Biomedical subjects

W J Gibb

Publications and source records attributed to W J Gibb.

7 recordsLinked to original sources

PubMed1996

Modeling triggered cardiac activity: an analysis of the interactions between potassium blockade, rhythm pauses, and cellular coupling.

It is known that under certain conditions, a combination of potassium channel blockade, sympathetic nervous activity, and pauses in sinus rhythm can increase the occurrence of cardiac arrhythmias. Although the arrhythmogenic interactions of these three factors are not completely understood, it is believed that the associated arrhythmias may be initiated by afterpotentials via a process that we refer to as propagated triggered activity. Using a two-cell computational model of ventricular action potential kinetics, we simulate nonuniform potassium blockade, sympathetic nervous activity, and pauses in sinus rhythm under conditions of hypokalemia. Under these conditions, the two-cell model suggests that (1) the arrhythmogenic interactions of potassium blockade and sympathetic nervous activity are highly dependent on heart rate; (2) triggered activity induced by potassium blockade would most likely occur during a pause in sinus rhythm; (3) during a sufficiently large pause in sinus rhythm, potassium blockade can induce triggered activity at normal levels of sympathetic activity; and (4) potassium blockade can increase the probability of triggered activity only if heart rate falls within a critical range. We also show that during pauses in sinus rhythm, two-cell triggering interactions between potassium blockade and sympathetic activity closely parallel the parametric displacement of the dynamic instability underlying the afterpotentials. Our results indicate that the behavior of the triggering mechanism studied here is consistent with that of pause-induced arrhythmias.

Action Potentials↗

PubMed1995

A model study of propagation of early afterdepolarizations.

Early afterdepolarizations (EAD's) are irregularities of the cardiac action potential that interrupt or retard repolarization. EAD's have been linked to the development of specific types of cardiac arrhythmias, however, the mechanism underlying the development of these arrhythmias remains unclear. We implemented a two-element kinetic model of the ventricular action potential to investigate a potentially arrhythmogenic form of triggered activity. By approximating EAD's by a sinusoidal driving force, we were able to study the effects of interelement coupling resistivity and sinusoidal frequency and amplitude on the triggering of action potentials. We demonstrated EAD's in a ventricular action potential model by altering the potassium and calcium channels to simulate experimental conditions under which EAD's occur. We also found that triggered activity depends critically on the frequency and amplitude of the driving force and also on the degree of cellular uncoupling between the elements. Our results suggest that triggered activity (due to EAD's) may be suppressed by drugs that improve coupling in unhealthy tissue, or ones that prevent EAD formation by inhibiting calcium channels.

Action Potentials↗

PubMed1994

Effects of simulated potassium blockade on the dynamics of triggered cardiac activity.

Under certain conditions, drugs that partially block transmembrane potassium currents in ventricular myocytes predispose patients to ventricular tachyarrhythmias. Although the precise mechanisms by which potassium blockade initiates tachyarrhythmias are unknown, it is believed that early afterdepolarizations (EADs) may play a role. Using the Luo-Rudy kinetic model of the ventricular action potential, we examine the effect of potassium blockade on the likelihood of observing triggered cardiac activity in a system of two coupled kinetic patches. We found that (i) phase 2 EADs are capable of triggering full action potentials in neighboring tissue if the patches are separated by a relatively large resistive barrier, and (ii) partial potassium blockade can either increase or decrease triggering probabilities depending on coupling resistivity. To understand the dynamic contribution of potassium blockade to triggered activity, the two-patch model is decomposed into two single patches. In one of the patches we compute the stability properties of simulated EADs (arising from phase 2 of the ventricular action potential) as a function of potassium blockade. The EAD stability properties are then related to the frequency-amplitude response of the neighboring patch. From the analysis of the decomposed system we found (iii) that increases in triggering probabilities brought about by potassium blockade may result from frequency and amplitude shifts of stable EAD oscillations. The first finding suggests a mechanism by which potassium blockade could induce EAD-triggered arrhythmias within the setting of chronic myocardial infarction. The second and third findings may partially explain why potassium blockade is antiarrhythmic in some patients, and proarrhythmic in others.

Action Potentials↗

PubMed1994

Adaptive classification of myocardial electrogram waveforms.

The shape of myocardial electrogram complexes can change gradually in response to electrical and physiological transients. These changes could affect the reliability of morphologic-based electrogram classifiers proposed for use in implantable cardioverters. In this report, we present a method of detecting gradual changes in the shape of electrogram complexes and evaluate the method by incorporating it into a simple adaptive classification scheme. Of the six subjects recruited to take part in a previous comparative study of myocardial electrogram features, we observed extensive morphologic drift of normal sinus beats in two subjects. Our results indicate that the adaptive classification scheme proposed here can reduce observed classification error rates compared to rates obtained without adaptation.

Algorithms↗

PubMed1993

Selection of myocardial electrogram features for use by implantable devices.

Implantable devices that terminate ventricular tachycardia must be capable of correctly classifying heart rhythms to a high degree of reliability. We evaluated the relative discriminating power of several myocardial electrogram (ME) features in six human subjects by reducing the order of their corresponding feature spaces using three different optimization methods: 1) minimizing univariate Bayes error rates (univariate parametric), 2) maximizing the Kullback divergence (multivariate parametric), and 3) pruning classification trees (nonparametric). We found that although the composition of the optimal subspaces varied considerably from one subject to another, one frequency domain feature was common to most of the optimal subspaces.

Bayes Theorem↗

PubMed1991

Aging effects on heart rate variation.

Heart rate variation was studied in 56 healthy subjects from ages 20-81 while supine and standing during spontaneous and metronome breathing. Time domain analyses revealed no age effect on supine heart rate but standing heart rate decreased with aging (p less than .008). The SD of R-R intervals decreased with increasing age in both positions (p less than .001). Frequency domain analysis (Fast Fourier Transformation of R-R interval data) showed total spectral content to decrease with aging (p less than .001). Both high frequency (0.20-0.32 Hz) and low frequency (0.04-0.12 Hz) content were reduced with aging (p less than .001). The ratio of high to low frequency content, however, was not affected by age in the supine position nor were changes in this ratio in response to standing during spontaneous breathing. Although the absolute increase in low frequency content upon standing was less with aging (p less than .001), the percent increase in low frequency content was not related to age. Metronome breathing decreased total spectral content (p less than .001) but increased high frequency content, especially in younger subjects (p less than .03). In response to standing, greater proportional and absolute decreases in high frequency content occurred in younger subjects resulting in age differences in the changes in ratios of high to low frequency content with standing during metronome breathing. In summary, decreased heart rate variation was seen with aging, but the balance between parasympathetic and beta-adrenergic input at rest and in response to postural changes does not appear to be influenced by age during spontaneous breathing. Metronome breathing altered spectral content within subjects and produced age-related differences in responses to postural maneuvers not seen during spontaneous breathing.

Adult↗

PubMed1988

Identification of ventricular tachycardia with use of the morphology of the endocardial electrogram.

Currently available antitachycardia devices rely primarily on timing information to define abnormal rhythms. It would be useful to have more specific means of automatically identifying pathologic tachycardias. Using unfiltered (0.04 to 500 Hz bandpass) recordings made during electrophysiologic testing in 10 patients with ventricular tachycardia (VT), we studied the differences in electrogram morphology during sinus rhythm and VT. Signals were digitized at 1 kHz. A template of a normal sinus rhythm electrogram was created for each patient by averaging five sinus complexes from the beginning of each study. Ten sinus electrograms just before the onset of VT and 10 electrograms during stable monomorphic VT were compared with this template. The difference in morphology between a given electrogram and its template was quantitated by superimposing the two signals and measuring the area between the curves. There was no overlap in the ranges of these "area of the difference" measurements between sinus and VT electrograms from any of the 10 patients studied, including four with intraventricular conduction disturbances. In contrast, discrete features of the signal, including peak amplitude and maximum dV/dt, did not reliably differentiate sinus from VT electrograms. Bandpass filtering, sample window size, and digitizing rate were manipulated to determine the minimal signal content necessary for the area of difference method to reliably identify VT. These interventions suggest that the low-frequency far-field portion of the signal is primarily responsible for the morphologic differences between sinus and VT electrograms. In conclusion, the morphology of VT electrograms in man is consistently and distinctly different from the morphology of sinus electrograms.(ABSTRACT TRUNCATED AT 250 WORDS)

Electrocardiography↗