The ventricular defibrillation and upper limit of vulnerability dose-response curves

Simultaneous comparison of many triphasic defibrillation waveforms

Biphasic defibrillation waveforms are now accepted as being more effective at terminating ventricular fibrillation (VF) than monophasic waveforms. If two phases are better than one, this naturally leads to the hypothesis that additional phases improve efficacy. This study tests the hypothesis by adding one additional phase. We examined the efficacy of 18 different triphasic waveforms simultaneously.

We tested the rate of recovery, i.e., successful defibrillation, of 21 guinea pigs (820-1,050 g) using triphasic, monophasic and biphasic defibrillation waveforms. The biphasic and monophasic were control waveforms. VF was electrically induced twenty times per animal and a single defibrillation attempt was made using a test waveform VF episode. Every waveform was adjusted to the energy required to defibrillate that animal 50% of the time, using a biphasic waveform as a control. The success rate of each triphasic waveform was pair-wise compared to the biphasic and monophasic control using the adjusted McNemar statistical test.

Of the 18 triphasic waveforms tested, two were significantly poorer than the monophasic control (p<0.05). One was superior to the biphasic waveform (p<0.1), but not statistically so. We concluded that, while adding a phase to a monophasic waveform does improve efficacy, adding an additional phase to a biphasic waveform does not necessarily improve efficacy.

Mechanisms of defibrillation

Electrical shock has been the one effective treatment for ventricular fibrillation for several decades. With the advancement of electrical and optical mapping techniques, histology, and computer modeling, the mechanisms responsible for defibrillation are now coming to light. In this review, we discuss recent work that demonstrates the various mechanisms responsible for defibrillation. On the cellular level, membrane depolarization and electroporation affect defibrillation outcome. Cell bundles and collagenous septae are secondary sources and cause virtual electrodes at sites far from shocking electrodes. On the whole-heart level, shock field gradient and critical points determine whether a shock is successful or whether reentry causes initiation and continuation of fibrillation.

The dilemma of ICD implant testing

Ventricular fibrillation (VF) has been induced at implantable cardioverter defibrillator (ICD) implant to ensure reliable sensing, detection, and defibrillation. Despite its risks, the value was self-evident for early ICDs: failure of defibrillation was common, recipients had a high risk of ventricular tachycardia (VT) or VF, and the only therapy for rapid VT or VF was a shock. Today, failure of defibrillation is rare, the risk of VT/VF is lower in some recipients, antitachycardia pacing is applied for fast VT, and vulnerability testing permits assessment of defibrillation efficacy without inducing VF in most patients. This review reappraises ICD implant testing. At implant, defibrillation success is influenced by both predictable and unpredictable factors, including those related to the patient, ICD system, drugs, and complications. For left pectoral implants of high-output ICDs, the probability of passing a 10 J safety margin is approximately 95%, the probability that a maximum output shock will defibrillate is approximately 99%, and the incidence of system revision based on testing is < or = 5%. Bayes' Theorem predicts that implant testing identifies < or = 50% of patients at high risk for unsuccessful defibrillation. Most patients who fail implant criteria have false negative tests and may undergo unnecessary revision of their ICD systems. The first-shock success rate for spontaneous VT/VF ranges from 83% to 93%, lower than that for induced VF. Thus, shocks for spontaneous VT/VF fail for reasons that are not evaluated at implant. Whether system revision based on implant testing improves this success rate is unknown. The risks of implant testing include those related to VF and those related to shocks alone. The former may be due to circulatory arrest alone or the combination of circulatory arrest and shocks. Vulnerability testing reduces risks related to VF, but not those related to shocks. Mortality from implant testing probably is 0.1-0.2%. Overall, VF should be induced to assess sensing in approximately 5% of ICD recipients. Defibrillation or vulnerability testing is indicated in 20-40% of recipients who can be identified as having a higher-than-usual probability of an inadequate defibrillation safety margin based on patient-specific factors. However, implant testing is too risky in approximately 5% of recipients and may not be worth the risks in 10-30%. In 25-50% of ICD recipients, testing cannot be identified as either critical or contraindicated.

Mechanistic enquiry into the effect of increased pacing rate on the upper limit of vulnerability

The goal of this study is to investigate the mechanisms responsible for the increase in the upper limit of vulnerability (ULV; highest shock strength that induces arrhythmia) following the increase in pacing rate. To accomplish this goal, the study employs a three-dimensional bidomain finite element model of a slice through the canine ventricles. The preparation was paced eight times at a basic cycle length (BCL) of either 80 or 150ms followed by delivery of shocks of various strengths and timings. Our results demonstrate that the shock strength, which induced an arrhythmia 50% of the time, increased 20% for the faster pacing compared to the slower pacing. Analysis of the mechanisms underlying the increased vulnerability revealed that delayed post-shock activations originating in the tissue depths appear as breakthrough activations on the surfaces of the preparation following an isoelectric window (IW). However, the IW duration was consistently shorter in the faster-paced preparation. Consequently, breakthrough activations appeared on the surfaces of this preparation earlier, when the tissue was less recovered, resulting in higher probability of unidirectional block and reentry. This explains why shocks of the same strength were more likely to result in arrhythmia induction when delivered to a preparation that was rapidly paced.

Effect of stress induced by electrical stimulation of the hypothalamus on the electrical stability of the heart in rabbits

The influence of stress on cardiac electrical stability (CES) and chaotic dynamics of the electrical activity of the heart was studied in acute and chronic experiments in rabbits. Stress was caused by 2-3 h daily immobilization of the animals with electrical stimulation of emotiogenic centers of the hypothalamus through implanted electrodes. CES was estimated by the thresholds for ventricular arrhythmia: paroxysmal ventricular tachycardia, repeated ventricular extrasystoles and ventricular fibrillation (VF). The results showed: (i) CES in stressed rabbits was decreased significantly compared with controls; (ii) the level of chaos at the onset of VF in stressed rabbits was increased significantly compared with controls; (iii) heart rate of stressed rabbits was significantly greater than in controls; (iv) changes in CES parameters depended on whether stress was acute or chronic; (v) acute stress promoted transition of spontaneously reversible VF into spontaneously irreversible VF. Thus, stress increased the degree of disorganization of heart electrical activity and also decreased its electrical stability. The experiments indicate that stress is a destabilizing factor influencing the reversibility of heart rate disorders. The probability of such reversibility depends on whether stress is acute or chronic: acute stress is more likely to lead to irreversible spontaneous VF.

Hemodynamic collapse, geometry, and the rapidly paced upper limit of ventricular vulnerability to fibrillation by T-wave stimulation

There is an upper limit to the vulnerability (ULV) of the ventricles to fibrillation (VF) induced by T-wave stimuli. Across species, disease states, and pharmacological treatments, the ULV is correlated to the defibrillation threshold (DF50). However, one factor known to increase the ULV far above the DF50 is rapid pacing. In this article we test the hypothesis that this increase is owing to an accompanying hemodynamic collapse or geometric change. In 18 dogs, T-wave stimuli were delivered from transvenous defibrillating electrodes. The T-wave shock strength that induced VF 50% of the time (the ULV50) was measured using a 10-step Bayesian up-down protocol. T-wave stimuli were delivered after 15 paced beats at one of several rates: normal (80% of the R-R interval), rapid (the interval just fast enough to cause hemodynamic collapse), or 10 milliseconds greater than rapid (which did not cause hypotension). We measured the geometry of the left ventricle at the moment of T-wave stimulation using linear ultrasound. Rapid pacing significantly increased the ULV50 above the normal rate ULV (507 +/- 62.9 vs 379 +/- 70.6 V, P < .005, n = 18), even in the subset without hemodynamic collapse (505 +/- 84.4 vs 394 +/- 66.5 V, P < .005, n = 6). No significant geometric changes were noted between rapid (19.8 mm) and normal (20.6 mm, n = 6, P < NS) pacing, but QT interval reduction appears to correlate with the ULV50 (QT vs ULV50, r > 0, P < .01). Rapid pacing can dramatically increase the measured ULV50. The most likely cause is a concurrent change in the electrophysiology, eg, QT or APD, of the myocardium. As the only known factor to consistently alter the relationship between ULV and the DF50, rapid pacing offers a unique opportunity for the study of the link between defibrillation and ULV testing.

A four-shock Bayesian up-down estimator of the 80% effective defibrillation dose

INTRODUCTION

New defibrillation techniques are often compared to standard approaches using the defibrillation threshold. However, inference from thresholding data necessitates extrapolation from reactions to relatively ineffective shocks, an error prone procedure requiring large sample sizes for hypothesis testing and large safety margins for defibrillator implantation. In contrast, this article presents a clinically validated statistical model of a minimum error, four-shock defibrillation testing protocol for estimating the 80% effective defibrillation strength for a given patient (ED80).

METHODS AND RESULTS

A Bayesian statistical model was constructed assuming that the defibrillation dose-response curve is sigmoidal, and the ED80 is between 150 and 750 V. The model was used to design a minimum predicted error testing protocol and estimates. To prospectively validate the testing protocol and estimates, 170 patients received voltage-programmed biphasic testing. Four fibrillation episodes were induced and terminated in each patient according to the Bayesian up-down protocol. In addition, a validation attempt was made at the estimated ED80 rounded up to the nearest 50 V. In order to estimate the safety margin, in 136 patients, a defibrillation attempt was made at the rounded ED80 + 100 V. Of the 170 attempts at the rounded ED80, 143 (84%) attempts terminated fibrillation. Of the 136 attempts at the rounded ED80 + 100 V, 133 (98%) were effective.

CONCLUSIONS

The four-shock Bayesian up-down protocol is the first clinical protocol to accurately predict an ED80 voltage. A 100 V increment above the ED80 provides an adequate safety margin. This simple and accurate method for estimating a highly effective defibrillation dose may be a valuable tool for population-based clinical hypothesis testing, as well as defibrillator implantation.