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. 2024 Jan 23:11:1343424.
doi: 10.3389/fcvm.2024.1343424. eCollection 2024.

Implantable cardiac monitors: artificial intelligence and signal processing reduce remote ECG review workload and preserve arrhythmia detection sensitivity

Giovanni Bisignani  1 , Jim W Cheung  2 , Roberto Rordorf  3 , Valentina Kutyifa  4 , Daniel Hofer  5 , Dana Berti  6 , Luigi Di Biase  7 , Eimo Martens  8 , Vincenzo Russo  9 , Paolo Vitillo  10 , Marlies Zoutendijk  11 , Thomas Deneke  12 , Irina Köhler  13 , Jürgen Schrader  13 , Gaurav Upadhyay  14
Affiliations

Implantable cardiac monitors: artificial intelligence and signal processing reduce remote ECG review workload and preserve arrhythmia detection sensitivity

Giovanni Bisignani et al. Front Cardiovasc Med. .

Abstract

Introduction: Implantable cardiac monitors (ICMs) provide long-term arrhythmia monitoring, but high rates of false detections increase the review burden. The new "SmartECG" algorithm filters false detections. Using large real-world data sets, we aimed to quantify the reduction in workload and any loss in sensitivity from this new algorithm.

Methods: Patients with a BioMonitor IIIm and any device indication were included from three clinical projects. All subcutaneous ECGs (sECGs) transmitted via remote monitoring were classified by the algorithm as "true" or "false." We quantified the relative reduction in workload assuming "false" sECGs were ignored. The remote monitoring workload from five hospitals with established remote monitoring routines was evaluated. Loss in sensitivity was estimated by testing a sample of 2000 sECGs against a clinical board of three physicians.

Results: Of our population of 368 patients, 42% had an indication for syncope or pre-syncope and 31% for cryptogenic stroke. Within 418.5 patient-years of follow-up, 143,096 remote monitoring transmissions contained 61,517 sECGs. SmartECG filtered 42.8% of all sECGs as "false," reducing the number per patient-year from 147 to 84. In five hospitals, nine trained reviewers inspected on average 105 sECGs per working hour. This results in an annual working time per patient of 83 min without SmartECG, and 48 min with SmartECG. The loss of sensitivity is estimated as 2.6%. In the majority of cases where true arrhythmias were rejected, SmartECG classified the same type of arrhythmia as "true" before or within 3 days of the falsely rejected sECG.

Conclusion: SmartECG increases efficiency in long-term arrhythmia monitoring using ICMs. The reduction of workload by SmartECG is meaningful and the risk of missing a relevant arrhythmia due to incorrect filtering by the algorithm is limited.

Keywords: artificial intelligence; cardiac arrhythmia; employee workload; implantable cardiac monitor; remote monitoring.

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Conflict of interest statement

Cheung reports consulting for Abbott, Biotronik, Boston Scientific and Medtronic; Research support from Boston Scientific and fellowship grant support: Abbott, Biotronik, Boston Scientific and Medtronic. Rordorf received modest speaking fees by Boston Scientific, Abbott and Biosense Webster. Hofer reports educational grants, consultant fees, speaker fees or fellowship support from Abbott, Medtronic, Biotronik, Boston Scientific, Biosense Webster, Novartis, Bayer, Pfizer, and Spectranetics/Philips. Martens reports speaker fee/consulting fee from Deutsche Gesellschaft für Kardiologie, Abbott, Astra Zeneca, Biotronik, Böhringer-Ingelheim, Bristol Myers Squibb, Medtronic and Philips/Spectranetics. Deneke reports speaker fee from Biotronik (educational grant). Schrader is an employee of Biotronik. Upadhyay reports speaking or consulting fees from Abbott, Biotronik, Boston Scientific, GE Medical, Medtronic, Philips BioTel, and RhythmScience. Bisignani, Kutyifa, Berti, Di Biase, Russo, Vitillo and Zoutendijk report no conflict of interest. RR and VR are editorial board member of Frontiers, at the time of submission.

Figures

Figure 1
Figure 1
Example of an sECG with an “AF” detection, classified as false detection both by the clinical board and SmartECG.
See this image and copyright information in PMC

References

    1. Kwok CS, Darlington D, Mayer J, Panchal G, Walker W, Zachariah D, et al. A review of the wide range of indications and uses of implantable loop recorders: a review of the literature. Hearts. (2022) 3:45–53. 10.3390/hearts3020007 - DOI
    1. Seiler A, Biundo E, Di Bacco M, Rosemas S, Nicolle E, Lanctin D, et al. Clinic time required for remote and in-person management of patients with cardiac devices: time and motion workflow evaluation. JMIR Cardio. (2021) 5(2):e27720. 10.2196/27720 - DOI - PMC - PubMed
    1. Hindricks G, Pokushalov E, Urban L, Taborsky M, Kuck KH, Lebedev D, et al. Performance of a new leadless implantable cardiac monitor in detecting and quantifying atrial fibrillation: results of the XPECT trial. Circ Arrhythm Electrophysiol. (2010) 3(2):141–7. 10.1161/CIRCEP.109.877852 - DOI - PubMed
    1. O’Shea CJ, Middeldorp ME, Hendriks JM, Brooks AG, Harper C, Thomas G, et al. Remote monitoring of implantable loop recorders: false-positive alert episode burden. Circ Arrhythm Electrophysiol. (2021) 14(11):e009635. 10.1161/CIRCEP.121.009635 - DOI - PubMed
    1. Mittal S, Oliveros S, Li J, Barroyer T, Henry C, Gardella C. AI filter improves positive predictive value of atrial fibrillation detection by an implantable loop recorder. JACC Clin Electrophysiol. (2021) 7(8):965–75. 10.1016/j.jacep.2020.12.006 - DOI - PubMed

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