(Circulation. 1995;91:2371-2377.)
© 1995 American Heart Association, Inc.
Articles |
Long-term Temporal Patterns of Ventricular Tachyarrhythmias
From the Department of Medicine (Cardiology) (M.A.W., B.S.S., K.A.E.) and Department of Biostatistics (P.M.S.), Medical College of Virginia, McGuire Veterans Administration Medical Center (M.A.W., B.S.S., K.A.E.), Richmond; and Sentara Norfolk General Hospital (J.M.H., R.C.B.), Norfolk, Va.
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Abstract |
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 Top Abstract IntroductionMethods Results Discussion References |
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Background Technological limitations have precluded investigation of long-term temporal patterns of ventricular tachyarrhythmia recurrences. Newer implantable cardioverter-defibrillators permit such analyses by accurately recording the time and date of tachycardia detections during long-term follow-up. This study tests the hypothesis that ventricular tachycardia occurrences are randomly distributed over time in individual patients.
Methods and Results The time and date of 727 episodes of
ventricular tachyarrhythmias were recorded from the data logs of 31
patients with implantable cardioverter-defibrillators followed for a
median of 177 days (range, 7 to 782 days). All patients had three or
more ventricular tachycardia detections and no detections from causes
other than ventricular arrhythmias. In 28 of 31 patients, the
distribution of the interdetection time intervals during follow-up
differed significantly (all P<.01) from an exponential
model distribution of interdetection intervals that assumed that
detections were equally likely to occur at any time during follow-up
(random). The Kolmogorov-Smirnov goodness-of-fit test was used to
compare sample and model distributions. In each patient, the nonrandom
distributions resulted from a preponderance of interdetection time
intervals that were shorter than predicted by the random model,
resulting in a temporal clustering of arrhythmic events. The
interdetection interval was 
1 hour and 91 hours for 55% and 78%
of all intervals, respectively. When only those episodes receiving
shock or antitachycardia pacing therapy were analyzed, 25 of 29
patients still manifested nonrandom distributions (all
P<.01). When only episodes with tachycardia rates >240
beats per minute were analyzed, 11 of 13 patients manifested nonrandom
distributions (all P<.01).
Conclusions Ventricular tachycardia detections and delivered antitachycardia therapies by implantable cardioverter-defibrillators are nonrandomly distributed throughout long-term follow-up in the majority of patients. The temporal clustering of these arrhythmic events may allow preemptive antiarrhythmic therapy and should be considered in the design of therapy based on suppression of spontaneous ventricular arrhythmias to statistically derived end points.
Key Words: tachyarrhythmias • defibrillation
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Introduction |
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TopAbstractIntroductionMethods Results Discussion References |
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Ventricular tachyarrhythmias remain the most common cause of cardiovascular death in most industrialized countries; however, little is known about the long-term temporal patterns of arrhythmia occurrence.1 2 3 Methodological shortcomings have limited previous studies to the use of telemetric or ambulatory ECG monitoring over observational periods of only hours to days.4 5 6 7 8 Late-generation implantable cardioverter-defibrillators (ICDs) now have the ability to accurately record the time and date of each tachycardia detection over years of follow-up, thus providing unique insights into the long-term patterns of tachycardia occurrences.9 10 Accurate description of these temporal distributions may be extremely valuable in the design of new treatment strategies and may directly affect current management strategies that depend on ECG monitoring to document suppression of spontaneous ventricular ectopy by serial drug testing.11 12 This study describes for the first time the long-term temporal patterns of ventricular tachycardia occurrence in humans as documented by chronically implanted ICDs and tests the hypothesis that the tachycardia occurrences are randomly distributed over time.
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Methods |
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TopAbstractIntroductionMethods Results Discussion References |
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Description of ICDs
The Ventak PRx (Cardiac Pacemakers, Inc) and Guardian 4210 ATP (Telectronics) ICDs were used in this study. Both devices provide extensive retrievable data-logging capabilities, including storage of the time, date, and tachycardia cycle length and the ICD response to each tachycardia detection. The Guardian 4210 has electrogram storage capacity. Both devices use bipolar endocardial or two epicardial unipolar leads for pacing and sensing. The Guardian 4210 device uses epicardial patch electrodes; the PRx uses epicardial patch electrodes or a transvenous endocardial lead (Endotak, CPI) system for shock delivery. The Guardian 4210 uses programmable fixed gain sensing amplifiers (0.5 to 5.7 mV). The PRx uses automatic gain adjusting amplifiers (maximal sensitivity, 0.2 mV). Detection criteria for the Guardian 4210 require that 8 of 10, 12 of 15, or 16 of 20 sensed ventricular events equal or exceed the programmable tachycardia detection rate (100 to 240 beats per minute [bpm]). For the Guardian 4210, tachycardias faster than 240 bpm require 8 of 10 consecutive sensed intervals at these rates to initiate a detection. The CPI PRx records a tachycardia detection when a rate-counting "bin" is filled to a preprogrammed value (8 to 24 beats). Each sensed interval faster than the programmed rate cutoff increases the bin counter by a value of one; subsequent intervals below the rate cutoff decrease the counter by one toward a minimum value of zero.
The time and date of recorded events are provided by reference to time calibrations from the respective programmers. The programmers were maintained at correct local time. The PRx ICD records time to the hour, minute, and second; the Guardian 4210 records time to the hour and minute. The internal clock accuracy for both devices is ±0.03% of the time elapsed since recorded events. The Telectronics Guardian 4210 ATP stores up to 500 tachycardia episodes in clearable memory. The CPI stores up to 228 episodes.
Study Group
All patients undergoing implantation of the CPI
Ventak PRx
or Telectronics Guardian 4210 ATP ICDs at the Medical College of
Virginia, McGuire Veterans Affairs Medical Center, or Sentara Norfolk
General Hospital between April 10, 1991, and April 21, 1993, were
eligible for inclusion in the study. Patients receiving defibrillators
had failed previous drug testing or had noninducible arrhythmias after
documented sustained ventricular arrhythmias or sudden death. Each
patient gave informed written consent to protocols approved by each
hospital's Committee for the Conduct of Human Research. Patients were
excluded from the study if the time or date of tachycardia detections
was not available for any episode from the data log or if detections
known or suspected to result from supraventricular tachyarrhythmias,
lead or connector failure, environmental or electromagnetic noise, or
generator malfunction occurred. The classification of detections as
resulting from ventricular tachyarrhythmias, supraventricular
tachycardias, or noise in the absence of ECG documentation followed
previously published
criteria.13 14 15 16
Detections were
classified as ventricular tachyarrhythmias if accompanied by syncope,
presyncope, typical prodromal symptoms of ventricular tachyarrhythmias
for a given patient, or distinct changes in morphology of stored
electrograms. Ventricular fibrillation was diagnosed if the recorded
R-R interval was 250 milliseconds (>240 bpm) and accompanied by
symptoms of hemodynamic compromise or changes in the morphology of
stored electrograms. Sinus tachycardia was diagnosed if detections
occurred without symptoms during physical exertion likely to cause
sinus tachycardia. Detections were classified as atrial fibrillation if
irregular predetection R-R intervals (>60-millisecond differences)
were recorded without symptoms of ventricular tachyarrhythmias or
without change in morphology of available stored electrograms. Other
supraventricular tachycardias were diagnosed on the basis of previously
documented supraventricular tachycardias, regular R-R interval at the
same rate as supraventricular tachycardia intervals, and absence of
symptoms of ventricular tachycardia. The difficulty of diagnosing
supraventricular arrhythmias in the absence of atrial recordings even
with ventricular electrograms was recognized previously.14
Noise detections were classified by irregular, closely coupled R-R
intervals (<70 milliseconds) or intervals reproduced by manipulation
of the device or lead or associated with other evidence of lead or
generator malfunction. For statistical reasons related to power,
patients with two or fewer detections during follow-up were also
excluded from analysis.
ICD Implantation and Follow-up
All devices were implanted by
use of standard surgical
techniques and were activated on discharge from the operating suite or
within 48 hours. Each patient had appropriate sensing confirmed, and
each device was interrogated for recorded tachycardia events before
hospital discharge and 1, 2, 4, and 6 months after implantation.
Follow-up after 6 months from implantation occurred at intervals of 2
to 6 months. Arrhythmia induction for device testing was performed
before discharge and 2 to 4 months after discharge. Tachycardia
detections resulting from induced arrhythmias were not included in the
data analysis.
Statistics
For each patient, the time intervals between each
consecutive
pair of tachycardia detections were plotted against the cumulative
relative frequency of interdetection intervals during follow-up (Figs 1
through 3
). All
spontaneous tachycardia detections, whether self-terminating or
requiring shock or antitachycardia pacing therapies from the device,
were analyzed. Tachycardia episodes requiring multiple therapy
deliveries to terminate were considered a single detection. For each
patient, a model distribution was generated for the expected random
distribution of the same number of interevent intervals as occurred
spontaneously during the patient's follow-up time period. This model
assumed that each tachycardia detection had an equal likelihood of
occurring at any time during follow-up. Statistically, this model of
independent and random detection occurrence would be described by an
exponential distribution of the interdetection intervals. For each
patient, the cumulative relative frequency for this random model of
tachycardia detections over the follow-up duration is given by
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indicates ventricular
tachyarrhythmias.
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where F(t) is
the cumulative relative frequency of detections
with interdetection intervals t and ß is the estimated mean time
between episodes for the patient (patient's total number of episodes
divided by duration follow-up). The model of random distribution for
each patient was also plotted against the predicted cumulative relative
frequency of interdetection intervals during follow-up. The
Kolmogorov-Smirnov goodness-of-fit test was used to compare each
patient's observed (sample) distribution with his or her own model of
random distribution. The null hypothesis assumed that the
interdetection intervals were independent and randomly distributed
throughout follow-up for each patient. The null hypothesis was rejected
if the patient's sample distribution differed significantly from his
or her model of random distribution. The sign test was used to evaluate
the significance of the proportion of patient groups demonstrating
nonrandom distributions of tachycardia events. Comparisons between
continuous and categorical data were made with Student's t
test and 
2 tests, respectively.
The level of statistical significance was set at P<.01. All values are expressed as mean±SD when appropriate.
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Results |
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TopAbstractIntroductionMethods Results Discussion References |
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Study Group
Of 114 patients receiving the ICDs used in this study, 31 met inclusion criteria. A total of 83 patients were excluded because of incomplete data logs (n=13), detections caused by supraventricular tachycardias or noise (n=22), or two or fewer detections during follow-up (n=34 patients with no detections; n=12 patients with one or two detections). One patient was excluded because the data storage capacity was completely filled (Guardian 4210), and 1 patient was excluded for multiple ventricular tachycardia detections associated with acute myocardial infarction.
The study group comprised 26 men and 5 women. The mean age was 62.6±14.4 years, and average left ventricular ejection fraction was 34±9%. Twenty-five patients had coronary artery disease, and 6 patients had idiopathic cardiomyopathy. The indication for ICD implantation was ventricular tachycardia in 24 patients, ventricular fibrillation in 6 patients, and sudden cardiac death (primary rhythm uncertain) in 1 patient. Fifteen patients received antiarrhythmic drugs during follow-up. Of these, 12 received antiarrhythmic drugs continuously throughout follow-up, and 4 had tachycardia episodes recorded off medications initially and also after starting amiodarone (n=3) or procainamide (n=1). Three patients on continuous drug therapy changed antiarrhythmic agents (without drug-free intervals) owing to drug intolerance or frequent detections. Overall (including drug changes), 3 patients received procainamide, 2 received mexiletine, 2 received propafenone, 1 received disopyramide, and 7 received amiodarone during follow-up. In addition, 1 patient received combination therapy with procainamide and mexiletine and 1 patient received amiodarone and procainamide. The mean duration of follow-up was 227±183 days (range, 7 to 782 days; median, 177 days). Ten patients had the Telectronics Guardian 4210; 21 patients had the CPI Ventak PRx. Detection criteria at implantation for patients with the Telectronics device were 8 of 10 consecutive beats and 12 of 15 consecutive beats above the rate cutoff in 7 and 3 patients, respectively. All patients with the CPI device had detection criteria set between 10 and 16 beats above the rate cutoff.
Patterns of Tachycardia Detections
A total of 727 detections
were recorded from 31 study patients
during follow-up (range, 3 to 101 detections per patient; mean, 23±35
detections per patient; median, 12 detections per patient). Fig
2
shows
an example of the distribution of tachycardia detections during
follow-up for a single patient. For 28 of the 31 patients, the
distribution of interdetection intervals during follow-up differed
significantly from the individuals' respective models of random
distribution (all P<.01) (Fig 3). The proportion of
patients (28 of 31) with nonrandom distributions was highly significant
for the group as a whole (P<.001). All 28 patients
demonstrated a preponderance of interdetection intervals that were
shorter than predicted by their models of random distribution. For the
entire study group of 31 patients, 55% of all interdetection intervals
were 1 hour, 69% were 24 hours, and 78% were 91 hours (Fig
4).
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Table 1 shows the clinical data,
follow-up data,
shortest recorded interdetection interval, and longest duration during
follow-up without detection for all 31 study patients. For 23 of 31
patients (74%), the shortest interdetection interval recorded was
14.4 minutes. Table 1 also shows the 50th percentile for
interdetection intervals for each patient. The median value for the
50th percentile interdetection intervals among the 31 patients was 15.8
hours. The longest documented intervals between detections for these
patients ranged up to 493.3 days (patient 20). The 3 patients (patients
4, 15, and 31) with random detection distributions are identified in
Table 1. Of these 3 patients, 2 received antiarrhythmic drugs
(patient
4 received procainamide; patient 31, amiodarone).
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Data Analysis
by Patient Characteristics
Subgroup analysis of the 31 study patients
revealed that the
proportion of patients with nonrandom detection distributions was
significant for patients with coronary artery disease (22 of 25
patients), patients receiving antiarrhythmic drugs (13 of 15 patients),
patients receiving no antiarrhythmic drugs (15 of 16 patients),
patients with ventricular tachycardia (21 of 24 patients), and patients
with ventricular fibrillation or sudden death (7 of 7) as implantation
indications (all P<.01 for the groups). The proportion of
patients with nonischemic cardiomyopathy and nonrandom distributions (6
of 6 patients) reached the highest achievable significance for a group
of only 6 patients at P=.016.
Data Analysis
of Detections Receiving Therapy
The analysis for nonrandom detection
distributions was
performed for all 31 study patients by use of only those detections
resulting in delivery of shock or antitachycardia pacing therapy. Two
patients were excluded from this subgroup analysis because they had
<3 treated detections. Of 31 patients, 29 had 
3 treated tachycardia
detections and were included in this subgroup. The total number of
treated episodes was 489 (191 antitachycardia pacing and 298 shocks)
from these 29 patients. Of these 29 patients, 25 had distributions of
treated detections that differed significantly from the models of
random distribution for the treated detections (all P<.01).
The proportion of patients with nonrandom distributions (25 of 29) was
highly significant for the group (P=.001).
Data Analysis by Tachycardia Rate
The analysis was
performed for tachycardia episodes with cycle
lengths 250 milliseconds (>240 bpm) and separately for episodes with
cycle lengths of >250 milliseconds. All 727 detections from the 31
total study patients were included in this subgroup analysis by
tachycardia rate. Eleven of 13 patients with 3 detections with a
cycle length 250 milliseconds (108 total detections) had nonrandom
distributions of these events (all P<.01;
P=.0001 for the group). Of 29 patients with 3 tachycardia
detections with cycle lengths >250 milliseconds (619 detections), 25
had nonrandom distributions of these events (all P<.01;
P<.0001 for the group).
Data Analysis of
Detections >7 Days After Implant
Previous studies demonstrated an
enhanced likelihood of
tachycardia episodes in the period immediately after ICD implantation,
possibly caused by mechanical irritation of the heart or the
physiological stresses of surgery.17 18 To control
for the
possibility that multiple postimplantation tachycardia detections would
skew the distributions, the analysis was repeated for each of the
31 study patients with all detections except those occurring in the
first 7 days after ICD implantation. Four patients were excluded from
this subgroup analysis because of <3 tachycardia episodes
occurring more than 7 days after implantation. A total of 670 episodes
occurred >7 days after ICD implantation in the remaining 27 patients.
Of 27 patients, 24 still demonstrated nonrandom distributions of these
tachycardia detections (all P<.01). The proportion of
patients with nonrandom distributions (24 of 27) was highly significant
for the group (P=.001).
Patients With Fewer
Than Two Detections
Table 2 gives clinical data,
follow-up data, and
time to first shock for patients with one (n=8) or two (n=4)
detections. The median interdetection interval for the 4 patients with
two detections was 19.9 hours. The median time to first shock for all
12 patients was 60 days. The longest interval without a detection in
these 12 patients was 697.5 days (patient 10). For these 12 patients
with two or fewer detections, the average follow-up was 257±203 days
compared with 227±183 days for the 31 patients with three or more
detections (P=.64). There were no significant differences in
the proportions of patients with three or more or with two or fewer
detections with respect to the occurrence of coronary artery disease
(25 of 31 versus 9 of 12, respectively), antiarrhythmic drug use during
follow-up (15 of 31 versus 6 of 12), or indication for defibrillator
implantation (ventricular tachycardia in 24 of 31 versus 9 of 12; all
P.8).
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Discussion |
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TopAbstractIntroductionMethods Results Discussion References |
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The description of the long-term temporal patterns of ventricular tachycardia recurrence was not technologically feasible before ICDs with data storage capabilities became available. Previous studies relied on serial Holter monitoring, rarely exceeding 96 hours, or the patients' own subjective recognition of symptoms to record arrhythmic episodes.2 3 4 5 6 7 8 19 The devices used in this study accurately recorded the time and date of each tachycardia episode that met detection criteria during continuous monitoring up to 782 days. Previous work showed that such long-term follow-up is necessary to assess more accurately the frequency and variance of spontaneous arrhythmia recurrences in individual patients.3 5 20 21
This study demonstrates a nonrandom distribution of ventricular
tachycardia episodes over time with a distinct tendency toward temporal
clustering of these episodes in 28 of 31 study patients. The
tachycardia detections were infrequently isolated events with 55% and
69% of all interdetection intervals 1 hour and 24 hours,
respectively. The median value for the 50th percentile interdetection
interval for all 31 patients was 15.8 hours. This nonrandom, clustered
pattern persisted for a highly significant majority of patients after
the exclusion of potentially surgically related arrhythmias and in
separate analyses of episodes by tachycardia rate; by those treated
with the device; and by patient characteristics of heart disease, drug
therapy, and indications for implantation.
Previous studies of the temporal patterns of ventricular
arrhythmias focused on the variability of ectopic activity frequency
over time; however, analyses of the time intervals between individual
ventricular tachyarrhythmic events are
lacking.2 3 5 6 7 8
Marked variation in the frequency of ventricular ectopic activity over
observational periods of minutes, hours, and days has been well
documented. Winkle22 described up to 100% variation in
the frequency of ventricular ectopy during short-term monitoring, while
Pratt et al7 found that 90% of 40 patients with
ventricular tachycardia on any of four serial 24-hour Holter monitors
also had a complete 24-hour recording without ventricular tachycardia.
Many studies stressed the importance of long-term follow-up by
demonstrating that the assessed variability in ectopy frequency is
dependent on the duration of
monitoring.3 5 20 21
Anastasiou-Nana et al3 found that 98% suppression of
repetitive ventricular ectopic forms is necessary to exceed the 95%
CIs for spontaneous variability in individual patients when Holter
monitors are performed 1 year apart. In this same study, a >4000%
increase in total ventricular ectopy was needed to establish
proarrhythmia. The temporal clustering of arrhythmic events in our
study may explain the extreme variance in repetitive ventricular ectopy
and the greater appreciation for the ranges in spontaneous variability
with longer follow-up that is more likely to include a period of
clustered activity. Stein et al23 also demonstrated
nonuniform, clustered distributions of single premature ventricular
beats during short-term monitoring.
The mechanism responsible for the clustering of the tachycardia detections is uncertain. The grouping possibly results from relatively persistent states of myocardial ischemia, autonomic imbalance or activation, or electrolyte abnormalities that favor tachycardia induction.24 25 These conditions alone or in combination may linger for hours or days, allowing frequent tachycardia arrhythmias. Our group also described circadian patterns of tachyarrhythmia detections by ICDs.10 This study of 43 patients demonstrated a distribution of detections fitting a sine wave model with 24-hour periodicity and peak frequency at approximately 3 PM. The contribution of circadian distributions to the clustering of arrhythmic events requires further evaluation. Another explanation for clustering events may be that alterations in myocardial repolarization patterns, oxygen demand, or autonomic tone that follow an initial episode of ventricular tachycardia may facilitate closely timed subsequent arrhythmias.26 27 This may also explain the enhanced likelihood of tachycardia episodes in the days after ICD implantation, which necessitates multiple arrhythmic indications. Waning drug effects is an unlikely explanation for event clustering, given the occurrence of the same temporal pattern in patients receiving no antiarrhythmic drugs.
This report also includes data on 12 patients with rare (two or fewer) detections despite a similar average duration of follow-up to those with more frequent (three or more) events. It is unclear why some patients have very infrequent events despite similar use of antiarrhythmic drugs, indications for implantation, and frequency of coronary artery disease compared with those with frequent events. Perhaps this finding identifies a patient subgroup with a different pattern or trigger for ventricular arrhythmia.
Study Implications
The ability to anticipate the occurrence
of arrhythmic events even
over short periods of time may have important implications for
intermittent antiarrhythmic therapy. After an initial tachycardia
episode and identification of a "high-risk" period for
tachycardia recurrence, additional drug therapy could be taken orally
by the patient or conceivably administered by an automatic pump through
a drug reservoir in the defibrillator. The device could possibly
institute arrhythmia-suppressing pacing algorithms temporarily to
prevent subsequent episodes.28 29 Further studies
into the
pathophysiological factors that contribute to the clustering of
arrhythmic events may greatly advance the understanding of spontaneous
ventricular tachyarrhythmias. In a previous report,10 the
circadian pattern of ventricular tachycardia episodes detected by
defibrillators was apparent in patients not taking antiarrhythmic drugs
but was not observed in patients on long-term antiarrhythmic drug
therapy. In contrast, the clustering of tachycardia episodes over time
was noted in patients both on and off drug therapy in this study. This
suggests that different factors influence these temporal patterns.
The demonstration of long interdetection intervals (up to 493 days) suggests that very extensive follow-up may be needed to determine the long-term success of pharmacological and nonpharmacological therapy (such as radiofrequency ablation) for ventricular arrhythmias. Short-term suppression of arrhythmias after a cluster of events may not be reassuring that the arrhythmic substrate has been suppressed.
Finally, knowledge of systematic variations in the distribution of ventricular arrhythmias raises a question about the appropriateness of treatment strategies based on the pharmacological suppression of spontaneous ventricular arrhythmic events to statistically derived end points.11 12 This strategy assumes relatively constant mean and variance to the frequency of arrhythmic events such that periods of observation with event frequency above or below statistically derived limits are presumed unlikely to occur by chance and therefore can be attributed to a pharmacological intervention. The demonstrated clustering of arrhythmic events into periods of hours or days greatly confounds the ability to define spontaneous variability and thus calculate reliable treatment end points. Others2 3 4 5 raised similar concerns by suggesting that the frequency of ventricular ectopy may follow systematic fluctuations over time. Our data provide support for this hypothesis.
Study Limitations
Although the use of stored electrograms,
data logging, and
clinical history allows discrimination of ventricular tachyarrhythmic
events from noise or supraventricular tachycardias with a high degree
of accuracy, it is possible that some arrhythmic events included in
this analysis resulted from other causes than ventricular
arrhythmias.14 16 All current defibrillators can
store
electrograms for only a limited number of detections. Thus, it is not
always possible to obtain electrograms of every event in patients with
very frequent episodes. The devices recognize only the subset of
ventricular arrhythmic events of sufficient rate and duration to meet
programmed detection criteria. Although considered "sustained"
events, the true duration of treated episodes if shock or pacing
therapy had not been delivered cannot be known. Factors such as silent
myocardial infarction or electrolyte abnormalities may have contributed
to the clustering of detections in some patients. The study group was
relatively small (31 patients); thus, sample biases may have occurred,
and the statistical power of patient subgroup analyses may be limited.
Antiarrhythmic drug therapy was not randomized, so selection bias is
possible. Previous studies examined primarily the frequencies of
isolated or brief ventricular ectopic activities. Conclusions drawn by
comparison to these studies must be considered speculative.
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Footnotes |
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Reprint requests to Mark A. Wood, MD, Medical College of Virginia, PO Box 980053, Richmond, VA 23298.
Received September 12, 1994; revision received November 14, 1994; accepted November 26, 1994.
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