(Circulation. 1999;99:1446-1451.)
© 1999 American Heart Association, Inc.
Clinical Investigation and Reports |
Atrial Fibrillation Detection and R-Wave Synchronization by Metrix Implantable Atrial Defibrillator
Implications for Long-Term Efficacy and Safety
From Queen Mary Hospital, the University of Hong Kong, Hong Kong, China (H-F.T., C-P.L.); St Luke's Medical Center, Milwaukee, Wis (J.S.); Academic Hospital Groningen, Groningen, Netherlands (H.C.); Sahlgrenska Sjukhuset, Göteborg, Sweden (N.E.); Hôpital Cardiologique, Lille Cedex, France (S.K.); and University of Calgary, Calgary, Alberta, Canada (D.G.W.).
 |
Abstract |
|---|
 Top Abstract IntroductionMethodsResultsDiscussionAppendix 1References |
|---|
Background—The long-term efficacy of atrial fibrillation (AF) detection and R-wave synchronization are critical safety requirements for the development of an implantable atrial defibrillator (IAD) for treatment of AF.
Methods and Results—The long-term efficacy of the Metrix IAD for AF detection and R-wave synchronization was tested in 51 patients. The mean duration of follow-up was 259±138 days (72 to 613 days). AF detection tests were performed 2240 times during observed operation with 100% specificity and 92.3% sensitivity for differentiation between sinus rhythm and AF; 2219 episodes and their electrograms stored in the device during AF detection were analyzed. The positive predictive value of the AF detection algorithm was 97.4% (lower 95% confidence limit [CL], 94.5%) in the out-of-hospital setting. A total of 242 435 R waves were analyzed for R-wave synchronization. Of these, 49% were marked for synchronized shock delivery, 82% of sinus rhythm and 36% of AF R waves, respectively. All shock markers were properly synchronized and within the R wave (overall synchronization accuracy, 100%; lower 95% CL, 99.999%). Overall, 3719 shocks have been delivered via the IAD with no instance of unsynchronized shock delivery or any episode of proarrhythmia. The observed proarrhythmic risk was 0%, with an estimated maximum proarrhythmic risk of 0.084% per shock (95% upper CL).
Conclusions—The Metrix IAD can appropriately detect AF with a high specificity and sensitivity and reliably synchronize within a suitable R wave for shock delivery to minimize the risk of ventricular proarrhythmia.
Key Words: fibrillation • atrium • heart-assist device • defibrillation
|
Introduction |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionAppendix 1References |
|---|
Recent studies suggest that atrial fibrillation (AF) is not a benign arrhythmia. The development of AF carries an ominous prognosis with increased morbidity and mortality.1 Transthoracic electrical cardioversion is an effective method to restore sinus rhythm (SR), but the procedure requires general anesthesia and has limited applicability in patients with frequent AF episodes.2 3 The successful application of low-energy biphasic atrial shocks delivered between electrodes in the right atrium (RA) and the coronary sinus (CS) for cardioversion of AF in humans4 5 6 7 has prompted the development of an implantable atrial defibrillator (IAD).8 9 However, the potential ventricular proarrhythmic risk of atrial defibrillation shocks remains a major concern. Atrial shocks when delivered asynchronously or after a short preceding ventricular cycle length can induce potentially lethal ventricular arrhythmias.10 11 12 Therefore, the efficacy of an IAD for AF detection and R-wave synchronization for shock delivery is critically important with regard to ventricular proarrhythmia and safety of the device.
Wellens et al9 recently reported the overall clinical results of the multicenter study of the Metrix IAD and demonstrated the safety and efficacy of this device in patients with AF. The aim of this study was to report in detail the efficacy and safety for AF detection and R-wave synchronization algorithms of the Metrix IAD in the same cohort of patients in this multicenter study.
|
Methods |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionAppendix 1References |
|---|
Patients
The study population included 51 patients (40 men, 11 women; mean±SD age, 58±9 years) with drug-refractory symptomatic AF who received an IAD. Their clinical characteristics have been reported elsewhere.9 The protocol was approved by the ethics committee or institutional review board of each participating center. Informed consent was obtained from all patients.
IAD and Lead System
InControl Metrix IADs (model 3000 or 3020) were used; they have
been described elsewhere.8 9 The device uses 2
defibrillation leads: 1 RA active fixation lead (Perimeter RA model
7205) and 1 CS passive fixation lead (Perimeter CS model 7109). The
RA-CS lead configuration is used for both atrial sensing and
defibrillation. A bipolar endocardial ventricular pacing
lead is used for R-wave synchronization and ventricular
pacing. The device can monitor intracardiac atrial and
ventricular electrograms (EGMs) and use them in specific
algorithms for AF detection and R-wave synchronization (see below). The
device stores the intracardiac EGM data from the last 6 successfully
treated AF episodes (or those marked for treatment when the device is
in monitor mode) and provides data on 170 AF episodes in an episode
log. The IAD can deliver R-wave synchronized biphasic shocks of 3 ms/3
ms (model 3000) or 6 ms/6 ms (model 3020) at a selected voltage, with a
maximal intensity of 300 V and a maximal energy of 3 or 6 J,
respectively, for AF induction or defibrillation.
Study Protocol
During this study, all devices were programmed into the
physician-activated monitor mode. During the monitor mode, the
device is automatically activated at a regular interval
(programmable from 1 to 120 minutes) to detect AF, and the EGMs are
stored in the device memory. However, all the atrial defibrillation
therapies are delivered under close observation by the physician.
Device testing was performed during implantation, at discharge, at 1
and 3 months of follow-up, and during spontaneous AF episodes. During
testing, AF detection and R-wave synchronization were performed with
patients in both SR and AF. After the R-wave synchronization process
had been tested, R-wave synchronized shocks were delivered during SR to
induce AF or during AF for defibrillation.
AF Detection Algorithm
The AF detection algorithm consists of 2 phases: collection and
qualification of EGMs and rhythm analysis. After
collecting an 8-second sample of EGM data from the existing rhythm in
the RA-CS vector and in the RV bipolar vector, the device
analyzes the signals and checks quality for noise
contamination. Then, the sensitivity setting for each channel is
optimized independently by use of automatic gain control (AGC)
(default) or by manual programming of sensitivity. AGC provides
automatic increases or decreases in sensitivity on the basis of the
amplitude of detected signals and permits sensing over a large dynamic
range of input signals while minimizing the incidence of oversensing
and/or undersensing. After the detected R waves have been blanked out
to avoid contamination by the ventricular signal, a 300-ms
detection window is used for atrial sensing in the RA-CS vector. For
sensing of the RA-CS EGM, the RA-CS sense margin ratio
parameter (programmable from 2.0 to 3.4) allows the
physician to specify the relationship between the RA-CS channel
sensitivity threshold and the average peak amplitude of sensed atrial
signals. The greater the sense margin ratio, the wider the range of
RA-CS signal amplitudes the device can sense. The sensitivity threshold
is determined by dividing the average peak signal amplitude by the
sense margin ratio. The device proceeds to rhythm analysis only
when signal amplitude of the 8-second signal strip is considered
adequate and the AGC successfully sets the gain.
Rhythm analysis starts with the "quiet-interval"
analysis that segregates SR from an atrial
tachyarrhythmia. There is only a short period of time
in which atrial electrical activity can be detected during SR. However,
during most atrial tachyarrhythmias, especially AF, the
percentage of time with quiescent atrial electrical activity is much
lower. The quiet-interval algorithm observes the 8-second EGM sample to
look for periods in which the device has not detected events in the
RA-CS vector for at least 170 ms (programmable from 130 to 220 ms). The
cumulative percent time of these quiet intervals (quiet time) is
calculated by dividing the total time by 8 seconds and multiplying by
100%. If the quiet time is >25% (programmable from 10% to 30%) of
the total sample, the rhythm is considered non-AF rhythm; if <25%,
the rhythm is considered to be possible AF (Figure 1
).
|
The device proceeds to implement the "baseline-crossing"
analysis only after the quiet-interval analysis results
in detection of a possible AF. This algorithm detects the presence of
atrial electrical activity at the ST-T region of the cardiac cycle,
which is usually quiescent during SR and most non-AF atrial
tachyarrhythmias. During AF, however, the atrial
electrical activity is random and present throughout the entire
cardiac cycle. The algorithm constructs a detection window in the RA-CS
EGM with a programmable width (nominal width, 200 ms) beginning 80 ms
after the end of each detected R wave. A sensitivity threshold level is
set by the AGC as described above to allow optimal signal detection.
The device then determines the number of times that the atrial signal
crosses both the positive and negative sensitivity threshold levels
within each detection window. The average baseline crossing is the
average number of baseline crossings per window (per R wave) in the
8-second strip. If the average baseline crossing is >2.0 (programmable
from 1.6 to 3.0), then the rhythm is considered to be AF (Figure 2). This analysis is designed to
be highly specific for detection of AF. Furthermore, AF detection will
not proceed when the minimum R-R interval is <400 ms during the
8-second segment. This restriction prevents false-positive AF detection
due to other rapid supraventricular
tachycardias.
|
R-Wave Synchronization
In each patient, the synchronization algorithm was performed
during both AF and SR. Both RV and RV-CS vectors are used for the
synchronization process, which ensures that all shocks are delivered
synchronous to an R wave. The R-wave synchronization algorithm consists
of 2 phases: presynchronization and real-time synchronization.
Presynchronization consists of collecting EGM data from both the RV
bipolar and RV-CS vectors. AGC is again used to check the signal
quality and determine the optimal sensitivities for RV bipolar and
RV-CS vectors. An R wave qualifying for mark shock or shock delivery
must be greater than the programmed minimal synchronization R-R
interval and without a preceding long-short R-R interval sequence.
Because the R wave is sensed at a slightly different time on the RV and
RV-CS channels, a minimal synchronization R-R interval is defined as
the interval between the later of the 2 last detections of the R-wave
activity (S wave) of the first QRS complex and the earlier of the 2
first detections of the R-wave activity (Q wave) of the next QRS
complex. The shortest synchronization R-R interval must be 
500 ms
(programmable from 500 to 800 ms) to minimize the risk of
proarrhythmia due to delivery of atrial shocks to closely
coupled R waves. Furthermore, if the preceding R-R interval on the RV
channel is <800 ms, the qualifying synchronization interval must be
not more than 140 ms shorter (Figure 3).
This restriction avoids shock delivery to an R wave with a preceding
long-short rhythm sequence. If the real-time EGM analysis is
unable to identify an R wave meeting the criteria for R-wave
synchronization within 90 seconds, the device goes back to sleep until
the end of the next wake-up cycle in the monitor mode or until it is
manually activated again.
|
Shock Delivery
After proper synchronization was confirmed by use of the shock
marker, R-wave–synchronized, biphasic shocks were delivered by the
device for AF induction or defibrillation. Atrial defibrillation shocks
for follow-up testing or treating spontaneous AF episodes (amplitudes
varying from 120 to 300 V) were delivered either manually via the
device's induction feature or by use of the device's automatic mode.
The automatic mode combines the individual algorithms of AF detection,
R-wave synchronization, and shock delivery (Figure 4).
|
Statistical Analysis
Numerical values are expressed as mean±SD. Data for calculation
of the sensitivity and specificity of the AF detection algorithm were
collected at implantation, before discharge, at 1 and 3 months, and
during spontaneous episodes. The sensitivity of the AF detection
algorithm was calculated by use of the ß binomial model, and the
specificity of the AF detection algorithm was calculated by use of the
truncated exponential model.
To determine the positive predictive value of the AF detection algorithm, at each follow-up visit, the episodes, if any, in the 6 registers of the episode data log were printed. The data for this analysis from each encounter consisted of (1) the number of EGMs recorded (maximum of 6), including the number of times the device detected AF, and (2) the number of these EGMs that truly documented the presence of AF. The positive predictive value of the AF detection algorithm was then calculated with the ß binomial model. At each follow-up visit, five 1-minute segments of EGMs during AF and during SR were stored and analyzed for the total number of R waves and the number of incorrect shock indicators. Synchronization accuracy was then estimated with the exponential Poisson model.
The total number of atrial defibrillation shocks delivered and the total number of instances of ventricular proarrhythmia observed were determined for each subject. The mean risk of ventricular proarrhythmia was estimated with the truncated exponential model.
|
Results |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionAppendix 1References |
|---|
Forty-seven patients (92%) completed the study protocol after a mean follow-up of 259±138 days (range, 72 to 613 days). As reported elsewhere,9 3 patients had their devices explanted for complications and 1 patient underwent atrioventricular junction ablation and permanent pacing due to frequent AF episodes.
AF Detection Algorithm Performance During Observed
Operation
The AF detection test was performed 2240 times in 51 patients
(Table 1). During SR, the AF
detection test was performed 1062 times, and identification of SR was
successful for all of these, corresponding to a 0% false-positive
rate. During AF, the AF detection test was performed 1178 times. There
were 109 episodes (9%) of false-negative detection (determination of
SR when the actual rhythm was AF). The majority of false-negative
detections were due to atrial flutter or related to low signal
amplitude with a noisy background signal (Figure 5). However, all of these false-negative
episodes were transient, and the device was able to correctly detect AF
in the next cycle of rhythm analysis during the same episode of
arrhythmia or after reprogramming of the device
parameters. The remaining 1069 detection tests identified
as AF were all confirmed as being AF by the attending physician,
corresponding to a 100% true-positive rate. Overall, the AF detection
algorithm had 100% (lower 95% confidence limit [CL], 99.7%)
specificity for normal SR and 92.3% (lower 95% CL, 89.3%)
sensitivity for AF detection.
|
|
AF Detection Algorithm Performance During Monitor Mode
Operation
A total of 2219 eight-second EGM data segments stored in devices
in which AF was detected by the algorithm during the monitor mode were
available for analysis. In 2211 of these episodes, the EGMs
were confirmed to be AF. However, there were 8 episodes of
false-positive AF detection in 3 patients, in which the device
identified SR as AF. Thus, the positive predictive value of the AF
detection algorithm was 97.4% (lower 95% CL, 94.5%). Seven of the 8
episodes of false-positive AF detection were from 2 patients and
occurred within the first 3 months after implantation. A third patient
had a single episode of false-positive AF detection 4 months after
implantation. All of these episodes of false-positive AF detection
occurred during sinus tachycardia and had an R-R interval
of >500 ms (Figure 5
). However, in all 3 patients, the devices
could be successfully reprogrammed to avoid AF detection, and none of
them had further false-positive AF detection thereafter.
R-Wave Synchronization
In total, 242 435 R waves were analyzed, 119 241 (49%)
of them marked as "shockable" by the device (Table 2). The percentages of R waves marked for
shock during SR and AF were 82% and 36%, respectively. The main
reason for rejecting R waves for shock was violation of the minimum R-R
interval of >500 ms. However, during all the episodes of AF,
successful R-wave synchronization was achieved by repeating the
synchronization test. All shock markers were within the R wave, and
none of them were outside the R wave (overall synchronization accuracy,
100%; lower 95% CL, 99.9987%).
|
Shock Delivery Results
The overall clinical result for shock delivery in this study was
recently reported.9 In brief, a total of 3719 shocks were
delivered via the IADs, with shock amplitudes varying from 20 to 300 V.
No instance of inaccurately synchronized shock delivery and no
ventricular proarrhythmia was noted during the
study. The observed ventricular proarrhythmic risk of the
atrial defibrillation shock was 0%, with a maximum
ventricular proarrhythmic risk of 0.084% per shock (upper
95% CL).
|
Discussion |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionAppendix 1References |
|---|
Recent advances in technology have made the IAD a prospective new therapeutic approach for patients with drug-refractory AF. However, the nonlethal nature of AF requires a high level of safety and efficacy before such a device gains general acceptance. The reliability and accuracy of AF detection and R-wave synchronization for shock delivery are the most important considerations in assessment of the safety and feasibility of the IAD.
Detection of AF
The ability to detect AF automatically and reliably via
intracardiac EGMs is a challenging task. Atrial EGMs are smaller and
more variable in amplitude than ventricular EGMs. There
is greater variability and a substantial loss in signal amplitude
between AF and SR.13 Thus, AF detection requires special
methodology for reliable and accurate detection. The high-gain settings
required may render AF detection more prone to electrical interference
and far-field QRS oversensing. Although a previous short-term
study14 showed that the AF detection algorithm of Metrix
IAD can accurately detect AF, there are no long-term data on the
efficacy of AF detection algorithms during implantation and in an
ambulatory setting with permanent leads.
The results of this study confirm that AF detection algorithms of the IAD can detect AF appropriately in ambulatory patients during long-term follow-up. The combination of quiet-interval and baseline-crossing analysis can discriminate between AF and SR with a high degree of sensitivity (92%) and specificity (100%). AF detection during daily activities while the IAD is in the monitor mode shows that the positive predictive value of this AF detection algorithm is 97%. False-positive AF detection is potentially more important than false-negative AF detection. Unlike defibrillation for ventricular tachyarrhythmia, a delay of defibrillation therapy because of false-negative detection during AF would not be likely to be harmful. On the other hand, false-positive detection of AF during SR may result in an inappropriate defibrillation shock.
In 
9% of the AF episodes in the present study, the IAD
determined that the rhythm was SR when in fact it was AF. There are
several possible explanations for these episodes of false-negative AF
detection. First, the most common cause of false-negative AF detection
is atrial flutter or a more organized AF in which the atrial rate is
regular and slow, resulting in a low baseline-crossing count (Figure 5). Second, the device will reject those AF signals with poor
signal quality due to a noisy background signal (Figure 5) or
those during a rapid ventricular rate (R-R interval <400
ms). Finally, if the AF signal levels are too small, the algorithms
sense a low number of events and calculate a high percent quiet
interval.
Of more concern are those episodes of false-positive AF detection
observed during sinus tachycardia (Figure 5).
Overall, 8 episodes (0.3%) of false-positive AF detection occurred in
3 patients. Because both the quiet-interval and baseline-crossing
algorithms are closely related to the atrial rate, any rapid atrial
rhythm may potentially be mistaken for AF. In the majority of
supraventricular tachyarrhythmias, a short
R-R interval (<400 ms) during tachycardia would prevent AF
detection. However, during sinus tachycardia, when the
atrial cycle length is shortened but the R-R interval is >400 ms,
these algorithms may have difficulty discriminating AF from sinus
tachycardia. In the present study, all the
false-positive AF detection episodes occurred during sinus
tachycardia. Importantly, in all of these false-positive
episodes during sinus tachycardia, the R-R intervals were
>500 ms, and inappropriate shock therapy might have resulted if the
device were programmed to the fully automatic mode. Nevertheless,
successful reprogramming of the IAD prevented further false-positive AF
detection in all 3 of these patients. Thus, before the device is
programmed to the fully automatic mode, an initial period of
observation in the monitor mode or testing during sinus
tachycardia is advisable to achieve optimal device
programming.
R-Wave Synchronization and Risk of Ventricular
Proarrhythmia
The proarrhythmic potential of an atrial shock therapy for atrial
defibrillation has been well documented previously.10 11 12
In most instances, the ventricular proarrhythmic episodes
resulted from shocks that were not properly synchronized within the R
wave. Poor synchronization is a major concern with respect to the
safety of the IAD, particularly in relation to automatic shock therapy
in a device without the capacity for backup ventricular
defibrillation. These considerations emphasize the importance of
achieving reliable R-wave synchronization for shock delivery. However,
R-wave synchronization alone may not be sufficient to prevent the
ventricular proarrhythmia. Previous
studies12 have demonstrated that as long as the atrial
shock was not delivered during the ventricular vulnerable
period, ie, the T wave, of the preceding beat, the risk of induced
ventricular tachyarrhythmia is nil.
However, the ventricular vulnerable period can be affected
by the preceding cycle length and rhythm. Even with proper R-wave
synchronization, the proarrhythmic risk was higher with shock delivery
after a short preceding R-R interval (<300 ms), because the terminal
portion of the preceding T wave may encroach on the R
wave.10 12 Furthermore, the occurrence of a preceding
long-short cycle length sequence is associated with a higher risk of
ventricular proarrhythmia because of an increase in
the dispersion of ventricular
refractoriness.10 Thus, delivery of an atrial shock to an
R wave with a preceding long-short R-R sequence should also be
avoided.
The IAD uses special algorithms to reject R waves for shock delivery if the preceding R-R intervals are below a minimum interval of 500 ms (which is well above the safety limit observed in animal studies) or if the preceding R-R intervals have a long-short cycle-length sequence. The present results demonstrate the efficacy of the R-wave synchronization and shock delivery algorithm of this device. Although only 36% of R waves analyzed during AF were determined by the device to be suitable for shock delivery, all shock synchronization markers and shock delivery were accurately placed within the R wave after an appropriate preceding R-R sequence. Because defibrillation of AF is rarely an emergency, there is no penalty in allowing the device to wait for an appropriate R wave. A total of 3719 shocks were delivered via the IADs in this study with no instances of ventricular proarrhythmia. Successful cardioversion of spontaneous AF was achieved in 96% of episodes, with a very low estimated proarrhythmia risk.
Conclusions
The results of the present study demonstrate the long-term
efficacy and safety of the AF detection algorithms and the R-wave
synchronization algorithms of an IAD in a large cohort of patients
implanted with this device. The AF detection algorithms of the IAD
incorporate the quiet interval, and the baseline-crossing
analysis allows sensitive and specific differentiation between
SR and AF. The R-wave synchronization algorithms of the IAD reliably
and properly synchronize to an R wave appropriate for shock delivery.
The proarrhythmic risk of the atrial shocks by the IAD is minimized by
avoiding shock delivery within an R wave with a preceding R-R interval
<500 ms or with a preceding long-short R-R cycle-length sequence.
These findings have positive implications concerning the safety and
efficacy of IADs for clinical use.
|
Footnotes |
|---|
Reprint requests to Prof Chu-Pak Lau, Chief, Division of Cardiology, Department of Medicine, University of Hong Kong, Queen Mary Hospital, Hong Kong, China.
|
Appendix 1 |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionAppendix 1References |
|---|
List of Participating Centers and Investigators
St George's Hospital, London, UK: A.J. Camm, E. Rowland, D. Ward, S.M. Sopher, M. Gallagher, A. Slade, J. Waktare. Queen Mary Hospital, The University of Hong Kong, China: C.P. Lau, H.F. Tse, N.S. Lok, K. Lee. University of Calgary, Calgary, Alberta, Canada: D.G. Wyse. Institute of Cardiology, Montréal, Quebec, Canada: B. Thibault, M. Talajic. St Michael's Hospital, Toronto, Ontario, Canada: P. Dorian, D. Newman. Academic Hospital Gent, Gent, Belgium: L. Jordaens, R. Tavernier, F. Provenier. Hôpital Nord, Marseille, France: S. Levy, V. Taramasco, E. Dolla. Hôpital Cardiologique, Lille, France: S. Kacet, D. Lacroix, P. le Franc, D. Klug, C. Kouakam. Hôpital Hôtel Dieu, Rennes, France: C. Daubert, D. Gras, P. Mabo, D. Pavin. University of Bonn, Bonn, Germany: B. Lüderitz, W. Jung. Klinikum der Stadt, Ludwigshafen, Germany: K. Seidl. Academic Hospital Maastricht, Maastricht, Netherlands: H. Wellens, C. Timmermans, L.M. Rodriguez. Sahlgrenska Sjukhuset, Göteborg, Sweden: N. Edvardsson, L. Lurje, M. Aunes, H. Walfridsson. Karolinska Hospital, Stockholm, Sweden: M. Rosenqvist, C. Linde. Academic Hospital Groningen, Groningen, Netherlands: H. Crijns, I. Van Gelder. St Luke's Medical Center, Milwaukee, Wis: J. Sra, M. Akhtar, M. Miehl, Z. Blanck, S. Deshpande, A. Dhala, H. Jazayeri, D. Kress. University Hospitals of Cleveland, Cleveland, Ohio: L. Biblo, J. Mackall, A. Waldo, D. Rosenbaum, M. Carlson. University of Michigan Medical Center, Ann Arbor, Mich: A. Strickberger, F. Morady, E. Daoud, R. Goyal, M. Harvey, K. Ching Man. University of Utah Medical Center, Salt Lake City, Utah: R. Freedman, R. Klein, J. Mason, G. Muelheims, P. Spector, S. Compton.
Received June 23, 1998; revision received November 20, 1998; accepted December 17, 1998.
|
References |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionAppendix 1References |
|---|
1. Kannel WB, Abbott RD, Savage DD, McNamara PM. Epidemiologic features of chronic atrial fibrillation: the Framingham study. N Engl J Med. 1982;306:1018–1022.[Abstract]
2.
Lown B. Electrical cardioversion of cardiac
arrhythmias. Br Heart J. 1967;29:469–487.
3. Van Gelder IC, Crijns HJ, Van Gilst WH, Verwer R, Lie KI. Prediction of uneventful cardioversion and maintenance of sinus rhythm after direct-current electrical cardioversion of chronic atrial fibrillation and flutter. Am J Cardiol. 1991;68:41–46.[Medline] [Order article via Infotrieve]
4. Murgatroyd FD, Slade AKB, Sopher SM, Rowland E, Ward DE, Camm AJ. Efficacy and tolerability of low energy cardioversion of paroxysmal atrial fibrillation in humans. J Am Coll Cardiol. 1995;25:1347–1353.[Abstract]
5. Lok NS, Lau CP, Ho DSW, Tang YW. Hemodynamic effects and clinical determinants of defibrillation threshold for low energy transvenous atrial defibrillation in patients with chronic atrial fibrillation. Pacing Clin Electrophysiol. 1997;20:899–908.[Medline] [Order article via Infotrieve]
6. Levy S, Richard P, Lau CP, Lok NS, Camm AJ, Murgatroyd FD, Jordaens LJ. Multicenter low energy transvenous atrial defibrillation (XAD) trial results in different subsets of atrial fibrillation. J Am Coll Cardiol. 1997;27:750–755.
7.
Levy S, Richard P, Gueunoun M, Yapo F, Trigano J,
Mansouri C, Paganelli F. Low-energy cardioversion of spontaneous atrial
fibrillation: immediate and long-term results. Circulation. 1997;96:253–259.
8. Lau CP, Tse HF, Lok NS, Lee KLF, Ho DSW, Sopher M, Murgatroyd F, Camm AJ. Initial clinical experience with an implantable human atrial defibrillator. Pacing Clin Electrophysiol. 1997;20:220–225.[Medline] [Order article via Infotrieve]
9.
Wellens HJJ, Lau CP, Lüderitz B, Akhtar M, Waldo
AL, Camm AJ, Timmermans C, Tse HF, Jung W, Jordaens L, Ayers G; for the
Metrix Investigators. Atrioverter, an implantable device for the
treatment of atrial fibrillation. Circulation. 1998;98:1651–1656.
10.
Ayers GM, Alferness CA, Ilina MB, Wagner DO, Sirokman
WA, Adams JM, Griffin JC. Ventricular proarrhythmic effects
of ventricular cycle length and shock strength in a sheep
model of transvenous atrial defibrillation. Circulation. 1994;89:413–422.
11. Barold HS, Wharton JM. Ventricular fibrillation resulting from synchronized internal atrial defibrillation in a patient with ventricular preexcitation. J Cardiovasc Electrophysiol. 1997;8:436–440.[Medline] [Order article via Infotrieve]
12.
Sokoloski MC, Ayers GM, Kumagai K, Khrestian CM, Niwano
S, Waldo AL. Safety of transvenous atrial defibrillation: studies in
the canine sterile pericarditis model. Circulation. 1997;96:1343–1350.
13. Jenkins J, Noh KH, Guezennec A, Bump T, Arzbaecher R. Diagnosis of atrial fibrillation using electrograms from chronic leads: evaluation of computer algorithms. Pacing Clin Electrophysiol. 1988;11:622–631.[Medline] [Order article via Infotrieve]
14. Sra JS, Maglio C, Dhala A, Blanck Z, Biehl M, Deshpande S, Keelan E, Jazaayeri MR, Akhtar M. Feasibility of atrial fibrillation detection and use of a preceding synchronization interval as a criterion for shock delivery in humans with atrial fibrillation. J Am Coll Cardiol. 1996;28:1532–1538.[Abstract]
This article has been cited by other articles:
 |
|
 |
|
  A. Kadish and M. Mehra Heart Failure Devices: Implantable Cardioverter-Defibrillators and Biventricular Pacing Therapy Circulation, June 21, 2005; 111(24): 3327 - 3335. [Full Text] [PDF]
|
|
|
|
|
|
T. H. Everett IV, J. R. Moorman, L.-C. Kok, J. G. Akar, and D. E. Haines Assessment of Global Atrial Fibrillation Organization to Optimize Timing of Atrial Defibrillation Circulation, June 12, 2001; 103(23): 2857 - 2861. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
E. G. Daoud, C. Timmermans, C. Fellows, R. Hoyt, R. Lemery, K. Dawson, and G. M. Ayers Initial Clinical Experience With Ambulatory Use of an Implantable Atrial Defibrillator for Conversion of Atrial Fibrillation Circulation, September 19, 2000; 102(12): 1407 - 1413. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 C. Timmermans, S. Levy, G. M. Ayers, W. Jung, L. Jordaens, M. Rosenqvist, B. Thibault, J. Camm, L.-M. Rodriguez, H. J. J. Wellens, et al. Spontaneous episodes of atrial fibrillation after implantation of the Metrix Atrioverter: observations on treated and nontreated episodes J. Am. Coll. Cardiol., May 1, 2000; 35(6): 1428 - 1433. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
H.-F. Tse, C.-P. Lau, B. M. Yomtov, and G. M. Ayers Implantable atrial defibrillator with a single-pass dual-electrode lead J. Am. Coll. Cardiol., June 1, 1999; 33(7): 1974 - 1980. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
W. Xu, H.-F. Tse, F. H.Y. Chan, P. C. W. Fung, K. L.-F. Lee, and C.-P. Lau New Bayesian Discriminator for Detection of Atrial Tachyarrhythmias Circulation, March 26, 2002; 105(12): 1472 - 1479. [Abstract] [Full Text] [PDF]
|
|
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||