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Updated: Jan 11, 2026

A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program
Published on: April 19, 2019
Algorithm Improvements in an Insertable Cardiac Monitor Reduce False Positives and Episode Review Burden
Mark Richards1, Molly Kupfer2, Keith Herrmann2
1Baylor Scott & White Arrhythmia Management, Plano, Texas, USA.
Introduction:
The use of insertable cardiac monitors (ICM) for arrhythmia monitoring continues to grow steadily. However, ICM performance remains less than perfect, and the volume of transmitted data poses a challenge to clinics. Here, we evaluate the impact of three improvements implemented in the LUX-Dx II+ ICM for atrial fibrillation (AF), pause, and bradycardia detection.
Methods:
Enhanced AF and pause algorithms were evaluated using real-world ECG data and compared against the predecessor LUX-Dx algorithms. Optimized nighttime (11 p.m.-7 a.m.) programming settings were simulated on LUX-Dx data to evaluate the reduction of non-actionable nocturnal bradycardia (>30 bpm) and pause (<5 s) detections.
Results:
The novel AF algorithm reduced false positives by 34% in the training dataset and 38% in the test dataset while maintaining >98% sensitivity relative to the legacy algorithm. False positive reduction and relative sensitivity were even higher (74% and 100%, respectively) in a subset of patients with more sensitive AF programming settings. The enhanced pause algorithm reduced false positives by 62.5% in the training set and 48.6% in the test set, while maintaining 100% relative sensitivity. Application of adjusted nocturnal detection thresholds reduced the number of nighttime bradycardia and pause episodes by 98% and 90%, corresponding to an overall episode reduction of 75% and 56%, respectively.
Conclusion:
The enhanced ICM algorithms and programming settings substantially reduced false positive AF and pause detections as well as non-actionable nighttime bradycardia and pause detections. These enhancements are expected to improve ICM performance and workflow in the device clinic.
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