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Utilization and programming of an automatic MRI recognition feature for cardiac rhythm management devices

BACKGROUND: Cardiac implantable electronic devices (CIED)—ie, pacemakers, implantable cardioverter-defibrillators, and cardiac resynchronization therapy devices—have recently been designed to allow for patients to safely undergo magnetic resonance imaging (MRI) when specific programming is implement...

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Autores principales: Mullane, Steven, Michaelis, Kyle, Henrikson, Charles, Iwai, Sei, Miller, Crystal, Harrell, Camden, Hayes, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8183951/
https://www.ncbi.nlm.nih.gov/pubmed/34113915
http://dx.doi.org/10.1016/j.hroo.2021.03.002
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author Mullane, Steven
Michaelis, Kyle
Henrikson, Charles
Iwai, Sei
Miller, Crystal
Harrell, Camden
Hayes, David
author_facet Mullane, Steven
Michaelis, Kyle
Henrikson, Charles
Iwai, Sei
Miller, Crystal
Harrell, Camden
Hayes, David
author_sort Mullane, Steven
collection PubMed
description BACKGROUND: Cardiac implantable electronic devices (CIED)—ie, pacemakers, implantable cardioverter-defibrillators, and cardiac resynchronization therapy devices—have recently been designed to allow for patients to safely undergo magnetic resonance imaging (MRI) when specific programming is implemented. MRI AutoDetect is a feature that automatically switches CIED’s programming into and out of an MR safe mode when exposed to an MRI environment. OBJECTIVE: The purpose was to analyze de-identified daily remote transmission data to characterize the utilization of the MRI AutoDetect feature. METHODS: Home Monitoring transmission data collected from MRI AutoDetect–capable devices were retrospectively analyzed to determine the workflow and usage in patients experiencing an MRI using the MRI AutoDetect feature. RESULTS: Among 48,756 capable systems, 2197 devices underwent an MRI using the MRI AutoDetect feature. In these 2197 devices, the MRI AutoDetect feature was used a total of 2806 times with an average MRI exposure of 40.83 minutes. The majority (88.9%) of MRI exposures occurred on the same day as the MRI AutoDetect programming. A same day post-MRI exposure follow-up device interrogation was performed 8.6% of the time. A device-related complaint occurred within 30 days of the MRI exposure in 0.25% of MRI exposures using MRI AutoDetect but with no adverse clinical outcome. CONCLUSION: As a result of automation in device programming, the MRI AutoDetect feature eliminated post-MRI device reprogramming in 91.4% of MRI exposures and, while less frequent, allowed for pre-MRI interrogations prior to the day of the MRI exposure—reducing resource utilization and creating workflow flexibility.
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spelling pubmed-81839512021-06-09 Utilization and programming of an automatic MRI recognition feature for cardiac rhythm management devices Mullane, Steven Michaelis, Kyle Henrikson, Charles Iwai, Sei Miller, Crystal Harrell, Camden Hayes, David Heart Rhythm O2 Clinical BACKGROUND: Cardiac implantable electronic devices (CIED)—ie, pacemakers, implantable cardioverter-defibrillators, and cardiac resynchronization therapy devices—have recently been designed to allow for patients to safely undergo magnetic resonance imaging (MRI) when specific programming is implemented. MRI AutoDetect is a feature that automatically switches CIED’s programming into and out of an MR safe mode when exposed to an MRI environment. OBJECTIVE: The purpose was to analyze de-identified daily remote transmission data to characterize the utilization of the MRI AutoDetect feature. METHODS: Home Monitoring transmission data collected from MRI AutoDetect–capable devices were retrospectively analyzed to determine the workflow and usage in patients experiencing an MRI using the MRI AutoDetect feature. RESULTS: Among 48,756 capable systems, 2197 devices underwent an MRI using the MRI AutoDetect feature. In these 2197 devices, the MRI AutoDetect feature was used a total of 2806 times with an average MRI exposure of 40.83 minutes. The majority (88.9%) of MRI exposures occurred on the same day as the MRI AutoDetect programming. A same day post-MRI exposure follow-up device interrogation was performed 8.6% of the time. A device-related complaint occurred within 30 days of the MRI exposure in 0.25% of MRI exposures using MRI AutoDetect but with no adverse clinical outcome. CONCLUSION: As a result of automation in device programming, the MRI AutoDetect feature eliminated post-MRI device reprogramming in 91.4% of MRI exposures and, while less frequent, allowed for pre-MRI interrogations prior to the day of the MRI exposure—reducing resource utilization and creating workflow flexibility. Elsevier 2021-03-09 /pmc/articles/PMC8183951/ /pubmed/34113915 http://dx.doi.org/10.1016/j.hroo.2021.03.002 Text en © 2021 Heart Rhythm Society. Published by Elsevier Inc. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Clinical
Mullane, Steven
Michaelis, Kyle
Henrikson, Charles
Iwai, Sei
Miller, Crystal
Harrell, Camden
Hayes, David
Utilization and programming of an automatic MRI recognition feature for cardiac rhythm management devices
title Utilization and programming of an automatic MRI recognition feature for cardiac rhythm management devices
title_full Utilization and programming of an automatic MRI recognition feature for cardiac rhythm management devices
title_fullStr Utilization and programming of an automatic MRI recognition feature for cardiac rhythm management devices
title_full_unstemmed Utilization and programming of an automatic MRI recognition feature for cardiac rhythm management devices
title_short Utilization and programming of an automatic MRI recognition feature for cardiac rhythm management devices
title_sort utilization and programming of an automatic mri recognition feature for cardiac rhythm management devices
topic Clinical
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8183951/
https://www.ncbi.nlm.nih.gov/pubmed/34113915
http://dx.doi.org/10.1016/j.hroo.2021.03.002
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