LUX-Dx™ ICM resources
Tools & resources to make the most of your time
Education & workflow tools
This interactive guide provides tips and instructions to help you integrate the LUX-Dx ICM System into your clinic workflow.
Explore tools and resources to help you integrate the LUX-Dx ICM into your practice, including continuing education courses, an insertion procedure animation, how-to guides, billing and coding information, patient education materials and more.
This helpful chart summarizes options to consider when adjusting programming settings in the LATITUDE Clarity™ Data Management System.
Product info & videos
Find detailed product specs, directions for use, MRI compatibility, device longevity information, and more resources for the LUX-Dx ICM System.
Engineered for Advanced Control
The Boston Scientific research and development team discusses their design process and how they developed an ICM that addresses the shortcomings of existing devices, reduces patient burden and accelerates critical decision making.
Find out how the dual-stage algorithm is designed to reject false positives and see performance results across multiple cardiac arrythmias for the LUX-Dx ICM System.
LUX-Dx ICM Overview Video
This quick video provides an overview of the LUX-Dx ICM System and how it is redefining the ICM with a dual-stage algorithm and remote programming.
LATITUDE Clarity System
See how the LATITUDE Clarity System helps you streamline your workflow and enhance patient care.
Get an overview of the LUX-Dx ICM System, including the intuitive insertion procedure, dual-stage algorithm, remote programming capabilities, myLUX™ patient app, and LATITUDE Clarity Data Management System.
Find out how the S-ECG signal quality of the LUX-Dx ICM is designed to emulate Lead II and puts the power of astoundingly clear signals in your hands, helping to achieve more efficient and confident event reviews.
Atrial Fibrillation (AF) Algorithm Video
Find out how the AF algorithm monitors R-R variability to detect potential AF rhythms. And how the verification stage uses an adaptive morphology, noise discrimination and pattern detectors to identify and reject false positives.
Atrial Tachycardia (AT) Algorithm Video
See how the LUX-Dx ICM uses rate, duration and built-in flexibility to detect only high-rate rhythms sustained for a prolonged period of time, or to detect short duration AT/Atrial Flutter. The AT algorithm duration is independent of the AF algorithm duration.
Pause Algorithm Video
Watch the video to see how the LUX-Dx ICM is designed to monitor R-R duration to detect pause episodes and, in the verification stage, reject false positives by using a dynamic noise-reduction filter, signal-to-noise ratio and loss-of-signal conditions.
Tachycardia Algorithm Video
Find out how the tachycardia algorithm uses traditional ICD-based rate and duration parameters during the detection stage. The verification stage uses a machine-learning-based decision tree to identify potential tachy episodes. If they are not within the rate zone, they’re rejected as noise.
Bradycardia Algorithm Video
Watch the video to find out how the bradycardia algorithm helps reject false positives due to under-sensing. First, the algorithm uses rate and duration parameters during the detection stage to identify potential brady episodes. Then during the verification stage, episodes are further examined for under-sensing before being rejected.
Sidharth Shah, MD, MS, FACC of UNC Health in Raleigh, North Carolina talks with EP Lab Digest about how the LUX-Dx ICM helps him provide more proactive heart health care. Plus, he discusses the benefits of remote programming technology during the COVID-19 pandemic.
Cardiac Monitoring and COVID-19
In this engaging session of Rhythm Theater, a device clinic nurse manager and an electrophysiologist share their perspectives about navigating the challenges of managing ICM patients during the COVID-19 pandemic.
Distributed with permission from the Heart Rhythm Society.
Watch this webinar for an overview of the LUX-Dx ICM System, clinic and patient mobile apps, LATITUDE Clarity™ Data Management System, insertion procedure and more. Plus, learn about the dual-stage algorithm, remote programming, astounding signal quality and other features that make the LUX-Dx ICM different.
Watch an electrophysiologist perform a live LUX-Dx ICM insertion procedure, review patient case studies, and see a device clinic manager’s demonstration of the LATITUDE Clarity Data Management System in this comprehensive webinar.
View the HRS 2021 poster showing the LUX-Dx ICM demonstrated consistent visibility of P-waves across a wide range of patients, which is an important clinical feature in diagnosing atrial arrhythmias.1
This HRS 2021 poster describes in vivo detection of the LUX-Dx ICM atrial tachycardia (AT) algorithm that enables detection of clinically relevant AT without compromising ideal AF detection settings. 2†
CARMEL Study Results
This pilot study evaluating the performance of a novel remote programming system for cardiac monitoring found that remote programming has the potential to substantially reduce ICM patient workload.3†
Distributed with permission from the Heart Rhythm Society.
See how using QRS morphology assessment in addition to R-R variability resulted in a 53.1% relative reduction in false positives and AF burden Positive Predictive Value (PPV) ranged from 73% to 99%.4†
Explore the research showing PPV improved from 54.4% to 99.2% with minimal changes to sensitivity.5†
See the data showing sensitivity performance for three-second pauses from four different settings ranged from 92% to 99% and PPV ranged from 82% to 98%.6†
See the data demonstrating PPV for combined AF and AT detection increased from 54% to 97% with both higher rates and longer durations.7†
Review the data showing how machine learning correctly rejected noise 96% of the time, which improved the PPV from 23% to 86%.8†
Download a summary of LUX-Dx ICM bench testing results across multiple cardiac arrhythmias, including AF, AT, tachy and pause.†
Download this brochure to give your patients a quick overview of the LUX-Dx ICM System, reasons for cardiac monitoring, and how to set up and use their myLUX™ Patient app.
The LUX-Dx patient website offers guides, videos and other resources to help patients learn about insertable cardiac monitors, the ICM insertion procedure, reasons for heart monitoring, how the myLUX Patient app works and more.
This comprehensive video covers how the LUX-Dx ICM works, what to expect from the insertion procedure, why cardiac monitoring is important, and how to set up and use the myLUX Patient app.
1. Frazier-Mills C, Rahan A, Saleeby R, Leguire R, et al. Consistent visibility in P-waves observed in patients implanted with LUX-Dx Insertable Cardiac Monitor. Poster presented at: 2021 Heart Rhythm Society; July 2021; Boston, MA
2. Richards M, Perschbacher D, Frost K, Hermann K. Improved Detection of AT In Vivo in Patients with the LUX-Dx Insertable Cardiac Monitor. Poster presented at: 2021 Heart Rhythm Society; July 2021; Boston, MA.
3. Dave Perschbacher, Sunipa Saha, Paul W. Jones, MS, Tim M. Stivland, Jonathan Kelly, Robert Parkinson and Kenneth M. Stein, MD, FHRS. CARMEL Study Reference Clinical Performance of a Novel Remote Programming. System for Insertable Cardiac Monitors: Results of the CARMEL Study. HRS 2020 Science Online.
4. Mittal S, Saha S, Perschbacher D, Siejko K. Improved AF Rhythm Discrimination with an Implantable Cardiac Monitor Using QRS Morphology. Poster presented at: 2019 Heart Rhythm Society; May, 2019; San Francisco, CA.
5. Richards M, Perschbacher D, Herrmann K, Siejko K, Saha S. A Novel Algorithm to Improve Atrial Fibrillation Detection in Implantable Cardiac Monitors. Poster presented at: 2019 Heart Rhythm Society; May, 2019; San Francisco, CA.
6. Richards, M. Perschbacher, D, Herrmann, K, Saha, S, Siejko, K. A Novel Algorithm to Reduce False Positives for Pause Detection in Implantable Cardiac Monitors. Poster presented at Heart Rhythm Society May 2018, Boston, MA.
7. Richards, M. Perschbacher, D, Saha, S. A Novel Algorithm Improves Detection of Arrythmias With Regular R-R Intervals. Poster Presented at Heart Rhythm Society May 2019 San Francisco, CA.
8. Mittal, S. Siejko, K, Saha, S, Herrmann, K, Perschbacher, D. Can Machine Learning Be Used to Optimize Tachycardia Detection Algorithm in an Implantable Cardiac Monitor. Poster presented at ESC, June 2018, Munich, Germany.
†Bench Test results may not necessarily be indicative of clinical performance. Bench data for this research was provided by Telemetric and Holter ECG Warehouse (THEW), University of Rochester, NY.