Accuracy of a Single Versus Multiple Trials of Novel Pacemaker ID Algorithm Mobile Phone App for Identification of Cardiac Devices

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Author Info

Alex Conant Jay J Chudow Syona S Shetty Rahul Grover John D Fisher Andrew Krumerman Kevin J Ferrick

Corresponding Author

Kevin J Ferrick
Department of Cardiology, Montefiore Medical Center, Bronx, New York, USA

A B S T R A C T

Fast and accurate identification of cardiac devices can facilitate device programming and interrogation in various medical settings. We have previously demonstrated the accuracy of the PacemakerID machine learning algorithm for mobile phone cardiac device identification. However, the questions of the reproducibility of this algorithm and whether a single trial sufficiently maximizes accuracy have yet to be answered. Here, we examine 502 chest x-rays performed at a single institution on patients with implantable cardioverter-defibrillators and permanent pacemakers. The PacemakerID mobile phone application was used for five sequential trials on each image and the accuracy of one, three, and five trials were compared. A single trial resulted in a 79% accuracy and 82% positive predictive value with no significant difference (p=0.69) as compared to five trials at identifying device manufacturers. Across all devices, the results of a single trial were not significantly different from those of five trials. Our data demonstrate that a single trial is sufficient to maximize diagnostic accuracy with the PacemakerID mobile phone application, facilitating rapid identification for prompt programming and interrogation of cardiac devices.

Article Info

Article Type

Research Article

Publication history

Received: Tue 16, Aug 2022
Accepted: Mon 05, Sep 2022
Published: Fri 23, Sep 2022

Copyright

© 2023 Kevin J Ferrick. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Hosting by Science Repository.
DOI: 10.31487/j.JICOA.2022.03.04