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Electrophysiology / HeartLogic™ Heart Failure Diagnostic / Clinical Data / MultiSENSE

About MultiSENSE

Overview

MultiSENSE was an international, multicenter, non-randomized feasibility study designed to determine how ambulatory sensor measurements change with worsening heart failure (HF).

Goals

Develop and validate a multi-sensor algorithm for the early detection of worsening heart failure.

Conclusions

HeartLogic multi-sensor index and alert algorithm provide a sensitive and timely predictor of impending heart failure decompensation.1

 

 

The Journey

 
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Research

  • 10+ years research
  • Data analysis from 12 clinical trials
  • Extensive HF clinic customer visits
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Algorithm Development

  • Thousands of candidate features evaluated and down selected for optimal algorithm development
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Algorithm Design

  • Multiple fusion techniques evaluated
  • Multiple combinations of learnings leveraged in final algorithm
MultiSENSE Study Results
The MultiSENSE study assessed more than 900 patients and validated the HeartLogic algorithm to have:1
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70% SENSITIVITY

in Detecting Heart Failure Events

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A MEDIAN OF 34 DAYS

Advance Notice of Worsening Heart Failure

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<2 TOTAL ALERTS

Per Patient Per Year

Chart showing the HeartLogic sensitivity and unexplained alert rates per patient-year.
 
Physician Perspectives
 
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“I think HeartLogic is very compelling because for the first time we have an algorithm that’s really been validated and is an algorithm that touches upon the things as clinicians that we think are important.”

Carl Fier, MD, FACC

Identifying High-Risk Patients

The MultiSENSE study demonstrated HeartLogic Heart Failure Diagnostic’s ability to identify high-risk patients, which may allow clinicians to focus on patients at highest risk while maintaining surveillance of low-risk patients.

Read the Article
A Multisensor Algorithm Predicts Heart Failure Events in Patients With Implanted Devices: Results From the MultiSENSE Study
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MANAGE-HF Study
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Real-World Evidence
See how HeartLogic consistently detected HF events in real-world analyses of nearly 500 patients in four studies.

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References

1. Boehmer JP, Hariharan R, Devecchi FG, et al. A multisensor algorithm predicts heart failure events in patients with implanted devices: results from the MultiSENSE study. JACC Heart Fail. 2017 Mar;5(3):216-225. doi: 10.1016/j.jchf.2016.12.011

2. Gardner R, Singh J, Stancak B, et al. HeartLogic multisensor algorithm identifies patients during periods of significantly increased risk of heart failure events: results from the MultiSENSE study. Circ Heart Fail. 2018;11(7):e004669. doi: 10.1161/circheartfailure.117.004669

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