Aims Generator longevity is the key issue for patients, and is also important for payers, yet implanters of Cardiac Implantable Electronic Devices (CIEDs) face a challenge when selecting the appropriate device since battery longevity is only known for previous generation devices and whilst projected longevities are available for current devices, these are not in comparable formats. This study presents a new framework that facilitates an estimation of longevities for all CIEDs of both previous and existing generations that could simplify personalization of the device choice. Methods Longevity can be calculated based upon a simple concept entitled the “power consumption index” (PCI = t x I/C, where t is a constant of 1 hour, I is the current required by the device and C, its battery capacity). We retrieved published data from the user manuals of all commonly used pacemakers including single chamber, dual chamber, cardiac resynchronization and leadless devices. C and the components of current I including background current (I background ) and the pacing current (I pacing ) were calculated prior to calculation of the PCI for each device. Subsequently, a set of fictitious patient pool conditions via a Monte-Carlo simulation were used to model CIED survival curves which were then compared with real-life data from the Swedish device registry of previous generation CIEDs. Finally, we modeled survival curves for current generation devices using the PCI model. Results Using the PCI approach we were able to calculate longevities for all pacemaker devices under a variety of settings. The modeled I background matched the data reported by manufacturers, and, under a variety of settings, regression analysis showed a low average error rate between industry-reported and modelled longevities (ratio: modelled longevity/industry reported longevity −1) = 0.1 ± 4.0% and 0.1 ± 0.7% for previous and existing SR/DR devices, 1.0 ± 5.0% and 0 ± 3.0% for previous and existing CRT-P, and 0 ± 4.0% for leadless pacemakers, respectively). More than 50% of the PCI and thereby a significant contributor to longevity was accounted for by I background . I pacing was the second largest contributor (20% for standard single and dual chamber devices, 30% for CRT-P and 40% for leadless devices). Certain pacing algorithms and IEGM storage considerably impacted specific devices with longevity losses of up to 1 year. The Monte-Carlo analysis demonstrated consistency between projected longevities by the PCI model and real-life data for historical devices and the calculated longevities that stemmed from this were consistent with the real-world data from Sweden. Conclusion The PCI model combining power consumption and battery capacity allows a comparison of longevity across CIEDs and programming options. Such a tool could help implanters improve personalization of device prescription for their patients and payers to make more informed decisions about tailoring device purchases and programming most appropriate for their population.
Defaye et al. (Mon,) studied this question.