Evidence map›Paper›PMID 42502885›Full record

ArticlePacing and clinical electrophysiology : PACE2026

Variability in Pacemaker Battery Estimates and Performance.

Benjamin A Steinberg, Riley Gillette, Michael Torre, Prashanthan Sanders, Niraj Varma, Tina Baykaner, Thomas Deering, Andrea M Russo, Yue Zhang, Yaxu Zhuang and 1 more

Abstract read
In one paragraph

Article in Pacing and clinical electrophysiology : PACE, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Benjamin A SteinbergDepartment of Medicine, Denver Health Medical Center, Denver, Colorado, USA.ORCID https://orcid.org/0000-0002-4729-7820
Riley GilletteDepartment of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA.
Michael TorreDepartment of Medicine, University of Utah Health Sciences Center, Salt Lake City, Utah, USA.
Prashanthan SandersCentre For Heart Rhythm Disorders (CHRD), University of Adelaide and Royal Adelaide, Hospital, Adelaide, Australia.ORCID https://orcid.org/0000-0003-3803-8429
Niraj VarmaDepartment of Medicine, Cleveland Clinic, Cleveland, Ohio, USA.
Tina BaykanerDepartment of Medicine, Stanford University, Stanford, California, USA.
Thomas DeeringPiedmont Heart Institute, Atlanta, Georgia, USA.ORCID https://orcid.org/0000-0002-6046-5083
Andrea M RussoCooper Medical School of Rowan University, Camden, New Jersey, USA.
Yue ZhangDepartment of Medicine, University of Utah Health Sciences Center, Salt Lake City, Utah, USA.
Yaxu ZhuangDepartment of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA.
James V FreemanDepartment of Medicine, Yale University School of Medicine, New Haven, Connecticut, USA.

Funding

Safety and Effectiveness of Left Atrial Appendage Closure in Atrial Fibrillation (SAFELY-AF)R01HL142765 · NHLBI · YALE UNIVERSITY · PI FREEMAN, JAMES · 2019 to 2022
$2.9M
Personalized Stroke Risk Stratification in Atrial Fibrillation: Integrating Probabilistic Graphical Models and High-dimensional EHR Data for Interpretable PrognosisR01HL177105 · NHLBI · DENVER HEALTH AND HOSPITAL AUTHORITY · PI BENJAMIN ADAM STEINBERG · 2025 to 2026
$1.1M
Personalized Risk Stratification in Atrial Fibrillation using Portable, Explainable Artificial IntelligenceR56HL168264 · NHLBI · UNIVERSITY OF UTAH · PI STEINBERG, BENJAMIN ADAM · 2023 to 2023
$684k
Overcoming explainability and data availability barriers to broad application of ECG ML screening with a system-wide ECG datasetR21HL172288 · NHLBI · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI STEINBERG, BENJAMIN ADAM, TASDIZEN, TOLGA · 2024 to 2025
$231k
NHLBI NIH HHS R01 HL142765NHLBI NIH HHS R01 HL177105NHLBI NIH HHS R21 HL172288NHLBI NIH HHS R56 HL168264NIH/NHLBI 1R01HL177105NIH/NHLBI R01HL142765NIH/NHLBI R21HL172288NIH/NHLBI R56HL168264
6 · The paper itself

Abstract

backgroundPermanent pacemaker (PPM) battery longevity impacts downstream procedures, patient outcomes, and healthcare costs.

objectivesTo measure and predict PPM battery longevity in routine, clinical practice.

methodsWe analyzed a nationwide, multicenter, remote monitoring dataset (PaceMate) to evaluate PPM battery longevity from 2007 to 2023. Multivariable models identified factors associated with replacement interval (RI) across device types and manufacturers. We also compared observed versus expected battery longevity and assessed differences between newer and older generation pacemakers.

resultsWe included 58,395 devices from 47 sites: 5803 single-chamber transvenous, 1637 single-chamber leadless, 45,293 dual-chamber transvenous, 1759 RV/LV-only CRT pacemakers, and 3903 full CRT-P systems (1888 reaching RI). Median observed battery longevity for the 1493 dual chamber transvenous pacemakers that reached RI ranged from (103 months for BSX to 125 months for MDT and BIO), with similar trends after adjustment (p<0.001). There was variability in median battery longevity across manufacturers for other device types: 105-122 months for single-chamber transvenous, 61-96 months for RV/LV-only CRT pacemakers, and 77-93 months for full CRT-P systems. Compared with older generators, those implanted in 2022-23 demonstrated improved estimated battery longevity for Medtronic devices but decreased for Abbott (no significant change for Boston Scientific).

conclusionsObserved pacemaker battery longevity, based on nearly 2000 devices reaching ERI, varies substantially by manufacturer and device type, without consistent improvement for newer devices. Device-based estimates of remaining longevity show manufacturer-specific variability and are influenced by programming and utilization, highlighting the need for individualized expectations in clinical practice. CONDENSED ABSTRACT: Permanent pacemaker (PPM) battery longevity is clinically impactful and not well described in routine, clinical practice. We quantified pacemaker battery performance in a nationwide, multicenter, remote monitoring dataset, including 58,395 devices. Pacemaker battery longevity varies by manufacturer and device type, without consistent improvement for newer devices. Manufacturer-specific accuracy of battery longevity estimates and differences in device programming and utilization highlight the need for individualized expectations in clinical practice.

Indexed as

battery longevitymanufacturerpermanent pacemaker

Identifiers

PMID42502885
PMCPMC13436807

What Socratic holds

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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 Socratic graph.