462.
44. Laguna P, Thakor NV, Caminal P, Jane R, Yoon HR. New algorithm for QT interval analysis in 24-hour Holter ECG: performance and applications. Med Biol Eng Comput. 1990;28:67-73.[Medline] [Order article via Infotrieve]
45.
Merri M, Moss AJ, Benhorin J, Locati EH, Alberti M,
Badilini F. Relation between ventricular
repolarization duration and cardiac cycle length during 24-hour Holter
recordings: findings in normal patients and patients with long
QT syndrome. Circulation. 1992;85:1816-1821.
46. Merri M, Alberti M, Moss AJ. Dynamic analysis of ventricular repolarization duration from 24-hour Holter recordings. IEEE Trans Biomed Eng. 1993;40:1219-1225.[Medline] [Order article via Infotrieve]
47. Sarma JSM, Singh N, Schoenbaum MP, Venkataraman K, Singh BN. Circadian and power spectral changes of RR and QT intervals during treatment of patients with angina pectoris with nadolol providing evidence for differential autonomic modulation of heart rate and ventricular repolarization. Am J Cardiol. 1994;74:131-136.[Medline] [Order article via Infotrieve]
48. Jackman WM, Szabo B, Friday KJ, Margolis PD, Moulton K, Wang X, Patterson E, Lazzara R. Ventricular tachyarrhythmias related to early afterdepolarizations and triggered firing: relationship to QT interval prolongation and potential therapeutic role for calcium channel blocking agents. J Cardiovasc Electrophysiol. 1990;1:170-195.
49. 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.[Medline] [Order article via Infotrieve]
50.
Bexton RS, Vallin HO, Camm AJ. Diurnal variation
of the QT interval: influence of the autonomic nerve system.
Br Heart J. 1986;55:253-258.
51. Adam DR, Smith JM, Akselrod S, Nyberg S, Powell AO, Cohen RJ. Fluctuations in T-wave morphology and susceptibility to ventricular fibrillation. J Electrocardiol. 1984;17:209-218.[Medline] [Order article via Infotrieve]
52.
Smith JM, Clancy EA, Valeri CR, Ruskin JN, Cohen
RJ. Electrical alternans and cardiac electrical
instability. Circulation. 1988;77:110-121.
53.
Nearing BD, Huang AH, Verrier RL. Dynamic
tracking of cardiac vulnerability by complex demodulation of the T
wave. Science. 1991;252:437-440.
54.
Rosenbaum DS, Jackson LE, Smith JN, Garan H, Ruskin JN,
Cohen RJ. Electrical alternans and vulnerability to
ventricular arrhythmias. N Engl
J Med. 1994;330:235-241.
55. Josephson ME, Almendral JM, Buxton AE, Marchlinski FE. Mechanisms of ventricular tachycardia. Circulation. 1987;75(suppl III):III-41-III-47.
56.
Almendral JM, Stamato NJ, Rosenthal ME, Marchlinski FE,
Miller JM, Josephson ME. Resetting response patterns during
sustained ventricular tachycardia: relationship
to the excitable gap. Circulation. 1986;74:722-730.
57.
Kuo C, Munakata K, Reddy CP, Surawicz B.
Characteristics and possible mechanisms of ventricular
arrhythmia dependent on the dispersion of action potential
durations. Circulation. 1983;67:1356-1367.
This article has been cited by other articles:
 |
|
 |
|
  M. Koschke, M. K. Boettger, S. Schulz, S. Berger, J. Terhaar, A. Voss, V. K. Yeragani, and K.-J. Bar Autonomy of Autonomic Dysfunction in Major Depression Psychosom Med, October 1, 2009; 71(8): 852 - 860. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 G. Piccirillo, D. Magri, M. Ogawa, J. Song, V. J. Chong, S. Han, B. Joung, E.-K. Choi, S. Hwang, L. S. Chen, et al. Autonomic Nervous System Activity Measured Directly and QT Interval Variability in Normal and Pacing-Induced Tachycardia Heart Failure Dogs. J. Am. Coll. Cardiol., August 25, 2009; 54(9): 840 - 850. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
R. D. Berger QT Interval Variability Is It a Measure of Autonomic Activity? J. Am. Coll. Cardiol., August 25, 2009; 54(9): 851 - 852. [Full Text] [PDF]
|
|
|
|
 |
|
 L. G. Tereshchenko, B. J. Fetics, P. P. Domitrovich, B. D. Lindsay, and R. D. Berger Prediction of Ventricular Tachyarrhythmias by Intracardiac Repolarization Variability Analysis Circ Arrhythm Electrophysiol, June 1, 2009; 2(3): 276 - 284. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 J. M. Samet, A. Rappold, D. Graff, W. E. Cascio, J. H. Berntsen, Y.-C. T. Huang, M. Herbst, M. Bassett, T. Montilla, M. J. Hazucha, et al. Concentrated Ambient Ultrafine Particle Exposure Induces Cardiac Changes in Young Healthy Volunteers Am. J. Respir. Crit. Care Med., June 1, 2009; 179(11): 1034 - 1042. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 K.-J. Bar, S. Berger, M. Metzner, M. K. Boettger, S. Schulz, C. T. Ramachandraiah, J. Terhaar, A. Voss, V. K. Yeragani, and H. Sauer Autonomic Dysfunction in Unaffected First-Degree Relatives of Patients Suffering From Schizophrenia Schizophr Bull, April 14, 2009; (2009) sbp024v1. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 E. Pueyo, J. P. Martinez, and P. Laguna Cardiac repolarization analysis using the surface electrocardiogram Phil Trans R Soc A, January 28, 2009; 367(1887): 213 - 233. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. J. Goldberger, M. E. Cain, S. H. Hohnloser, A. H. Kadish, B. P. Knight, M. S. Lauer, B. J. Maron, R. L. Page, R. S. Passman, D. Siscovick, et al. American Heart Association/American College of Cardiology Foundation/Heart Rhythm Society Scientific Statement on Noninvasive Risk Stratification Techniques for Identifying Patients at Risk for Sudden Cardiac Death: A Scientific Statement From the American Heart Association Council on Clinical Cardiology Committee on Electrocardiography and Arrhythmias and Council on Epidemiology and Prevention J. Am. Coll. Cardiol., September 30, 2008; 52(14): 1179 - 1199. [Full Text] [PDF]
|
|
|
|
 |
|
 J. J. Goldberger, M. E. Cain, S. H. Hohnloser, A. H. Kadish, B. P. Knight, M. S. Lauer, B. J. Maron, R. L. Page, R. S. Passman, D. Siscovick, et al. American Heart Association/American College of Cardiology Foundation/Heart Rhythm Society Scientific Statement on Noninvasive Risk Stratification Techniques for Identifying Patients at Risk for Sudden Cardiac Death: A Scientific Statement From the American Heart Association Council on Clinical Cardiology Committee on Electrocardiography and Arrhythmias and Council on Epidemiology and Prevention Circulation, September 30, 2008; 118(14): 1497 - 1518. [Full Text] [PDF]
|
|
|
|
 |
|
 M. Baumert, G. W. Lambert, T. Dawood, E. A. Lambert, M. D. Esler, M. McGrane, D. Barton, and E. Nalivaiko QT interval variability and cardiac norepinephrine spillover in patients with depression and panic disorder Am J Physiol Heart Circ Physiol, September 1, 2008; 295(3): H962 - H968. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. Malik Beat-to-beat QT variability and cardiac autonomic regulation Am J Physiol Heart Circ Physiol, September 1, 2008; 295(3): H923 - H925. [Full Text] [PDF]
|
|
|
|
 |
|
 M. Hinterseer, M. B. Thomsen, B.-M. Beckmann, A. Pfeufer, R. Schimpf, H.-E. Wichmann, G. Steinbeck, M. A. Vos, and S. Kaab Beat-to-beat variability of QT intervals is increased in patients with drug-induced long-QT syndrome: a case control pilot study Eur. Heart J., January 2, 2008; 29(2): 185 - 190. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 J.-P. Couderc, W. Zareba, S. McNitt, P. Maison-Blanche, and A. J. Moss Repolarization variability in the risk stratification of MADIT II patients Europace, September 1, 2007; 9(9): 717 - 723. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
W. Zareba Holter Electrocardiogram Parameters in Risk Stratification of Arrhythmic Events in Idiopathic Dilated Cardiomyopathy: More Studies Are Needed J. Am. Coll. Cardiol., July 17, 2007; 50(3): 232 - 233. [Full Text] [PDF]
|
|
|
|
|
|
G. Piccirillo, D. Magri, S. Matera, M. Magnanti, A. Torrini, E. Pasquazzi, E. Schifano, S. Velitti, V. Marigliano, R. Quaglione, et al. QT variability strongly predicts sudden cardiac death in asymptomatic subjects with mild or moderate left ventricular systolic dysfunction: a prospective study Eur. Heart J., June 1, 2007; 28(11): 1344 - 1350. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. B. Thomsen, P. G.A. Volders, J. D.M. Beekman, J. Matz, and M. A. Vos Beat-to-Beat Variability of Repolarization Determines Proarrhythmic Outcome in Dogs Susceptible to Drug-Induced Torsades de Pointes J. Am. Coll. Cardiol., September 19, 2006; 48(6): 1268 - 1276. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 A. A. Fossa, T. Wisialowski, A. Magnano, E. Wolfgang, R. Winslow, W. Gorczyca, K. Crimin, and D. L. Raunig Dynamic Beat-to-Beat Modeling of the QT-RR Interval Relationship: Analysis of QT Prolongation during Alterations of Autonomic State versus Human Ether a-go-go-Related Gene Inhibition J. Pharmacol. Exp. Ther., January 1, 2005; 312(1): 1 - 11. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. B. Thomsen, S. C. Verduyn, M. Stengl, J. D.M. Beekman, G. de Pater, J. van Opstal, P. G.A. Volders, and M. A. Vos Increased Short-Term Variability of Repolarization Predicts d-Sotalol-Induced Torsades de Pointes in Dogs Circulation, October 19, 2004; 110(16): 2453 - 2459. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. C. Haigney, W. Zareba, P. J. Gentlesk, R. E. Goldstein, M. Illovsky, S. McNitt, M. L. Andrews, A. J. Moss, and the MADIT II Investigators QT interval variability and spontaneous ventricular tachycardia or fibrillation in the Multicenter Automatic Defibrillator Implantation Trial (MADIT) II patients J. Am. Coll. Cardiol., October 6, 2004; 44(7): 1481 - 1487. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 S. Wasson, H. K. Reddy, and M. L. Dohrmann Current Perspectives of Electrical Remodeling and Its Therapeutic Implications Journal of Cardiovascular Pharmacology and Therapeutics, April 1, 2004; 9(2): 129 - 144. [Abstract] [PDF]
|
|
|
|
 |
|
 W. M. van den Bergh, A. Algra, and G. J.E. Rinkel Electrocardiographic Abnormalities and Serum Magnesium in Patients With Subarachnoid Hemorrhage Stroke, March 1, 2004; 35(3): 644 - 648. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 D. M. Roden A Surprising New Arrhythmia Mechanism in Heart Failure Circ. Res., October 3, 2003; 93(7): 589 - 591. [Full Text] [PDF]
|
|
|
|
|
|
F. G. Akar and D. S. Rosenbaum Transmural Electrophysiological Heterogeneities Underlying Arrhythmogenesis in Heart Failure Circ. Res., October 3, 2003; 93(7): 638 - 645. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
B. Vrtovec, R. Delgado, A. Zewail, C. D. Thomas, B. M. Richartz, and B. Radovancevic Prolonged QTc Interval and High B-Type Natriuretic Peptide Levels Together Predict Mortality in Patients With Advanced Heart Failure Circulation, April 8, 2003; 107(13): 1764 - 1769. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
R. M. Carney, K. E. Freedland, P. K. Stein, L. L. Watkins, D. Catellier, A. S. Jaffe, and V. K. Yeragani Effects of Depression on QT Interval Variability After Myocardial Infarction Psychosom Med, March 1, 2003; 65(2): 177 - 180. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 J. Nemec, J. B. Hejlik, W.-K. Shen, and M. J. Ackerman Catecholamine-Induced T-Wave Lability in Congenital Long QT Syndrome: A Novel Phenomenon Associated With Syncope and Cardiac Arrest Mayo Clin. Proc., January 1, 2003; 78(1): 40 - 50. [Abstract] [PDF]
|
|
|
|
 |
|
 M. Sosnowski, Z. Czyz, and M. Tendera Time and frequency analysis of beat-to-beat R-T interval variability in patients with ischaemic left ventricular dysfunction providing evidence for non-neural control of ventricular repolarisation Eur J Heart Fail, December 1, 2002; 4(6): 737 - 743. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
G.-R. Li, C.-P. Lau, A. Ducharme, J.-C. Tardif, and S. Nattel Transmural action potential and ionic current remodeling in ventricles of failing canine hearts Am J Physiol Heart Circ Physiol, September 1, 2002; 283(3): H1031 - H1041. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
G.-X. Yan, S. J. Rials, Y. Wu, T. Liu, X. Xu, R. A. Marinchak, and P. R. Kowey Ventricular hypertrophy amplifies transmural repolarization dispersion and induces early afterdepolarization Am J Physiol Heart Circ Physiol, November 1, 2001; 281(5): H1968 - H1975. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 S. Kaab and M. Nabauer Diversity of ion channel expression in health and disease Eur. Heart J. Suppl., September 1, 2001; 3(suppl_K): K31 - K40. [Abstract] [PDF]
|
|
|
|
|
|
L. M. Hondeghem, L. Carlsson, and G. Duker Instability and Triangulation of the Action Potential Predict Serious Proarrhythmia, but Action Potential Duration Prolongation Is Antiarrhythmic Circulation, April 17, 2001; 103(15): 2004 - 2013. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
H. Bonnemeier, F. Hartmann, U. K. H. Wiegand, F. Bode, H. A. Katus, and G. Richardt Course and prognostic implications of QT interval and QT interval variability after primary coronary angioplasty in acute myocardial infarction J. Am. Coll. Cardiol., January 1, 2001; 37(1): 44 - 50. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. Sosnowski, Z. Czyz, and M. Tendera Scatterplots of RR and RT interval variability bring evidence for diverse non-linear dynamics of heart rate and ventricular repolarization duration in coronary heart disease Europace, January 1, 2001; 3(1): 39 - 45. [Abstract] [PDF]
|
|
|
|
 |
|
 W. J. Kostis and J. C. Belina Differences in Beat-to-Beat Variability of the QT Interval Between Day and Night Angiology, November 1, 2000; 51(11): 905 - 911. [Abstract] [PDF]
|
|
|
|
|
|
J. Merot, V. Probst, M. Debailleul, U. Gerlach, N. S. Moise, H. Le Marec, and F. Charpentier Electropharmacological characterization of cardiac repolarization in German shepherd dogs with an inherited syndrome of sudden death: abnormal response to potassium channel blockers J. Am. Coll. Cardiol., September 1, 2000; 36(3): 939 - 947. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 P. G.A. Volders, M. A. Vos, B. Szabo, K. R. Sipido, S.H.M. de Groot, A. P.M. Gorgels, H. J.J. Wellens, and R. Lazzara Progress in the understanding of cardiac early afterdepolarizations and torsades de pointes: time to revise current concepts Cardiovasc Res, June 1, 2000; 46(3): 376 - 392. [Full Text] [PDF]
|
|
|
|
|
|
P. A. Doevendans Hypertrophic Cardiomyopathy : Do We Have the Algorithm for Life and Death? Circulation, March 21, 2000; 101(11): 1224 - 1226. [Full Text] [PDF]
|
|
|
|
|
|
W. L. Atiga, L. Fananapazir, D. McAreavey, H. Calkins, and R. D. Berger Temporal Repolarization Lability in Hypertrophic Cardiomyopathy Caused by {beta}-Myosin Heavy-Chain Gene Mutations Circulation, March 21, 2000; 101(11): 1237 - 1242. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
A. Bénardeau, J. Weissenburger, L. Hondeghem, and E. A. Ertel Effects of the T-Type Ca2+ Channel Blocker Mibefradil on Repolarization of Guinea Pig, Rabbit, Dog, Monkey, and Human Cardiac Tissue J. Pharmacol. Exp. Ther., February 1, 2000; 292(2): 561 - 575. [Abstract] [Full Text]
|
|
|
|
|
|
K. Adachi, Y. Ohnishi, T. Shima, K. Yamashiro, A. Takei, N. Tamura, and M. Yokoyama Determinant of microvolt-level T-wave alternans in patients with dilated cardiomyopathy J. Am. Coll. Cardiol., August 1, 1999; 34(2): 374 - 380. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
G. F. Tomaselli and E. Marban Electrophysiological remodeling in hypertrophy and heart failure Cardiovasc Res, May 1, 1999; 42(2): 270 - 283. [Full Text] [PDF]
|
|
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||