© 2004 by European Society of Cardiology
REVIEW
Performance of a dual-chamber implantable defibrillator algorithm for discrimination of ventricular from supraventricular tachycardia
aDepartment of Cardiac Pacing and Electrophysiology Lille University Hospital, France; bGuidant CRM Rueil-Malmaison, France; cDepartment of Cardiology CHU La Timone, Marseille, France; dDepartment of Cardiology CHU Gabriel Montpied, Clermont Ferrand, France; eDepartment of Cardiology CHU Michalon, Grenoble, France; fDepartment of Cardiology CHU A. de Villeneuve, Montpellier, France
Manuscript submitted 22 April 2003. Accepted after revision 21 September 2003.
*Corresponding author. Service de Cardiologie A, Hôpital Cardiologique, Boulevard du Pr J. Leclercq - CHR & U 59037 Lille Cedex, France. Tel.: +33-3-20-44-50-38; fax: +33-3-20-44-68-98. E-mail address: c-kouakam@chru-lille.fr (C. Kouakam)
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Abstract |
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BACKGROUND: Inappropriate therapies remain a major problem in patients with implantable cardioverter defibrillators (ICDs). Decreasing the proportion of inappropriate therapies is a major objective. With the addition of atrial detection and advanced algorithms, dual-chamber ICDs are designed to offer better discrimination of ventricular (VT) and supraventricular (SVT) arrhythmias. The present multicentre, open study aimed to evaluate the performance of a dual-chamber detection algorithm, the Atrial ViewTM algorithm, incorporated in a dual-chamber ICD, the Ventak® AV (Guidant Inc., St. Paul, Minnesota, USA).
METHODS AND RESULTS: Fifty-one patients (45 males, 62±11 years, ejection fraction 42±15%) with standard indications received a Ventak® AV ICD which analyzes, within the VT zone RR stability, tachycardia onset, atrial rate and AV relationship. Predischarge enhanced-detection algorithms were prospectively programmed: stability 24 ms, onset 9%, atrial fibrillation threshold 200 beats/min, and V rate A rate. An additional sustained rate duration criterion was programmed at least at 30 s. ICDs were interrogated every 3 months or when patients received shocks. A blinded review of electrograms for arrhythmia diagnosis and appropriateness of therapy was performed by 2 experts. Over the follow-up period (12±3.6 months), a total of 400 tachycardia episodes was recorded within the VT zone. After the review of stored electrograms, 237 (59%) true positive, 143 (36%) true negative, 17 (4%) false positive and 3 (1%) false negative episodes were diagnosed. Considering the 3 VTs incorrectly detected by the detection algorithms, therapy was delivered in 2 cases after sustained rate duration and 1 VT reverted spontaneously. Inappropriate therapy occurred in 17 cases. All but 1 were related to SVT with 1:1 atrioventricular relationship. Finally, on a per episode basis, the detection algorithm sensitivity was 99% and specificity was 89%.
CONCLUSIONS: Programming of detection criteria based on stability, onset, atrial fibrillation rate threshold and V rate A rate allows a 99% sensitivity and an 89% specificity in Guidant ICDs. Discrimination of SVT with 1:1 atrioventricular relationship, however, remains a challenge for which new algorithms have to be designed.
Key Words: dual-chamber ICD, ventricular tachycardia, supraventricular tachycardia, tachycardia detection algorithms
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Introduction |
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The implantable cardioverter defibrillator (ICD) has been proven to reduce the mortality of patients with life-threatening ventricular arrhythmias [1]
and has become the therapy of choice for patients with aborted sudden cardiac death or poorly tolerated ventricular tachycardias (VTs) [2]. Despite many technological improvements in ICDs (device miniaturization, transvenous implant techniques, biphasic shocks, antitachycardia pacing), accurate discrimination of VT from supraventricular tachycardia (SVT) remains a challenge [3]. Earlier single-chamber discrimination algorithms analyzed ventricular intervals, and previously described studies reported that inappropriate therapies occurred in up to one third of patients with single-chamber ICDs [4–6]. These inadequate therapies are frequently multiple and ineffective, and may induce ventricular arrhythmias [7,8] or psychological stress [9]. The goal of newer generation ICDs is not only to control life-threatening arrhythmias but also to improve patients' quality-of-life. Decreasing the incidence of inappropriate therapies is, therefore, a major objective. With the development of dual-chamber ICDs, it was anticipated that these devices could substantially reduce the incidence of inaccurate detection of SVT by providing additional information about the underlying atrial rhythm [10]. To address this issue, we aimed to evaluate the sensitivity and specificity of a dual-chamber discrimination algorithm, the "Atrial ViewTM" algorithm, incorporated in a dual-chamber device, the Ventak® AV ICD (Guidant Inc., St. Paul, Minnesota, USA). |
Methods |
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Patient selection
Fifty-one consecutive patients with a currently accepted indication for ICD therapy were enroled at 11 centres from June 1997 to July 1999. Patients participated in this French, multicentre, open study if they were treated with a dual-chamber Guidant ICD. The major exclusion criteria were chronic atrial fibrillation or atrial flutter. All patients gave written, informed consent according to a protocol approved by the Human Subjects Committee (or Ethical Committee), and were followed up for at least 12 months after implant. All patients were in sinus rhythm at implant. The characteristics of the 51 study patients are listed in Table 1.
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Implant techniques, device description and Ventak AV detection architecture
All patients underwent a standard implant procedure of pectoral ICD systems with transvenous endocardial leads (Endotak, Guidant, St. Paul, Minnesota, USA) via the subclavian and/or cephalic veins. Ventricular and atrial sensing and pacing thresholds were evaluated carefully at implant and predischarge testing. The devices used in this study (Ventak® AV II/III DR) feature an increased intracardiac electrogram (EGM) storage capacity up to 16 min for VT/VF episodes, as well as for episodes with intervals in the VT detection zone for which therapy is withheld due to classification as an SVT. The ICD also offers the ability automatically to measure and store the data relating to sudden onset and RR stability of spontaneous arrhythmia episodes.
Incremental to the basic single-chamber detection criteria, the dual-chamber uses the Atrial ViewTM algorithm. Fig. 1 provides an introduction to the Ventak® AV Atrial ViewTM detection architecture [11]. Briefly, Ventak® AV is designed to differentiate SVT from VT through the use of 2 additional detection algorithms: (1) atrial fibrillation rate threshold (known as AFib rate threshold) and (2) ventricular rate greater than atrial rate (known as V rate A rate). These algorithms are best used in conjunction with the established stability, onset and sustained rate duration (SRD) single-chamber discrimination algorithms [12,13]. The goal of the stability criterion is to distinguish VTs characterized by a small variation in tachycardia cycle length from SVTs presenting a higher degree of variability of RR intervals such as atrial fibrillation. The onset is intended to distinguish sinus tachycardias with a gradual rate increase from ventricular arrhythmias characterized by a sudden increase in heart rate. When the AFib rate threshold (programmed from 200 to 400 beats/min) is fulfilled, the device recognizes that atrial arrhythmia is present, and it will withhold therapy for unstable ventricular rhythms with atrial rate greater than the programmed threshold. In the presence of a ventricular rate that is faster than the atrial rate, the device will deliver therapy immediately in order to ensure patient safety. Onset and stability, along with AFib threshold, are therapy inhibitors. But either SRD or V rate A rate can override these inhibitors to initiate therapy delivery. These criteria can be programmed only in the lowest zone of a device programmed in a 2- or 3-zone configuration.
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Predischarge ICD programming
The protocol required the activation of all Atrial ViewTM discrimination criteria with at least 2 detection zones in all patients (including VF survivors). The VT zone was programmed beginning at 120–185 beats/min, depending on the age of the patient and expected exercise level. In 13 patients with a history of "slow" VTs, 2 VT zones were programmed. The lower VT zone was set at 10–20 beats/min below the known VT rates for the individual patient. The mean cutoff rate for VT detection was 148±14 beats/min. The mean cutoff rate for the VF zone was 194±16 beats/min (range 185–220). Detection enhancement algorithm programming was standardized. The stability criterion was programmed at 24 ms. The onset criterion was programmed at 9%. The V rate A rate criterion was activated. The AFib rate threshold criterion was programmed at 200 beats/min. Programming of the safety algorithm SRD was recommended at least at 30 s. Investigators were allowed to modify the initial programming after 1 recorded spontaneous episode.
Follow-up
Patients were followed up every 3–4 months after implantation. Additional visits were scheduled whenever patients experienced shocks, palpitations, or presyncope. During each visit, patients were examined and devices were interrogated to determine episodes with stored EGMs. Reprogramming, adjustments of drug therapy, or hospitalizations were performed as necessary according to the recorded events and factors deemed causative. Stored EGMs were reported on a Save To Disk file. When the number of episodes exceeded the EGM storage capability of the device, episodes without an accompanying EGM were excluded.
Data collection
For all patients, selected demographic and historic data (i.e. age, gender, underlying cardiac disease, left ventricular ejection fraction, arrhythmia history before implant, and prior SVT episodes) were entered into an update database. In addition, for patients with an arrhythmic event during follow-up, data derived from the EGMs (i.e. day and time of the episode, cycle length, stability, and onset) were entered prospectively into the database.
Classification of arrhythmia episodes
Only stored EGMs recorded in the lowest VT zone were considered for analysis. All stored EGMs were analyzed by at least 2, and in questionable cases, 3 senior physicians, and became the standard for the determination of the true nature of the rhythm. The stored diagnostic data for episodes identified as SVT and VT episodes for which therapy was withheld allowed confirmation of detection algorithm appropriateness. This information, automatically stored within the ICD, was copied to disk for investigator evaluation and confirmation of classification. An arrhythmia was classified as VT if the ventricular rate exceeded the atrial rate. The arrhythmia was classified as atrial fibrillation if the atrial rate exceeded the ventricular rate with irregular RR intervals. The arrhythmia was classified as sinus tachycardia if atrial rate was equal to ventricular rate, and if there was no sudden onset. The diagnosis of atrial flutter was based on: (1) atrial rate > ventricular rate with regular PP and RR intervals and a ventricular rate at 150 beats/min and (2) a history of atrial flutter. Diagnosis of SVT with 1:1 atrioventricular (AV) relationship was considered when atrial rate was equal to ventricular rate, with the stored EGM showing the onset of tachycardia in the atrium. Therapy of a spontaneous VT was considered appropriate if the stored EGM clearly demonstrated VT. Inappropriate therapy was defined as therapy delivered with an underlying SVT or sinus tachycardia. Calculations were made from the perspective of the ICD accurately to detect VT (true positive [TP]), accurately to detect SVT (i.e. withhold therapies for SVT) without coexistent VT (true negative [TN]), falsely to detect SVT as VT (false positive [FP]) and falsely to detect VT as SVT (false negative [FN]). The following parameters were utilized to characterize the performance of the detection algorithm: sensitivity was defined as the ability appropriately to detect VT [(TP/TP+FN)×100], and specificity as the ability to reject SVT [(TN/TN+FP)×100]. The predictive positive value was calculated to determine the likelihood that a delivered therapy was appropriate [(TP/TP+FP)×100]. The predictive negative value was calculated to determine the likelihood that a delivered therapy was appropriately not required [(TN/TN+FN)×100].
Note that the absolute sensitivity and specificity of VT detection cannot be computed from these data, since any tachycardia (VT or SVT) with ventricular rates slower than the VT rate threshold will not be detected. In addition, SVT with ventricular rate faster than "slow VT" threshold were excluded from the analysis since the Atrial ViewTM diagnostics do not operate in the VF zone or in the fast VT zone when 2 VT zones are programmed (Fig. 1).
Statistical analysis
Data are expressed as mean±SD, median, or percentage. Performance measures of sensitivity and specificity were analyzed by using the Generalized Estimating Equations (GEE) method. Only episodes that had a stored EGM, the physician's classification of the rhythm, and all enhanced-detection criteria programmed, were included in the analysis of these efficacy measures. If a spontaneous episode resulted in multiple stored device-defined episode, only the first stored episode was analyzed.
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Patient population
Baseline clinical and demographic characteristics of the study population are similar to those of previously reported ICD populations and are listed in Table 1. At predischarge testing, the atrial and ventricular sensing and pacing thresholds were 3.9±2.7 mV and 11.8±4.9 mV, 1.1±0.6 V and 1.3±0.9 V at 0.5 ms, respectively. These values were stable during follow-up. All patients were followed up for 12.3±3.6 months (range 9–21 months). During follow-up, 6 patients died: 4 due to progressive heart failure, 1 due to septicaemia and 1 patient died suddenly. At discharge, the device was programmed with 1 VT zone in 38 patients (tachycardia detection interval 150±15 beats/min, range 120–185 beats/min), and 2 VT zones in 13 patients (lowest tachycardia detection interval 143±6 beats/min, range 130–150 beats/min). Discrimination criteria were enabled in all patients. The mean duration of programmed SRD was 31±5 s (median 30, range 30–60 s).
Arrhythmias
Over the follow-up period, 400 episodes recorded in the lowest VT zone (i.e. with all detection-enhanced criteria programmed) were analyzed. These episodes occurred at an average of 7.4±6.8 months (median, 5 months) after ICD implantation in 27 out of 51 patients. Based on physician classification, there were 240 episodes of spontaneous VT in 21 patients (atrial rate 64±23 beats/min, ventricular rate 155±16 beats/min, RR stability 20±23 ms, onset 30±14%) and 160 episodes of spontaneous SVT in 14 patients (atrial rate 165±52 beats/min, ventricular rate 135±12 beats/min, RR stability 63±39 ms, onset 11±9%) (Table 2). In patients who experienced spontaneous arrhythmias, the mean number of VTs per patient was 11±17 (median 3, range 1–64) and the mean number of SVTs per patient was 7±9 (median 3, range 1–30). Thirty-six percent of detected VTs had a cycle length 
400 ms, 58% had a cycle length between 400 and 330 ms, and only 6% had a cycle length <330 ms.
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Algorithm performance
The Comparison between device diagnosis and physician diagnosis is summarized in Table 3. The Atrial View correctly identified 237 out of 240 episodes as VT, resulting in a sensitivity of 99%. Fig. 2 shows a stored EGM record for a case in which therapy was appropriately delivered for VT. Fig. 3 shows an example of an appropriately detected atrial tachycardia which leads to VT. Of the 3 incorrectly classified VTs, 2 were related to a dual tachycardia with a measured stability >24 ms, and 1 was related to a slow VT with 1:1 retrograde conduction and an onset value <9%. Therapy was finally delivered after SRD in 1 dual tachycardia and the slow VT, and the other dual tachycardia spontaneously terminated before SRD.
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The Atrial ViewTM discrimination algorithm demonstrated an 89% specificity on a per episode basis, appropriately withholding therapy for atrial arrhythmias (with ventricular responses in the VT zone) in 143 SVTs. These included 12 episodes of sinus tachycardia, 35 episodes of atrial flutter and 96 episodes of atrial fibrillation. Inappropriate therapies were delivered to 17 SVT episodes of which 16 tachycardias with 1:1 AV relationship, and 1 "stable" atrial fibrillation (measured stability 11 ms) with intermittent atrial undersensing resulting in false V rate A rate detection, with consequent failure of the respective dual-chamber algorithm (Table 2). These episodes occurred in 4 out of 27 patients. Inappropriate 1:1 SVT–VT discrimination could not be corrected by ICD reprogramming due to algorithm limitations (i.e. sudden-onset stable tachycardia). These patients were managed by antiarrhythmic drugs or radiofrequency ablation. Fig. 4 shows a stored EGM record for a case in which therapy was inappropriately delivered to an SVT episode with 1:1 AV relationship.
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Overall, the raw positive predictive value of VT detection was 93.3% and the negative predictive value of SVT rejection was 97.8%.
On a per patient basis, the Atrial ViewTM discrimination algorithm demonstrated a 92% sensitivity and a 91% specificity. Indeed, individual appropriate detection rates were 100% in 20 patients, 90–99% in 3 patients, 87.5% in 1 patient and 50% in 2 patients.
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Discussion |
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Background and main findings
Inappropriate therapy is one of the most common adverse events in ICD patients [14]
. With the development of dual-chamber ICDs, the challenge is to decrease or eliminate inappropriate therapies, which burden the patients, and increase the potential for ventricular arrhythmia occurrence. Our results show that the sensitivity and specificity of the Atrial ViewTM algorithm are high. False positive detection of VT in the presence of SVT with 1:1 AV relationship, however, remains a problem. It is important to point out that without the use of a dual-chamber device, it would have been impossible to prove the diagnosis of such SVTs with 1:1 AV relationship. The delivered therapy, therefore, would have been considered appropriate (since antitachycardia pacing may terminate 1:1 atrial tachycardias). Consequently, the results of studies reporting similar effectiveness in dual- and single-chamber ICDs are questionable [15]. One possible explanation for why inappropriate therapies have been more commonly observed with dual-chamber ICDs is that arrhythmia interpretation and classification based on stored EGMs are more accurate with dual-chamber devices [16].
Algorithm performance
The addition of an atrial lead and its impact on arrhythmia detection is an example of technological advance that is in the process of evaluation. When evaluating the Atrial ViewTM detection algorithm, we planned to evaluate the following questions: Does the algorithm detect all VTs? When is it safe to withhold therapy? The use of sensitivity, specificity, positive and negative predictive values addresses each of these questions. Several authors have investigated the performance of dual-chamber discriminators, and similar results have been reported recently by Kühlkamp et al. [17], Sadoul et al. [18] and Theuns et al. [19] with the PR LogicTM algorithm (Medtronic Inc., Minneapolis, Minnesota, USA), the PARADTM algorithm (ELA Medical, Le Plessis Robinson, France) and the SMARTTM algorithm (Biotronik, Berlin, Germany), respectively. The reported sensitivity and specificity were 100%, 99%, 100%, and 72%, 89%, 88%, respectively. Although interesting, a comparison of different dual-chamber devices as reported by Hintringer et al. [20] is difficult since the design of their SVT–VT discrimination architecture is different. For example, Atrial ViewTM detection criteria are principally used for the classification of atrial fibrillation or flutter.
Available data on the potential benefits of dual-chamber detection algorithms, however, are contradictory [21]. Kühlkamp et al. [22] previously reported on the Atrial ViewTM dual-chamber algorithm compared with the single-chamber detection Ventak® Mini. The study focussed on a comparison of the ability of these devices to withhold therapy only for atrial fibrillation and atrial flutter. The authors concluded that although identical detection zones and stability values were used, the Atrial ViewTM algorithm did not reduce inappropriate therapies compared with the single-chamber device of the same manufacturer. They attributed the failure of the new algorithm properly to detect and withhold therapy for atrial fibrillation to atrial undersensing, decision algorithms based on the AFib threshold criterion and the weakened stability criterion in Ventak® AV devices. In fact, independently of atrial sensing problems which can be minimized by reprogramming atrial detection, the same authors [23] have shown that the ventricular response to atrial fibrillation becomes more regular (and thus more similar to VT) as ventricular rates increase. In the present study, atrial undersensing leading to inappropriate therapy was observed in only one episode of atrial fibrillation and stability programmed at 24 ms appropriately discriminated atrial fibrillation.
Clinical implication
The incidence of SVT with 1:1 AV relationship was 8% of patients and 10% of SVT episodes in our study. Our results therefore suggest the need for development of new discrimination algorithms, especially for patients with a history of tachycardias with 1:1 AV relationship. Electrogram morphology discrimination [24–27] and/or electrogram vector timing and correlation [28] offer additional approaches to improve rhythm discrimination. For example, when integrated into dual-chamber devices, morphology algorithms may enhance discrimination of SVT with 1:1 AV relationship. Such SVTs, however, present specific problems such that with any passive SVT–VT discrimination algorithm, a 100% success rate will never be achieved. A complementary approach to improve discrimination between SVT with 1:1 AV relationship and VT may consist of the use of an active algorithm that analyzes the response to ventricular pacing during tachycardia.
Limitations
The real efficacy of the Atrial ViewTM algorithm implemented in the Ventak AV ICD in comparison with a single-chamber Ventak® ICD is still unknown. A prospective study randomized between enhanced single- and dual-chamber detection could answer this question. Though this study is based on a limited number of patients, another important limitation is that the episodes analyzed were only recorded in the slowest VT zone since the Atrial ViewTM algorithm does not operate in the fast VT zone when 2 VT zones are programmed. Although the potential risk of underdetection of ventricular tachyarrhythmias is a main danger in ICD patients, some future technological advances may allow the possibility of programming detection algorithms in all programmable VT zones to increase the absolute specificity of Guidant dual-chamber ICDs.
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Conclusions |
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Using the Atrial ViewTM discrimination algorithm, the Ventak® AV attained a specificity of 89%, withholding therapy for 89% of atrial arrhythmias with ventricular responses in the VT zone. Further improvements in dual-chamber detection algorithms may lead to more accurate SVT with 1:1 AV relationship–VT discrimination.
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Acknowledgements |
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We thank all the investigators, research coordinators, and support staff who participated in the Ventak AV Clinical Investigation.
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Footnotes |
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1The Ventak AV Investigators: Scanu P. (Caen); Ponsenaille J., Mansour H. (Clermont Ferrand); Defaye P. (Grenoble); Kacet S., Klug D., Kouakam C. (Lille); Lucioni R., Canavy I., Ferraci A. (Marseille); Levy S., Ricard P. (Marseille); Davy J.M., Pons M. (Montpellier); Leenhardt A., Thomas O. (Paris); Mabo P. (Rennes); Saoudi N. (Rouen); and Babuty D., Poret P. (Tours).
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References |
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[1] Antiarrhythmics Versus Implantable Defibrillators (AVID) Investigators:. a comparison of antiarrhythmic drug therapy with implantable defibrillators in patients resuscitated from near-fatal ventricular arrhythmias. N Engl J Med 1997; 337: 1576–1583.
[2] Gregoratos G., Abrams J., Epstein A.E., Freedman R.A., Hayes D.L., Hlatky M.A., et al. ACC/AHA/NASPE 2002 Guideline update for implantation of cardiac pacemakers and antiarrhythmia devices—summary article. J Am Coll Cardiol 2002; 40: 1703–1719 A report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (ACC/AHA/NASPE Committee to update the 1998 Pacemaker Guidelines).
[3] Swerdlow C.D. Supraventricular tachycardia–ventricular tachycardia discrimination algorithms in implantable cardioverter defibrillators: state-of-the-art review. J Cardiovasc Electrophysiol 2001; 12: 606–612.[CrossRef][Web of Science][Medline]
[4] Rosenqvist M., Beyer T., Block M., den Dulk K., Minten J., Lindemans F.W., et al. Adverse events with transvenous implantable cardioverter defibrillators: a prospective multicenter study. Circulation 1998; 98: 1085–1098.
[5] Grimm W., Menz V., Hoffmann J., Timmann U., Funck R., Moosdorf R., et al. Complications of third-generation implantable cardioverter defibrillator therapy. Pacing Clin Electrophysiol 1999; 22: 206–211.[CrossRef][Medline]
[6] Nanthakumar K., Paquette M., Newman D., Deno D.C., Malden L., Gunderson B., et al. Inappropriate therapy from atrial fibrillation and sinus tachycardia in automated implantable cardioverter defibrillators. Am Heart J 2000; 139: 797–803.[Web of Science][Medline]
[7] Johnson N.J. and Marchlinski F.E. Arrhythmias induced by device antitachycardia therapy due to diagnostic nonspecificity. J Am Coll Cardiol 1991; 18: 1418–1425.[Abstract]
[8] Pinski S.L. and Fahy G.J. The proarrhythmic potential of implantable cardioverter-defibrillators. Circulation 1995; 92: 1651–1664.
[9] Sears S.F., Todaro J.F., Lewis T.S., Sotile W., Conti J.B. Examining the psychological impact of implantable cardioverter defibrillators: a literature review. Clin Cardiol 1999; 22: 481–489.[Web of Science][Medline]
[10] Schuger C.D., Jackson K., Steinman R.T., Lehmann M.H. Atrial sensing to augment ventricular tachycardia detection by the automatic implantable cardioverter defibrillator: a utility study. Pacing Clin Electrophysiol 1988; 11: 1456–1464.[Medline]
[11] Morris M.M., Marcovecchio A., KenKnight B.H., Kuehl M., Lang D.J. Retrospective evaluation of detection enhancements in dual-chamber implantable cardioverter defibrillator: implications for device programming. Pacing Clin Electrophysiol 1999; 22: 849 [Abstract].[Medline]
[12] Neuzner J., Pitschner H., Schlepper M. Programmable VT detection enhancements in implantable cardioverter defibrillator therapy. Pacing Clin Electrophysiol 1995; 18: 539–547.[CrossRef][Medline]
[13] Schaumann A., von zur Mühlen F., Gonska B.D., Kreuzer H. Enhanced detection criteria in implantable cardioverter-defibrillators to avoid inappropriate therapy. Am J Cardiol 1996; 78: 42–50.[Web of Science][Medline]
[14] O'Nunain S., Roelke M., Trouton T., Osswald S., Kim Y.H., Sosa-Suarez G., et al. Limitations and late complications of third-generation automatic cardioverter-defibrillators. Circulation 1995; 91: 2204–2213.
[15] Deisenhofer I., Kolb C., Ndrepepa G., Schreieck J., Karch M., Schmieder S., et al. Do current dual chamber cardioverter defibrillators have advantages over conventional single chamber cardioverter defibrillators in reducing inappropriate therapies? A randomized, prospective study. J Cardiovasc Electrophysiol 2001; 12: 134–142.[CrossRef][Web of Science][Medline]
[16] Greenberg R.M. and Degeratu F.T. Use of atrial and ventricular electrograms from a dual chamber implantable cardioverter defibrillator to elucidate a complex dysrhythmia. Pacing Clin Electrophysiol 1998; 21: 2002–2004.[Medline]
[17] Kühlkamp V., Wilkoff B.L., Brown A.B., Volosin K.J., Hugl B.J., Stafford W., et al. Experience with a dual-chamber implantable defibrillator. Pacing Clin Electrophysiol 2002; 25: 1041–1048.[CrossRef][Medline]
[18] Sadoul N., Jung W., Jordaens L., Leenhardt A., Santini M., Wolpert C., et al. Diagnostic performance of a dual-chamber cardioverter defibrillator programmed with nominal settings: a European prospective study. J Cardiovasc Electrophysiol 2002; 13: 25–32.[CrossRef][Web of Science][Medline]
[19] Theuns D., Klootwijk A.P., Kimman G.P., Szili-Torok T., Roelandt J.R., Jordaens L. Initial clinical experience with a new arrhythmia detection algorithm in dual chamber implantable cardioverter defibrillator. Europace 2001; 3: 181–186.
[20] Hintringer F., Schwarracher S., Eibl G., Pachinger O. Inappropriate detection of supraventricular arrhythmias by implantable dual chamber defibrillators: a comparison of four different algorithms. Pacing Clin Electrophysiol 2001; 24: 835–841.[CrossRef][Medline]
[21] Wilkoff B.L., Kühlkamp V., Volosin K., Ellenbogen K., Waldecker B., Kacet S., et al. Critical analysis of dual-chamber implantable cardioverter-defibrillator arrhythmia detection: results and technical considerations. Circulation 2001; 103: 381–386.
[22] Kühlkamp V., Doernberger V., Mewis C., Suchalla R., Bosch R.F., Seipel L. Clinical experience with the new dual chamber detection algorithms for atrial fibrillation of a defibrillator with dual chamber sensing and pacing. J Cardiovasc Electrophysiol 1999; 10: 905–915.[Web of Science][Medline]
[23] Kühlkamp V., Mewis C., Suchalla R., Bosch R.F., Doernberger V., Seipel L. Rate dependence of R–R stability during atrial fibrillation and ventricular tachyarrhythmias. Circulation 1998; 98: I-713.
[24] Duru F., Bauersfeld U., Rahn-Schonbeck M., Candinas R. Morphology discriminator feature for enhanced ventricular tachycardia discrimination in implantable cardioverter defibrillators. Pacing Clin Electrophysiol 2000; 23: 1365–1374.[CrossRef][Medline]
[25] Boriani G., Biffi M., Frabetti L., Lattuca J.J., Branzi A. Clinical evaluation of morphology discrimination: an algorithm for rhythm discrimination in cardioverter defibrillators. Pacing Clin Electrophysiol 2001; 24: 994–1001.[CrossRef][Medline]
[26] Gronefeld G.C., Schulte B., Hohnloser S.H., Trappe H.J., Korte T., Stellbrink C., et al. Morphology discrimination: a beat-to-beat algorithm for the discrimination of ventricular from supraventricular tachycardia by implantable cardioverter defibrillators. Pacing Clin Electrophysiol 2001; 24: 1519–1524.[CrossRef][Medline]
[27] Swerdlow C.D., Brown M.L., Lurie K., Zhang J., Wood M.N., Olson W.H., et al. Discrimination of ventricular tachycardia from supraventricular tachycardia by a downloaded wavelet-transform morphology algorithm: a paradigm for development of implantable cardioverter defibrillator detection algorithms. J Cardiovasc Electrophysiol 2002; 13: 432–441.[CrossRef][Web of Science][Medline]
[28] Gold M.R., Shorofsky S.R., Thompson J.A., Kim J., Schwartz M., Bocek J., et al. Advanced rhythm discrimination for implantable cardioverter defibrillators using electrogram vector timing and correlation. J Cardiovasc Electrophysiol 2002; 13: 1365–1374.
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 D. A.M.J. Theuns, A. P. J. Klootwijk, D. M. Goedhart, and L. J.L.M. Jordaens Prevention of inappropriate therapy in implantable cardioverter-defibrillators: Results of a prospective, randomized study of tachyarrhythmia detection algorithms J. Am. Coll. Cardiol., December 21, 2004; 44(12): 2362 - 2367. [Abstract] [Full Text] [PDF]
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A. Przybylski, R. Baranowski, J. J. Zebrowski, and H. Szwed Verification of implantable cardioverter defibrillator (ICD) interventions by nonlinear analysis of heart rate variability - preliminary results Europace, January 1, 2004; 6(6): 617 - 624. [Abstract] [Full Text] [PDF]
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