Evidence map›Paper›PMID 41021628›Full record

ArticlePloS one2025

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

Pascal Defaye, Serge Boveda, Jean-Renaud Billuart, Klaus K Witte, Maria F Paton

Abstract readComparative Study
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Pascal DefayeUniversity Hospital of Grenoble-Alpes, Grenoble, France.ORCID 0000-0002-7183-4278
Serge BovedaClinique Pasteur, Toulouse Cedex 3, France.ORCID 0000-0002-1280-7042
Jean-Renaud BilluartMicroPort CRM, Clamart, France.
Klaus K WitteLeeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom.ORCID 0000-0002-7146-7105
Maria F PatonLeeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom.ORCID 0000-0001-8517-4621

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsGenerator 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.

methodsLongevity 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 (Ibackground) and the pacing current (Ipacing) 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.

resultsUsing the PCI approach we were able to calculate longevities for all pacemaker devices under a variety of settings. The modeled Ibackground 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 Ibackground. Ipacing 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.

conclusionThe 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.

Indexed as

Defibrillators, ImplantablePacemaker, ArtificialHumansMonte Carlo Method

Identifiers

PMID41021628
PMCPMC12478916

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.