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Electrophysiology / HeartLogic™ Heart Failure Diagnostic / Clinical Data

HeartLogic Clinical Data

Explore clinical data and real-world evidence demonstrating how HeartLogic Heart Failure Diagnostic can help give you the actionable information you need to change patients’ lives—before you expect it.
 

 

Time Course of HF Decompensation1

 

Emulating Clinical Assessment via Physiologic Sensor Monitoring

Timeline showing an example time course of heart failure decompensation.
  

  

MultiSENSE Study Results2

 
The MultiSENSE study assessed more than 900 patients and validated that the HeartLogic algorithm provides a sensitive and timely predictor of impending heart failure decompensation.
Icon of a heart.

70% SENSITIVITY

in Detecting Heart Failure Events

Icon of a calendar.

A MEDIAN OF 34 DAYS

Advance Notice of Worsening Heart Failure

Icon of an exclamation point inside a triangle.

<2 TOTAL ALERTS

Per Patient Per Year

  

  

MANAGE-HF Study3

 
MANAGE-HF enrolled 200 patients implanted with a CRT-D or ICD enabled with HeartLogic. The study found that HeartLogic was safely integrated into clinical practice and associated with lower natriuretic peptide levels and hospitalization rates.4
: Icon of a bar chart with decreasing values and an arrow pointing down.

MORE RAPID RECOVERY

Of HeartLogic Index

Icon of three test tubes in a stand.

LOWER

NTproBNP Levels

Icon of a circle with 67% in the middle.

67% REDUCTION

In HF Hospitalizations Associated with HeartLogic*

*Compared with pre-study hospitalization rate (12 months).
  

  

Electrophysiology Insights

 
HeartLogic uses automated intelligence to streamline your ability to see each patient’s physiologic response to arrhythmic and pacing changes.

Relationship Between Atrial Fibrillation and HeartLogic Index5

Chart showing the change in the HeartLogic index in comparison to the days from AF progression.

HeartLogic May Detect Sub-Optimal BiV Pacing and Poor Physiologic Response6

Two arrows showing that as the BiV pacing percentage decreased, the HeartLogic index increased.

HeartLogic May Identify Patients Vulnerable to RV Pacing7
 

Infographic showing that when RV pacing is greater than 10%, the HeartLogic index increases significantly.
  

  

Real-World Evidence

 
In real-world analyses of nearly 500 patients across four studies, HeartLogic was shown to provide consistent heart failure detection performance with low unexplained alert rates.
  

Real-World Results Compared to Validation Data Set

  MultiSENSE2
(Validation Data Set)
Capucci
et al.5

(ESC HF 2019)
Santini
et al.8

(Clin Card 2020)
RE-HEART
Phase I9

(ESC HF 2020)
RE-HEART
Phase II10

(ESC HF 2020)
SENSITIVITY 70% 100%* 69%* N/A N/A
UNEXPLAINED ALERT RATE 1.47 0.41 0.37 0.25 0.13
  

Highlights from Real-World Studies

Circle with 80% in the middle.

80% OF ALERTS

Provided New Information to Clinicians8

Icon of calendar showing that HeartLogic alert preceded heart failure symptoms by a median of 12 days.

ALERTS PRECEDED HF SYMPTOMS

by a Median of 12 Days5

Icon of calendar showing that HeartLogic alert preceded heart failure events by a median of 38 days.

ALERTS PRECEDED HF EVENTS

by a Median of 38 Days5

  

  

Physician Perspectives

 
HFSA 2019: HeartLogic™ – Validated Evidence, Clinical Implementation and Utility

HeartLogicTM Data and Integration into Clinical Practice: HFSA 2021

Watch Dr. Marat Fudim, Dr. Andrew Sauer and Dr. Larry Allen discuss HeartLogic, review case studies and highlight results from the MANAGE-HF Clinical Study.

Heart Rhythm 2019: HeartLogic – A Multi-Sensor HF Diagnostic

Integrated Heart Failure Patient Management EP and HF Perspective

Listen as three members of the Duke University Medical Center team – Dr. Marat Fudim, Dr. Camille Frazier-Mills and Dr. Adrian Hernandez – share their experience collaborating to implement HeartLogic™ in clinical care and demonstrate through case studies the value of integrated care.

Heart Rhythm 2019: HeartLogic – A Multi-Sensor HF Diagnostic

HeartLogic™ Clinical Data and Integration into Clinical Practice: AAHFN 2022

Hear from distinguished faculty as they review HeartLogic, discuss key clinical data, and share real-world integration into clinical practice including case examples.

  
HeartLogic Clinical Compendium

HeartLogic Clinical Compendium

Review a compilation of relevant publication references that form the clinical foundation of the HeartLogic Heart Failure Diagnostic, organized by sensor trend/topic area and relevance.
 

Pages from the HeartLogic Clinical Compendium.
  
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Increase Efficiencies. Improve Lives.

See how HeartLogic may help you increase clinic efficiencies, reduce hospital readmissions and improve patient outcomes.

 

LATITUDE NXT™ Remote Patient Management System: Indications, Safety and Warnings

Resonate™ ICD: Indications, Safety and Warnings

Resonate™ CRT-D: Indications, Safety and Warnings

 

References

1. Adamson PB. Pathophysiology of the transition from chronic compensated and acute decompensated heart failure: new insights from continuous monitoring devices. Curr Heart Fail Rep. 2009 Dec;6(4):287-92. doi: 10.1007/s11897-009-0039-z.

2. 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):216-25. doi: 10.1016/j.jchf.2016.12.011.

3. Multiple Cardiac Sensors for the Management of Heart Failure (MANAGE-HF).
https://clinicaltrials.gov/ct2/show/NCT03237858

4. Hernandez AF, Albert N, Allen L, et al. Multiple cardiac sensors for management of heart failure (MANAGE-HF) Phase I results. Abstract presented at: European Society of Heart Failure 2021 World Congress on Acute Heart Failure: June 29-July 1, 2021. Virtual.

5. Capucci A, Healey JS. Temporal association of atrial fibrillation with device-based heart failure status in patients with CRT. Oral presentation and LBCT presented at: EHRA Congress; March 2019, Lisbon, Portugal.

6. Varma N, Cao M, Schloss EJ, Ahmed R, Stolen C, Boehmer JP. Progressive worsening in device base failure sensors measurements are associated with sub-optimal BiV pacing percentages in CRT-D patients. J Heart Fail. 2019;21(Suppl. S1):370. doi: 10.1002/ejhf.1488

7. Varma N, Stein KM, Thakur PH, Jones PW, Ahmed R, J Boehmer J. Multiparametric analysis of device based physiological sensors may identify ICD patients reacting adversely to right ventricular pacing [abstract]. Heart Rhythm. 2019;16(5):S58-S59.

8. Santini L, D’Onofrio A, Russo AD, et al. Prospective evaluation of the multisensor HeartLogic algorithm for heart failure monitoring. Clin Card. 2020;43(7):691-697. doi: 10.1002/clc.23366

9. De Juan Baguda J, Gavira Gomex JJ, Pachó Iglesias M, et al. Preliminary results of the Spanish multicentric HeartLogic (RE-HEART) registry: a blinded analysis. Abstract presented virtually at: ESC-HFA Congress 2020.

10. De Juan Baguda J, Gavira Gomex JJ, Pachó Iglesias M, et al. Preliminary results of the Spanish multicentric HeartLogic (RE-HEART) registry: adoption of an alert-based heart failure management approach. Abstract presented virtually at: ESC-HFA Congress 2020.

*The HeartLogic Index and Alert were validated using data from the MultiSENSE study; however, HeartLogic’s impact on clinical outcome has not been established. Establishment of the impact will require a post market trial designed specifically to study clinical outcomes directly related to the use of this feature.

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