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L A DiCarlo

Publications and source records attributed to L A DiCarlo.

At least 19 recordsLinked to original sources
PubMed1998

Comprehensive scheme for detection of ventricular fibrillation for implantable cardioverter defibrillators.

Implantable cardioverter defibrillators (ICDs) detect and defibrillate ventricular fibrillation (VF) and ventricular tachycardia (VT). Other therapies which use less energy are also available to terminate VT. Previous studies have shown that ICD rate schemes often misdiagnose VT as VF. In this study, an improved VF classification scheme was designed and tested, which employs the classic rate criteria plus paired signal concordance (PSC); PSC uniquely detects VF where VT and VF rates overlap (220-340 ms). Two signals from a bipolar pair (1 cm) recorded in a unipolar sense exhibit similar signal shape for concordant rhythms, such as sinus rhythm and VT, and disconcordance for VF. Once the rate criterion is met, PSC is measured by the peak normalized cross-correlation coefficient calculated over the depolarization. Variability, measured by a modified range, determined the contextual diagnosis over a passage. Sinus rhythm (20), VT (12), VF (22), atrial fibrillation (10), sinus rhythm with ventricular premature depolarizations (7), and polymorphic VT (4) passages were recorded from 38 patients. Rate-PSC was tested with unfiltered, digitized signals (1-500 Hz, 1,000 samples per second) and with filtered, downsampled signals (1-50 Hz, 100 samples per second). Sensitivity values, or percentage of correct VF detection, and specificity values, or detection of all other rhythms, were generated and compared with simulations of three commercial ICDs programmed to similar settings as rate-PSC and to nominal settings. The sensitivity values for rate-PSC with unfiltered and with filtered signals and for ICDs with 220 ms and with nominal settings were 100%, 100%, 48-80%, and 100%, respectively; the corresponding specificity values were 95%, 83%, 93%, and 7-13%, respectively. It was concluded that the rate-PSC scheme was able to reliably separate VF from other rhythms, even rhythms that have a variable morphology or variable rate. With the confidence of accurate VF detection, use of low-energy therapies for non-VF rhythms will increase device longevity and enhance patient comfort.

Computer Simulation↗
PubMed1997

Analysis of the intraventricular electrogram for differentiation of distinct monomorphic ventricular arrhythmias.

This study investigated the effectiveness of correlation waveform analysis for identifying different ventricular electrogram morphologies of multiple VTs in the same patient. Patients with implantable antitachycardia devices are commonly subject to the occurrence of more than one distinct monomorphic VT. Each of these VTs may have unique therapeutic alternatives for termination. VTs with identical and different monomorphic configurations were recorded (1-500 Hz) using distal bipolar (1 cm) and distal unipolar electrograms from the right ventricular apex. Thirty-six distinct monomorphic VTs induced in 15 patients were analyzed. Nine VTs with identical morphologies (12/12 surface ECGs) were induced twice and used as a control. A template was created for each VT induced. Correlation waveform analysis was used to compare each depolarization of all other VTs induced subsequently in the same patient. The mean correlation coefficient (p mu) of cycle-by-cycle analysis was used as a discriminant function: p mu > or = 0.95 was considered matched; and p mu < 0.95 was considered distinct. From the control population, VTs were successfully classified as identical in 9 of 9 cases (100%) using both bipolar and unipolar electrograms. VTs with different monomorphic configurations were successfully classified as being different in 31 of 33 cases (94%) using bipolar electrogram analysis and in 29 of 33 cases (88%) using the unipolar. Template matching is effective for detecting: (1) the recurrence of VTs, which are identical; and (2) the occurrence of a VT with a different configuration. This method appears effective using either unipolar or bipolar intracardiac waveforms.

Aged↗
PubMed1996

A:V = 1:1 cardiac arrhythmia detection by VA interval analysis.

Dual-chamber-sensing implantable-cardioverter defibrillators are soon expected to replace ventricular sensing devices. The addition of an atrial sensing lead will dramatically improve the specificity of arrhythmia detection. Even when using combined ventricular and atrial rate criteria, ambiguity in the case of atrial tachycardia with: anterograde conduction versus ventricular tachycardia with: retrograde conduction still remains. The introduction of dual-chamber sensing in antitachycardia devices allows for additional features, such as the measurement of atrioventricular (AV) and ventriculoatrial (VA) intervals. This study investigated relationships between AV and VA intervals to address problems arising in tachycardias with confounding 1:1 relationships. Thirty-one passages of 1:1 anterograde conduction from nine patients during atrial pacing at cycle lengths of 600-300 ms and 24 passages of 1:1 retrograde conduction from eight patients during ventricular pacing at cycle lengths of 600-300 ms were analyzed. Moving averages of three successive VA interval measurements were used to develop a criterion to be implemented into an algorithm to reduce ambiguity. Five randomly selected ventricular pacing passages were used as a training set. Upper and lower VA interval boundaries (234 ms and 132 ms) determined from the training set were used to classify 1:1 retrograde activation. To account for premature beats and outliers, the boundary criterion required 9 of 12 of the most recent moving averages to fall within the upper and lower limits. Of the 19 analyzed passages of ventricular pacing, 18 (95%) were correctly classified using the VA interval as an added feature. Of the 31 atrial pacing passages, 24 (77%) were correctly classified. Using only atrial or ventricular rates, all 1:1 tachycardias in this patient sample would be classified as ventricular tachycardia, resulting in false shocks. Specificity of diagnosis in ambiguous 1:1 tachycardias can be increased using VA interval measurements at the cost of minimum loss in sensitivity for ventricular tachycardia detection. This algorithm imposes little in additional computation for dual-chamber-sensing implantable-cardioverter defibrillators and greatly reduces the possibility of false shocks in 1:1 supraventricular tachycardias.

Algorithms↗
PubMed1996

Augmented two-channel arrhythmia detection: an efficient diagnostic method for implantable devices.

ICDs are highly effective in preventing sudden cardiac death. However, inappropriate device shocks caused by false-positive diagnoses are estimated to happen in 20% of all patients. The need for implantable electrical devices to detect with precision arrhythmias requiring therapy has spawned a variety of proposals for better means of tachycardia identification. To address this problem, the augmented two-channel arrhythmia detection (A2CAD) algorithm, a real-time scheme utilizing timing and morphology from both the atrial and ventricular channels, is introduced. The algorithm uses rate detection as a first stage and augments this with morphological signal analysis in rhythms that confound the rate only diagnoses. The software executes in real-time (online), and has been tested on 60 passages of two-channel intracardiac signals. The following arrhythmias constituted the test set: 10 AF and/or atrial flutter; 15 SVT; 16 VT; 10 ventricular flutter or VF; 5 sinus tachycardia; and 4 cases of AF concurrent with VF. Results from 60 patient cases indicate 57 (95%) of 60 success rate for A2CAD, validating its potential for implementation in future implantable devices.

Algorithms↗
PubMed1994

Discrimination of ventricular tachycardia from sinus tachycardia by antitachycardia devices: value of median filtering.

Rate and rate variation algorithms used by implantable devices designed for management of life-threatening arrhythmias have major limitations in separating physiologic sinus tachycardia (ST) from pathologic ventricular tachycardia (VT) requiring therapy. These algorithms presently utilize criteria such as simple heart rate, stability of rate, or derivative of rate (sudden onset) which assumes a gradual onset for ST and an abrupt onset for VT. An alternative method employing median filtering was designed, tested, and compared to a previously published sudden onset rate algorithm using the same data set for analysis of performance. In 50 patients, the onset of ST during exercise and onset of VT were analysed. To accommodate occasional outlying intervals which might affect rate derived by averaging, a five-cycle median filter was used to smooth heart rate. Results from using a 'fixed-interval' or a 'percent' change in the median gave better discrimination of ST and VT than previously published 'fixed-interval' or 'percent' change algorithms. The superiority of median filtering performance was validated by statistical measures.

Algorithms↗
PubMed1994

Automated analysis of spontaneously occurring arrhythmias by implantable devices. Limitations of using rate and timing features alone.

Real-time automated systems for arrhythmia analysis by implantable antitachycardia devices have been designed to incorporate two-channel rate criteria with intracavitary atrial and ventricular electrogram morphology. Because the power requirements for morphologic analysis substantially limit antitachycardia device longevity, the authors sought to develop an alternative algorithm that relies solely on rate and three newly developed timing features: onset (median ventricular rate filtering to detect abrupt onset), loss of atrioventricular (AV) sequency (premature ventricular depolarizations), and regularity-multiplicity (minimal median cycle length variation concurrent with integral [n:1] AV periodicity). This system was assessed using spontaneously occurring arrhythmias in patients undergoing electrophysiology studies. Electrograms were captured on FM tape (1-500 Hz) using biopolar catheters in the high right atrium and the left ventricular apex. In 11 patients, 25 distinct arrhythmias were analyzed, which included sinus tachycardia (ST) (1 passage), supraventricular tachycardia (SVT) (6 passages), ventricular tachycardia (VT) with concurrent sinus rhythm (16 passages), VT with concurrent atrial flutter (VT/AFl) (2 passages), and ventricular fibrillation (VF) (1 passage). The algorithm correctly diagnosed 1 of 1 episode of ST, 4 of 6 episodes of SVT, 15 of 16 episodes of VT with concurrent sinus rhythm, 0 of 2 episodes of VT/AFl, and 1 of 1 episode of VF. Ventricular tachycardia episodes were misdiagnosed as SVT because of absence of loss of AV sequency in VT onset (1 episode), presence of multiplicity between VT and AFl (1 episode), and absence of VT regularity during AFl (1 episode).(ABSTRACT TRUNCATED AT 250 WORDS)

Algorithms↗
PubMed1994

The value of rate regularity and multiplicity measures to detect ventricular tachycardia in the presence of atrial fibrillation or flutter.

The predominant cause of inappropriate therapy by implantable antitachycardia devices with pacing and nonpacing cardioverter defibrillators, is mistaking a fast ventricular response during atrial fibrillation or flutter with true ventricular tachycardia (VT). The distinction between these arrhythmias is an important consideration in addressing the problem of reducing false-positives in detection mechanisms for implantable devices. Dual chamber analysis that examines atrial and ventricular event ratios has been proposed as a solution to this problem, but would still fail in distinguishing paroxysmal VT requiring treatment from a fast but otherwise benign ventricular response during atrial fibrillation or flutter. In this study, two methods for discriminating these tachyarrhythmias were evaluated. Method 1 examined ventricular rate and rate regularity as a method for VT detection. Method 2 combined rate and regularity as well as an additional multiplicity criterion for recognition of atrial flutter with a fast ventricular response. In 20 patients, Method 1 had 100% sensitivity of VT detection and 80% specificity for detection of atrial fibrillation or flutter. Method 2 had 90% sensitivity and 90% specificity. These results suggest that use of these algorithms in future implantable devices would result in a decrease in false-positive device therapies.

Algorithms↗
PubMed1994

Digital signal processing chip implementation for detection and analysis of intracardiac electrograms.

The adoption of digital signal processing (DSP) microchips for detection and analysis of electrocardiographic signals offers a means for increased computational speed and the opportunity for design of customized architecture to address real-time requirements. A system using the Motorola 56001 DSP chip has been designed to realize cycle-by-cycle detection (triggering) and waveform analysis using a time-domain template matching technique, correlation waveform analysis (CWA). The system digitally samples an electrocardiographic signal at 1000 Hz, incorporates an adaptive trigger for detection of cardiac events, and classifies each waveform as normal or abnormal. Ten paired sets of single-chamber bipolar intracardiac electrograms (1-500 Hz) were processed with each pair containing a sinus rhythm (SR) passage and a corresponding arrhythmia segment from the same patient. Four of ten paired sets contained intraatrial electrograms that exhibited retrograde atrial conduction during ventricular pacing; the remaining six paired sets of intraventricular electrograms consisted of either ventricular tachycardia (4) or paced ventricular rhythm (2). Of 2,978 depolarizations in the test set, the adaptive trigger failed to detect 6 (99.8% detection sensitivity) and had 11 false triggers (99.6% specificity). Using patient dependent thresholds for CWA to classify waveforms, the program correctly identified 1,175 of 1,197 (98.2% specificity) sinus rhythm depolarizations and 1,771 of 1,781 (99.4% sensitivity) abnormal depolarizations. From the results, the algorithm appears to hold potential for applications such as real-time monitoring of electrophysiology studies or detection and classification of tachycardias in implantable antitachycardia devices.

Algorithms↗
PubMed1993

Automated interpretation of cardiac arrhythmias. Design and evaluation of a computerized model.

Historically, the development of computerized models that utilize the deductive methods used by clinicians for the interpretation of cardiac arrhythmias have been limited by the absence of a consistently reliable means of detecting atrial activation. In this study, a theoretical model was developed with a hierarchical organization of problem-solving strategies utilizing automated analysis of atrial activation from a commercially available esophageal pill electrode and ventricular activation from a simultaneously recorded surface electrocardiographic lead. The theoretical model was then tested in 21 patients with 1 or more of 28 distinct supraventricular and ventricular arrhythmias. Of the 641 individual cardiac cycles analyzed, 636 (99.2%) were correctly identified. The accuracy of a contextual, that is, more comprehensive, interpretation of consecutive cardiac cycles was 638/641 (99.5%). The following cardiac arrhythmias were identified: sinus rhythm, sinus bradycardia, atrial premature depolarizations, atrial flutter, and supraventricular tachycardias with normal and aberrant ventricular conduction, first-degree and second-degree heart block; junctional escape, junctional rhythm, idioventricular rhythm, ventricular premature depolarization, and ventricular tachycardia with and without retrograde activation; atrial bigeminy, atrial trigeminy, atrial couplets, ventricular bigeminy, ventricular trigeminy, and ventricular couplets. This study represents the first computerized model ever developed to incorporate the morphology and timing of atrial activation with the morphology and timing of ventricular activation for arrhythmia diagnosis. Such modeling appears to be capable of achieving accurate interpretation of spontaneous, complex clinical cardiac arrhythmias and atrioventricular relationships.

Arrhythmias, Cardiac↗
PubMed1993

Real-time arrhythmia identification from automated analysis of intraatrial and intraventricular electrograms.

Implantable cardioverter defibrillators have dramatically improved survival rates for patients at risk of sudden cardiac death, but the occurrence of inappropriate shocks remains an unresolved problem. Various means for better tachycardia detection, chiefly morphological analysis, have been proposed to address this problem. A new computerized scheme entitled Two-Channel Rate-Morphology (2CRM) was introduced. It is a real-time arrhythmia detection algorithm that combines timing and morphology information from intraatrial and intraventricular electrograms for arrhythmia diagnosis. The program 2CRM applies an initial cycle-by-cycle coding scheme followed by contextual diagnosis of underlying rhythm. The program was tested on 36 distinct passages of two-channel intracardiac signals from 30 patients. The distribution of the arrhythmias are as follows: 4 atrial fibrillation, 6 atrial flutter, 6 supraventricular tachycardia, 10 ventricular tachycardia, and 10 ventricular flutter-fibrillation. Of the analyzed 3,417 individual cardiac cycles 3,135 (91.7%) were correctly identified. Contextual diagnosis reversed 123 single-cycle errors to obtain a performance of 3,258 correct out of 3,417 (95.3%). Utilizing an uninterrupted continuous correct contextual diagnosis as indicator of successful arrhythmia detection, 2CRM obtained an accuracy of 34 out of 36 passages (94.4%).

Algorithms↗