The Defibrillation Success Rate Versus Energy Relationship: Part I‐Curve Fitting and the Most Efficient Defibrillation Energy

The effect of applying an energy pulse to the heart during ventricular fibrillation is described by the probability of successful defibrillation or success rate. Seven to ten (8.60 ± 0.84: mean ± standard deviation) defibrillation trials per energy were randomly attempted at energies which span the defibrillation success rate versus energy curve. We obtained 70.0 ± 8.4 episodes per dog. We fit the defibrillation success rate versus energy relationship from ten dogs (20.5 y1.5 kg) to four types of curves: linear, exponential, profit transformed linear, and logic transformed linear. The correlation coefficients for each fit are 0.957 ± 0.057,0.944 ±0.014, 0.926± 0.051, and 0.889 ± 0.098. respectively. We therefore conclude that the exponential curve best describes the DSRE relationship. This suggests the existence of an energy below which defibrillation does not occur. At higher energies, the exponential curve asymptotically approaches a 100% success rate, which indicates that increasing the energy produces a diminishing benefit to defibrillation success rate. The estimated energies with a 0% defibrillation success rate are surprisingly consistent among dogs, with 2.072 ± 0.553 J. The estimated energy with an 80% defibrillation success rate is 5.217 ± 1.091 J. The estimated defibrillation success rate corresponding to the defibrillation threshold of 3.59 ± 3.06 J is consistent with 0.516 ± 0.144. The estimated energies with a 0% success rate correlate well with the defibrillation thresholds with R = 0.772; P = 0.0088. Since implant able defibrillators have a limited energy supply, we determined energy efficiency by dividing defibrillation success rate by the applied energy and energy consumption by dividing the applied energy by the defibrillation success rate. The most efficient defibrillation energy occurs at the maximum energy efficiency and the minimum energy consumption. The most efficient defibrillation energy of 4.34 ± 0.97 J determined from the exponential fit has a success rate of 0.70 ± 0.06. The most efficient defibrillation energy can be predicted from the defibrillation threshold. Clinically, a 70% success rate may not be adequate. We, therefore, compared the energy efficiency and consumption of energies with 90% and 95% success rates to the most efficient defibrillation energy. About a 50% increase in energy from the most efficient defibrillation energy is necessary for a 90% success rate which results in about a 33% loss in energy efficiency and about a 16% increase in energy consumption. About an 84% energy increase is necessary for a 95% success rate which results in about a 24% loss in energy efficiency and about a 33% increase in energy consumption. For these energies, the benefit to success rate may outweigh the decrease in energy efficiency and may be more appropriate clinically. A prudent choice of energy setting for the AICD must include careful consideration of energy efficiency and consumption.