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Algorithm Predicts and Lengthens Pacemaker Battery Life

By HospiMedica International staff writers
Posted on 14 Nov 2025

Selecting the right pacemaker and programming its functions is critical for long-term heart rhythm management — yet battery life varies widely depending on how the device is set up. More...

With pacemakers lasting between seven and fourteen years, unnecessary functions can shorten their lifespan, leading to more frequent replacement surgeries. Researchers have now developed a modelling algorithm that helps clinicians identify which features consume the most battery power so that only essential functions are activated for each patient.

The model, created through a collaboration between the University of Leeds (Leeds, UK) and Université Grenoble Alpes (Grenoble, France), works by analyzing real-world data from pacemaker user manuals and combining it with computer simulations. It estimates how much battery power each device function uses and predicts how long the device will last under different settings. The researchers simulated various clinical scenarios to determine which features add meaningful value for specific health conditions and which may drain power without clinical necessity.

They validated the tool using real-life patient data, ensuring that the predictions reflected real-world performance. The results showed clear differences in how specific functions — such as rate regulation during activity, chamber synchronization, remote monitoring, and data storage — impact battery longevity. By switching off non-essential options, cardiologists can significantly extend battery life, delay the need for replacement surgeries, and reduce healthcare system costs. The modelling also supports more accurate device comparisons, helping clinicians choose the most suitable pacemaker based on a patient's clinical profile.

These advancements come at a time when selecting between numerous pacemaker models and programming combinations can be imprecise. By providing visibility into the battery cost of each feature, the algorithm supports more personalized care and improves shared decision-making between clinicians and patients. The research, published in PLOS One and made freely available online, provides a transparent framework that clinicians worldwide can use to guide pacemaker selection and programming.

“This is the first step towards helping doctors to decide which pacemaker to choose and which program to activate, to provide the patient with the device and battery life that they need,” said Dr. Klaus Witte, Senior Lecturer and Consultant Cardiologist in Leeds’ School of Medicine and at Leeds Teaching Hospitals NHS Trust. “This will hopefully delay battery replacements or maybe avoid them altogether - which is good for patients, the NHS and wider society as a whole.”

Related Links:
University of Leeds
Université Grenoble Alpes


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