Optimal Implantable Cardioverter Defibrillator (ICD) Generator Replacement

Implantable cardioverter defibrillators (ICDs) include small, battery-powered generators, the longevity of which depends on a patient's rate of consumption. Generator replacement, however, involves risks, including death. Hence, a trade-off exists between prematurely exposing the patient to these risks and allowing for the possibility that the device is unable to deliver therapy when needed. Currently, replacements are performed using a one-size-fits-all approach. Here, we develop a Markov decision process model to determine patient-specific optimal replacement policies as a function of patient age and the remaining battery capacity. We analytically establish that the optimal policy is of threshold-type in the remaining capacity, but not necessarily in patient age. Based on clinical data, we conduct a large computational study that suggests that under the optimal policy, patients undergoing initial implantation at age 30–40, 41–60, and 61–80 see an approximate decrease in the total expected number of replacements of 8%–14%, 8%–15% and 8%–19%, respectively, while achieving the same or greater expected lifetime.