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R D Throne

Publications and source records attributed to R D Throne.

9 recordsLinked to original sources

A comparison of four new time-domain techniques for discriminating monomorphic ventricular tachycardia from sinus rhythm using ventricular waveform morphology.

Electrical management of intractable tachycardia via implantable antitachycardia devices has become a major form of therapy. Newly advanced methods of ventricular tachycardia detection propose examination of changes in intraventricular electrogram morphology in addition to or in combination with earlier rate-based detection algorithms. Unfortunately, most of the proposed morphology analysis techniques have computational demands beyond the capabilities of present devices or may be adversely affected by amplitude and baseline fluctuations of the intraventricular electrogram. We have designed four new computationally efficient time-domain algorithms for distinguishing ventricular electrograms during monomorphic ventricular tachycardia (VT) from those during sinus rhythm using direct analysis of the ventricular electrogram morphology. All four techniques are independent of amplitude fluctuations and three of the four are independent of baseline changes. These new techniques were compared to correlation waveform analysis, a previously proposed method for distinction of VT from sinus rhythm. Evaluation of these four new algorithms was performed on data from 19 consecutive patients with 31 distinct monomorphic ventricular tachycardia morphologies. Three of the algorithms performed as well or better than correlation waveform analysis but with one-tenth to one-half the computational demands.

Aged

Identification of ventricular tachycardia using intracardiac electrograms: a comparison of unipolar versus bipolar waveform analysis.

Implantable antitachycardia devices suffer a high false-positive rate of delivery of therapy because current detection schemes based upon ventricular rate and rate variations are excessively sensitive at the cost of specificity. Several methods have been proposed for providing complementary information derived from morphologic analysis of intraventricular electrograms in order to increase specificity. The majority of these techniques have utilized bipolar electrogram analysis to detect changes in ventricular activation indicative of ventricular tachycardia. Whether bipolar or unipolar intracardiac electrogram analysis might be preferred for discriminating ventricular tachycardia from sinus rhythm has not been determined. In this study, a previously demonstrated method for identification of ventricular tachycardia using intracardiac electrograms, correlation waveform analysis, was used to analyze both unipolar and bipolar signals during sinus rhythm and ventricular tachycardia recorded during electrophysiology studies of 15 patients with inducible sustained monomorphic ventricular tachycardia. Correlation waveform analysis consistently discriminated between all depolarizations during ventricular tachycardia in 14/15 patients (93%) using either electrogram configuration; 13 of the 14 patients were common to both groups. Of these patients, 8/15 (53%) had greater separation between sinus rhythm and ventricular waveforms with bipolar electrogram analysis while 7/15 (47%) had greater separation with unipolar electrogram analysis. We conclude that morphologic analysis of unipolar and bipolar electrograms may be equally effective in distinguishing ventricular tachycardia from sinus rhythm. For individual patients, either a unipolar or bipolar ventricular configuration may be preferable, and should be chosen on a patient-specific basis during electrophysiology study prior to antitachycardia device implantation.

Adult

A time-domain analysis of intracardiac electrograms for arrhythmia detection.

The analysis of intracardiac electrogram morphology has been proposed as a complementary method for accurate discrimination between sinus rhythm (SR), supraventricular dysrhythmias, and ventricular dysrhythmias by automatic antitachycardia and cardioverter defibrillator devices. In this study, the performance of a traditional time-domain method for surface electrocardiogram interpretation--Correlation Waveform Analysis (CWA) and a newly developed technique--Bin Area Method (BAM) were used to analyze unfiltered intraatrial and intraventricular electrograms obtained from 47 patients during routine cardiac electrophysiology studies. Nineteen patients had 31 distinct, sustained, monomorphic ventricular tachycardias (VTs) induced; 13 patients had paroxysmal bundle branch block of supraventricular origin (BBB) induced; 19 patients had retrograde atrial activation during ventricular overdrive pacing. Three patients were common to two or more groups. Using a best fit electrogram alignment, both CWA and BAM distinguished VT from SR in 28/31 cases (90%), BBB from SR in 15/15 patients (100%), and anterograde from retrograde atrial activation in 19/19 patients (100%). We conclude that the use of time-domain techniques that are independent of amplitude and baseline fluctuations appear to be reliable for discrimination of retrograde atrial activation, paroxysmal BBB, and VT from SR using intracardiac electrograms. Reduction of computational time and power constraints, without sacrificing reliable dysrhythmia discrimination, is possible. These features may make real-time morphology analysis of intracardiac electrograms feasible for automatic antitachycardia and cardioverter-defibrillator devices.

Algorithms

The Bin Area Method: a computationally efficient technique for analysis of ventricular and atrial intracardiac electrograms.

Recent studies have reported a significant false positive rate in delivery of therapy by implantable antitachycardia devices utilizing detection algorithms based on sustained high rate. More selective decision schemes for the recognition of life-threatening arrhythmias have been recently proposed that use analysis of the intrinsic electrogram rather than rate alone. Morphological discrimination of abnormal electrograms using correlation waveform analysis (CWA) has been proposed as an effective method of intracardiac electrogram analysis, but its computational demands limit its use in implantable devices. A new method for intracardiac electrogram analysis, the bin area method (BAM), was created to detect abnormal cardiac conduction with computational requirements of one-half to one-tenth those of CWA. Like CWA, BAM is a template matching method that is sensitive to conduction changes revealed in the electrogram morphology and is independent of amplitude and baseline fluctuations. Performance of BAM and CWA were compared using bipolar right ventricular and right atrial electrode recordings from 47 patients undergoing clinical cardiac electrophysiology studies. Nineteen patients had 31 distinct monomorphic ventricular tachycardias (VTs) induced (group I), thirteen patients had paroxysmal bundle branch block of supraventricular origin (BBB) induced (group II), and 19 patients had retrograde atrial activation during right ventricular overdrive pacing (group III). (One patient was common to all three groups, and two patients were common to groups II and III.) Using the ventricular electrogram, both BAM and CWA distinguished VT from sinus rhythm in 28/31 (90%) cases, and BBB from Normal Sinus Rhythm (NSR) in 13/13 (100%) patients. Using the atrial electrogram, both BAM and CWA distinguished anterograde from retrograde atrial activation in 19/19 (100%) patients. BAM achieves similar performance to CWA with significantly reduced computational demands, and may make real-time analysis of intracardiac electrograms feasible for implantable pacemakers and antitachycardia devices.

Algorithms

Paroxysmal bundle branch block of supraventricular origin: a possible source of misdiagnosis in detecting ventricular tachycardia using time domain analyses of intraventricular electrograms.

Current implantable antitachycardia devices use several methods for differentiating sinus rhythm (SR) from supraventricular tachycardia (SVT) or ventricular tachycardia (VT). These methods include sustained high rate, the rate of onset, changes in cycle length, and sudden onset. Additional methods for detecting VT include techniques based upon ventricular electrogram morphology. The morphological approach is based on the assumption that the direction of cardiac activation, as sensed by a bipolar electrode in the ventricle, is different when the patient is in SR as compared to VT. Whether paroxysmal bundle branch block of supraventricular origin (BBB) can be differentiated from VT has not been determined. In this study, we compared the morphology of the ventricular electrogram during sinus rhythm with a normal QRS (SRNIQRS) or SVT with a normal QRS (SVTNIQRS) with the morphologies of BBB and VT in 30 patients undergoing cardiac electrophysiology studies. Changes in ventricular electrogram morphology were determined using three previously proposed time domain methods for VT detection: Correlation Waveform Analysis (CWA), Area of Difference (AD), and Amplitude Distribution Analysis (ADA). CWA, AD, and ADA distinguished VT from SRNIQRS or SVTNIQRS in 16/17 (94%), 14/17 (82%), and 12/17 (71%) patients, and BBB from SRNIQRS or SVTNIQRS in 15/15 (100%), 13/15 (87%), and 6/15 (40%) patients, respectively. However, the ranges of values during BBB using these methods overlapped with ranges of values during VT in all cases for CWA, AD, and ADA. Hence, BBB may be a source of misdiagnosis in detecting VT when these time domain methods are used for ventricular electrogram analysis.

Adolescent

Intraventricular electrogram analysis for ventricular tachycardia detection: statistical validation.

Time-domain analysis of intraventricular electrogram morphology during ventricular tachycardia (VT) and sinus rhythm or atrial fibrillation (SR/AF) has been proposed as a method for increasing the specificity of pathological tachycardia detection by antitachycardia devices. However, few studies have validated the use of such analysis with statistical methods. When statistical methods have been utilized, it has been assumed that the distribution of the values derived from analysis of the intracardiac electrograms have had a normal (gaussian) distribution. In this study, we sought to determine whether: (1) the distribution of values derived from analysis of intracardiac electrogram during SR/AF and VT is gaussian or nongaussian; and (2) the discrimination of monomorphic VT from SR/AF using SR/AF templates can be validated statistically. Two previously proposed time-domain methods--correlation waveform analysis (CWA) and area of difference (AD)--were selected for evaluation of 29 patients with 33 distinct, sustained monomorphic VTs. An initial SR/AF template was used to analyze subsequent SR/AF and VT passages with a minimum of 50 consecutive depolarizations using a "best-fit" alignment. The values derived from each analysis were examined subsequently for skewness (asymmetry) and kurtosis (shape) using two-tailed tests (P less than 0.02). For passages of SR/AF, a normal (gaussian) distribution was present in only 24% (CWA), and 45% (AD); for passages of VT, normal distribution was present in only 58% for both CWA and AD. Using appropriate statistical testing with nonparametric tolerance intervals, CWA and AD discriminated VT from SR/AF in 29 out of 33 (88%), and 30 out of 33 (91%) instances, respectively, with 95% confidence.(ABSTRACT TRUNCATED AT 250 WORDS)

Atrial Fibrillation

Discrimination of retrograde from anterograde atrial activation using intracardiac electrogram waveform analysis.

The prevention of pacemaker-mediated tachycardias requires a safe, reliable method for distinguishing retrograde from anterograde atrial activation by dual chamber pacemakers. In this study, a technique was developed to detect the morphological change that occurs in the waveform of the intra-atrial electrogram during retrograde atrial activation. The method employed for waveform analysis is based upon statistical correlation. In 19 patients undergoing electrophysiological studies, atrial electrograms were recorded from bipolar endocardial electrodes during sinus rhythm and 1:1 retrograde atrial depolarization while undergoing right ventricular pacing. Data were digitally sampled at 750, 1,000, and 1,500 Hz. Templates of anterograde atrial depolarization were constructed by signal averaging waveforms from an initial sinus rhythm passage. These were used for analysis of anterograde depolarizations from a subsequent passage of sinus rhythm and a passage of known retrograde atrial depolarization. In all 19 cases, a patient-specific threshold could be derived to separate anterograde from retrograde atrial depolarizations using 1,000 Hz and 1,500 Hz sampling rates. However, at a sampling rate of 750 Hz, separation of anterograde from retrograde atrial activation was possible in only 16/19 patients (84%). We conclude that correlation waveform analysis of a suitably sampled atrial electrogram is a reliable method of discriminating retrograde atrial depolarization from anterograde atrial depolarization in intracardiac electrograms.

Adult