LINQ Sensor Algorithm for Heart Failure

(ALLEVIATE-HF Trial)

Recruiting at 59 trial locations

Overseen By Kelly Axsom, M.D.

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: Medtronic Cardiac Rhythm and Heart Failure

Must not be taking: Inotropes

Disqualifiers: CIED, Mechanical support, MI, others

Compensation: Varies

Number of Visits: Unknown

826 Participants Needed

Trial Summary

What is the purpose of this trial?

This trial tests a small device that monitors heart activity in patients with moderate heart failure. The device uses special software to help doctors manage patient care more effectively.

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications. It is best to discuss this with the trial coordinators or your doctor.

What data supports the effectiveness of this treatment for heart failure?

Research shows that implantable sensors, like the Reveal LINQ™ monitor, can continuously track heart health and detect early signs of heart failure worsening, which helps doctors adjust treatment and potentially reduce hospital visits. ^{1 2 3 4 5}

Is the LINQ Sensor Algorithm for Heart Failure safe for humans?

The LINQ Sensor, a minimally invasive device, has been tested in several studies for monitoring heart failure, showing it can be safely used to track heart health and detect early signs of worsening conditions. These studies suggest it is generally safe for human use, although specific safety data for other conditions is not detailed. ^{1 2 5 6 7}

How is the LINQ Sensor Algorithm for Heart Failure treatment different from other heart failure treatments?

The LINQ Sensor Algorithm for Heart Failure treatment is unique because it uses a miniaturized insertable cardiac monitor (ICM) that provides continuous, remote monitoring of heart activity, allowing for early detection of worsening heart failure. This approach is minimally invasive and offers personalized monitoring, which can help prevent complications and reduce healthcare costs. ^{1 2 7 8 9}

Research Team

Javed Butler, MD

Principal Investigator

Baylor Scott and White Health

Eligibility Criteria

This trial is for adults over 18 with NYHA Class II or III heart failure who have had recent symptoms or treatments for heart failure. They must expect to live at least another year, be able to follow the study protocol, and not be part of another interventional study. People with severe kidney issues, low blood pressure, certain heart conditions, active cancer treatment, or those on mechanical circulatory support cannot join.

Inclusion Criteria

I have had heart failure symptoms or treatment recently.

Patient has a life expectancy of 12 months or more.

I have moderate heart failure according to my latest check-up.

Exclusion Criteria

I am on long-term IV medication to strengthen my heart.

I have had a heart transplant or am on the waiting list for one.

I am currently receiving chemotherapy or radiation for my cancer.

Timeline

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Observation

Subjects receive a Reveal LINQ™ Insertable Cardiac Monitor and are managed per standard of care without visibility to sensor data

13 months

Intervention

Subjects are managed using an integrated device diagnostic-based risk stratification algorithm combined with a clinical medication plan

Up to 36 months

Follow-up

Participants are monitored for safety and effectiveness after treatment

7-13 months

Treatment Details

Interventions

• Medication intervention
• Reveal LINQ™ Insertable Cardiac Monitor with investigational ALLEVIATE-HF RAMware download

Trial Overview The ALLEVIATE-HF study tests a new patient management approach using an algorithm from LINQ sensors to guide care in heart failure patients. It also assesses the safety of Reveal LINQ™ monitors and procedures. Participants are randomly assigned to either receive this new intervention or continue with standard care.

Participant Groups

Group I: Intervention Arm Experimental Treatment 2 Interventions

Subjects will receive a Reveal LINQ™ Insertable Cardiac Monitor with an investigational ALLEVIATE-HF RAMware download, and will be managed using an integrated device diagnostic-based risk stratification algorithm combined with a clinical medication plan.

Group II: Observation Arm Placebo Group 1 Intervention

Subjects will receive a Reveal LINQ™ Insertable Cardiac Monitor with an investigational ALLEVIATE-HF RAMware download, and will be managed per standard of care for heart failure management without visibility to the heart failure sensor data. Subjects will transition to the intervention arm after 13 months.

Who Is Running the Clinical Trial?

Medtronic Cardiac Rhythm and Heart Failure

Lead Sponsor

Trials

206

Recruited

137,000+

Geoff Martha

Medtronic Cardiac Rhythm and Heart Failure

Chief Executive Officer since 2020

MBA from University of Minnesota

Dr. Kweli Thompson

Medtronic Cardiac Rhythm and Heart Failure

Chief Medical Officer since 2022

MD from Harvard Medical School

Findings from Research

A study involving 28 heart failure patients demonstrated that smartphone-based monitoring, which combined passive data (like movement and social interactions) and active surveys, can effectively predict heart failure decompensation events, achieving a high accuracy with an AUC of 0.83 for a 2-day prediction window.

The findings suggest that social data, such as the frequency and duration of phone calls, can provide valuable insights into a patient's health status, indicating that smartphone monitoring could be a cost-effective alternative to traditional monitoring methods for heart failure management.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Passively Captured Interpersonal Social Interactions and Motion From Smartphones for Predicting Decompensation in Heart Failure: Observational Cohort Study. Cakmak, AS., Perez Alday, EA., Densen, S., et al.[2022]

The Biomon-HF project developed and tested innovative sensors for monitoring vital signs during sleep in 115 heart failure patients, showing promise for personalized telemonitoring and therapy management.

These sensors can help detect heart failure exacerbations and related health issues early, potentially reducing complications and healthcare costs while improving patient outcomes.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Individualized biomonitoring in heart failure--Biomon-HF "Keep an eye on heart failure--especially at night". Vollmer, T., Schauerte, P., Zink, M., et al.[2015]

The Reveal LINQ insertable cardiac monitor (ICM) demonstrated a high positive predictive value for detecting atrial fibrillation (AF), with values of 84% for all episodes and up to 97% for episodes lasting at least one hour in patients with syncope, known AF, and cryptogenic stroke, based on a study of 3759 patients.

The study found that limiting ECG storage to the longest detected AF episode reduced the workload for reviewing episodes without significantly affecting the detection of true AF cases, indicating an efficient monitoring strategy.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Real-world performance of an enhanced atrial fibrillation detection algorithm in an insertable cardiac monitor. Mittal, S., Rogers, J., Sarkar, S., et al.[2022]

References

1. England pubmed.ncbi.nlm.nih.gov

Multiparameter diagnostic sensor measurements during clinically stable periods and worsening heart failure in ambulatory patients. [2021]

2. United States pubmed.ncbi.nlm.nih.gov

A Novel Heart Failure Diagnostic Risk Score Using a Minimally Invasive Subcutaneous Insertable Cardiac Monitor. [2023]

3. England pubmed.ncbi.nlm.nih.gov

The kinocardiograph for assessment of fluid status in patients with acute decompensated heart failure. [2023]

4. Netherlands pubmed.ncbi.nlm.nih.gov

The role of implantable sensors for management of heart failure. [2009]

5. United States pubmed.ncbi.nlm.nih.gov

Remote Left Ventricular Hemodynamic Monitoring Using a Novel Intracardiac Sensor. [2019]

6. Canada pubmed.ncbi.nlm.nih.gov

Passively Captured Interpersonal Social Interactions and Motion From Smartphones for Predicting Decompensation in Heart Failure: Observational Cohort Study. [2022]

7. Germany pubmed.ncbi.nlm.nih.gov

Individualized biomonitoring in heart failure--Biomon-HF "Keep an eye on heart failure--especially at night". [2015]

8. United States pubmed.ncbi.nlm.nih.gov

Miniaturized Reveal LINQ insertable cardiac monitoring system: First-in-human experience. [2016]

9. United States pubmed.ncbi.nlm.nih.gov

Real-world performance of an enhanced atrial fibrillation detection algorithm in an insertable cardiac monitor. [2022]