Cardiac implantable electronic devices' longevity: A novel modelling tool for estimation and comparison

Area of Science:

• Biomedical Engineering
• Medical Device Technology
• Cardiology

Background:

• Cardiac implantable electronic device (CIED) generator longevity is crucial for patients and payers.
• Current methods lack comparable formats for projecting battery longevity across different CIED generations.
• Implanters face challenges in personalizing device selection due to inconsistent longevity data.

Purpose of the Study:

• To present a novel framework for estimating CIED longevities across all device generations.
• To simplify the personalization of CIED device choice for improved patient outcomes.
• To provide a comparable format for projected battery longevities.

Main Methods:

• Developed a 'power consumption index' (PCI) model (PCI = t x I/C) using device manual data.
• Calculated background current (Ibackground) and pacing current (Ipacing) for various CIEDs.
• Utilized Monte-Carlo simulations to model CIED survival curves and compared them with real-world registry data.

Main Results:

• The PCI model accurately calculated longevities for all pacemaker devices under various settings.
• Modeled longevities showed low average error rates compared to industry-reported data across device types.
• Background current significantly contributed to PCI, while pacing algorithms and IEGM storage impacted longevity.

Conclusions:

• The PCI model effectively compares longevity across CIEDs and programming options.
• This tool can assist implanters in personalizing device prescriptions for patients.
• Payers can utilize the PCI model for more informed decisions on device procurement and programming.