LINK-HF2 - Remote Monitoring Analytics in Heart Failure

NCT04502563 | Completed Results DMC

• 1 other identifier: IIR 19-238
• Study Type: interventional
• Target: 176
• Locations: 1 country
• Sites: 4

Brief Summary

Heart failure (HF) is a type of heart disease that leads to need of admissions to the hospital during worsening of symptoms. These admissions are expensive and very inconvenient for patients. The investigators have previously shown that monitoring of patients with a using a small wearable sensor combined with a mathematical model can detect worsening of HF before the patient needs medical care. In this study the investigators will test whether the remote monitoring and prediction of HF worsening can be used to find out when patients are at risk, change their treatment and avoid a hospitalization. The study will enroll 240 Veterans with HF and randomly assign half of them to monitoring and communication of the information on HF worsening to their medical teams. The investigators hope to find our how to best use this approach in routine care of HF. The investigators also plan to determine if this approach will indeed led to less admissions to the hospital among these patients, shorter hospital stays and better quality of life.

Conditions

Heart Failure

Keywords

heart failure; remote monitoring; predictive analytics; artificial intelligence

Outcome Measures

Primary Outcomes (1)

• Heart Failure Hospitalization Rate

  90-day hospitalization rate in subjects in active arm vs control arm

  90 days

Secondary Outcomes (1)

• Kansas City Cardiomyopathy Questionaire Score

  90 days

Study Arms (2)

Active arm

EXPERIMENTAL

Subjects will undergo remote monitoring, remote monitoring data will be analyzed on a predictive platform, alerts indicating HF worsening shared with treating team, and algorithmic response to alerts implements.

Other: Remote monitoring and predictive analytics

Control

SHAM COMPARATOR

Subjects will wear a sensor, but data from the sensor will not generate alerts and will not be shared with the treating team.

Other: Sham comparator

Interventions

Remote monitoring and predictive analytics OTHER

Subjects will undergo remote monitoring, remote monitoring data will be analyzed on a predictive platform, alerts indicating HF worsening shared with treating team, and algorithmic response to alerts implements.

Active arm

Sham comparator OTHER

Subjects will wear a sensor, but data from the sensor will not generate alerts and will not be shared with the treating team.

Control

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Subject must be 18 years old or older
• New York Heart Association Functional Classification Class II-IV, documented in site's medical record system.
• Subject able and willing to sign Informed Consent Document, and if participating in a patient interview, able to comprehend and agree with items listed in the VA Consent Cover Letter.
• Subject willing and able to perform all study related procedures.

You may not qualify if:

• Expected Left Ventricular Assist Device implantation or heart transplantation in the next 30 days.
• Skin damage or significant arthritis, preventing wearing of device.
• Uncontrolled seizures or other neurological disorders leading to excessive abnormal movements or tremors in the upper body.
• Pregnant women or those who are currently nursing.
• Visual/cognitive impairment that as judged by the investigator does not allow the subject to independently follow rules and procedures of the protocol.

Sponsors & Collaborators

• VA Office of Research and Development: lead
• George E. Wahlen Department of Veterans Affairs Medical Center: collaborator
• Michael E. DeBakey VA Medical Center: collaborator
• VA Palo Alto Health Care System: collaborator
• Malcom Randall VA Medical Center: collaborator
• Hunter Holmes McGuire VA Medical Center: collaborator
• VHA Innovation Ecosystem: collaborator

Study Sites (4)

VA Palo Alto Health Care System, Palo Alto, CA

Palo Alto, California, 94304-1207, United States

Location

North Florida/South Georgia Veterans Health System, Gainesville, FL

Gainesville, Florida, 32608-1135, United States

Location

VA Salt Lake City Health Care System, Salt Lake City, UT

Salt Lake City, Utah, 84148-0001, United States

Location

Hunter Holmes McGuire VA Medical Center, Richmond, VA

Richmond, Virginia, 23249-0001, United States

Location

Related Publications (5)

• Nelson RE, Hyun D, Jezek A, Samore MH. Mortality, Length of Stay, and Healthcare Costs Associated With Multidrug-Resistant Bacterial Infections Among Elderly Hospitalized Patients in the United States. Clin Infect Dis. 2022 Mar 23;74(6):1070-1080. doi: 10.1093/cid/ciab696.

  PMID: 34617118 RESULT

• Sideris K, Weir CR, Schmalfuss C, Hanson H, Pipke M, Tseng PH, Lewis N, Sallam K, Bozkurt B, Hanff T, Schofield R, Larimer K, Kyriakopoulos CP, Taleb I, Brinker L, Curry T, Knecht C, Butler JM, Stehlik J. Artificial intelligence predictive analytics in heart failure: results of the pilot phase of a pragmatic randomized clinical trial. J Am Med Inform Assoc. 2024 Apr 3;31(4):919-928. doi: 10.1093/jamia/ocae017.

  PMID: 38341800 RESULT

• Aaronson KD, Stewart GC, Stevenson LW, Richards B, Khalatbari S, Cascino TC, Ambardekar AV, Stehlik J, Lala A, Kittleson MM, Palardy M, Mountis MM, Pagani FD, Jeffries N, Taddei-Peters WC, Mann DL; REVIVAL Investigators. Optimizing Triage of Ambulatory Patients With Advanced Heart Failure: 2-Year Outcomes From REVIVAL. JACC Heart Fail. 2024 Oct;12(10):1734-1746. doi: 10.1016/j.jchf.2024.05.008. Epub 2024 Jul 3.

  PMID: 38970587 RESULT

• Alba AC, Stehlik J. Dynamic Risk Prediction: A Step Closer to Personalizing Post-LVAD Care. JACC Heart Fail. 2024 Nov;12(11):1913-1914. doi: 10.1016/j.jchf.2024.08.015. Epub 2024 Oct 2. No abstract available.

  PMID: 39365236 RESULT

• Atik FA, Pego-Fernandes PM, Mejia JA, Goldraich LA, Marcondes-Braga FG, Azeka E, Figueira FA, Garcia VD, Haddad L, Cherikh W, Stehlik J, Cogswell R. ABTO Brazilian Transplant Registry and ISHLT Heart Transplant Registry: An Important/Valuable Partnership. Arq Bras Cardiol. 2025 Feb 10;122(1):e20240370. doi: 10.36660/abc.20240370. eCollection 2025. No abstract available. English, Portuguese.

  PMID: 39936696 RESULT

MeSH Terms

Conditions

Heart Failure

Condition Hierarchy (Ancestors)

Heart Diseases; Cardiovascular Diseases

Results Point of Contact

• Title: Dr Josef Stehlik, MD, MPH
• Organization: VA Salt Lake City Health Care System

josef.stehlik@va.gov

(801) 582-1565

Study Officials

• Josef Stehlik, MD MPH

  VA Salt Lake City Health Care System, Salt Lake City, UT

  PRINCIPAL INVESTIGATOR

Publication Agreements

• PI is Sponsor Employee: No
• Restrictive Agreement: No

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: QUADRUPLE
• Who Masked: PARTICIPANT, CARE PROVIDER, INVESTIGATOR, OUTCOMES ASSESSOR
• Masking Details: All subjects will wear non-invasive sensors. The subjects and the investigators will not know whether subjects are randomized to active arm (remote monitoring data shared with treatment team and used for clinical decisions per algorithm) or to control arm (data collected but not shared with treatment team).
• Purpose: HEALTH SERVICES RESEARCH
• Intervention Model: PARALLEL
• Sponsor Type: FED
• Responsible Party: SPONSOR

Model Details: Prospective randomized study

Study Record Dates

• First Submitted: August 4, 2020
• First Posted: August 6, 2020
• Study Start: April 19, 2021
• Primary Completion: August 31, 2024
• Study Completion: October 30, 2024
• Last Updated: April 28, 2026
• Results First Posted: April 28, 2026

Record last verified: 2026-04

Data Sharing

• IPD Sharing: Will not share

Locations

US (4)