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

K. Ferrick, Alexander Conant, Jay J Chudow, Syona S Shetty, Rahul Grover, John D Fisher, A. Krumerman
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Abstract

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.
新型起搏器ID算法手机应用程序用于心脏设备识别的单次试验与多次试验的准确性
快速准确地识别心脏设备可以促进各种医疗环境中的设备编程和询问。我们之前已经证明了PacemakerID机器学习算法用于手机心脏设备识别的准确性。然而,该算法的再现性以及单次试验是否足以使准确性最大化的问题还有待回答。在这里,我们检查了在一家机构对植入型心律转复除颤器和永久性起搏器的患者进行的502次胸部x光检查。PacemakerID手机应用程序在每张图像上进行了五次连续试验,并比较了一次、三次和五次试验的准确性。与确定设备制造商的五项试验相比,一项试验的准确率为79%,阳性预测值为82%,无显著差异(p=0.69)。在所有设备中,单个试验的结果与五个试验的结果没有显著差异。我们的数据表明,一次试验就足以最大限度地提高PacemakerID手机应用程序的诊断准确性,有助于快速识别心脏设备的即时编程和询问。
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