Cardiac FailureLINK-HFNCT03037710
Link-HF: Multisensor Non-invasive Telemonitoring System for Prediction of Heart Failure Exacerbation
An observational study of Cardiac Failure, run by Josef Stehlik at 4 sites in United States.
Trial summary
This is a multi-center, non-randomized, non-interventional study to evaluate the accuracy of a remote monitoring and analytical platform for prediction of heart failure exacerbation. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Cardiac Failure
- What is being tested?
- HealthPatch
- Type of treatment
- Medical device
- How many people
- 100 participants
- Where
- 4 sitesUnited States
- Study dates
- Jun 2015to 26 Jan 2017
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Individuals with heart failure, NYHA Class II-IV
Who may be able to join
- Subject must be 18 years old or older
- NYHA( 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.
- Subject willing and able to perform all study related procedures.
Who cannot join
- Expected LVAD (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.
Trial locations and contacts
4 sites in 1 country.
United States4 sites
Malcom Randall VA Medical Center
Gainesville, Florida, 32608
Michael E. DeBakey VA Medical Center
Houston, Texas, 77030
Palo Alto VA Health Care System
Palo Alto, California, 94304
George E Wahlen Medical Center
Salt Lake City, Utah, 84148
About this study
This is a multi-center, non-randomized, non-interventional study to evaluate the accuracy of a remote monitoring and analytical platform for prediction of heart failure exacerbation. The platform acquires continuous multivariate vital signs from HF patients using a new ambulatory wearable (attached by an adhesive) multi-sensor device and analyzes the data using a novel machine learning algorithm.
Read the detailed description
The analytics being investigated includes a Similarity-Based Modeling technique, that empirically estimates the expected physiological behavior of a subject based on prior learned dynamic data, for comparison to actual measured behavior from the subject, to reveal discrepancies hidden by normal variation. The measurements are typically an ensemble of vital signs that effectively characterizes the physiological "control system" of the subject. This technique is multivariate: multiple variables are leveraged, because single variables in isolation have little context - a high heart rate by itself could mean a person is exerting himself, or it could mean his physiology is in distress even though he is not exerting himself. With reference to several other variables, however, such as respiration rate, oximetry and motion/activity, a high heart rate might be recognized as a normal state when accompanied by the corroborating data showing a high respiration rate, a normal oximetry and a high level of motion - the person is exercising.
A wearable adhesive multi-sensor device will be used to collect continuous vital sign and other data from study subjects, including heart rate, respiration rate, bodily motion/activity, skin temperature, pulse, electrocardiogram and peripheral capillary oxygen saturation. Subjects are provided with a smartphone or cellular tablet that will be paired with the multi-sensor device to receive data and upload it to the analytics server via cellular network or WiFi internet. Study staff will interact with the subject during visits scheduled for routine heart failure follow-up to capture pre-specified heart failure medical events. All standard of care clinic and hospitalization notes and procedure reports including echocardiograms, right heart catheterizations, pulmonary function tests, six minute walk tests and radiology reports will be collected as they occur.
- Conditions
- Cardiac Failure
- Being tested
- HealthPatch
- Medical subject headings
- Heart Failure
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
HealthPatchDevice
A multi-sensor device to collect continuous vital signs
What is being measured
The primary outcome is the main question the study is designed to answer.
Detection of Heart Failure Exacerbation Event
Correlation of algorithmic alerts generated by a non-invasive telemonitoring system to a verified heart failure exacerbation event, measured in percent accuracy
Measured: 90 Days
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted31 Jan 2017 (estimated)
- Study startJun 2015
- Primary completion26 Jan 2017
- Study completion26 Jan 2017
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Cardiac FailureStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Other
- Time perspective
- Prospective
- Enrolment
- 100 participants (actual)
Sponsor and investigators
- Lead sponsor
- Josef Stehlik
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor-investigator, Josef Stehlik, University of Utah
- Investigators
- Josef Stehlik, MD, Principal investigator, University of Utah
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03037710
- Sponsor's protocol ID
- 81833
- Acronym
- LINK-HF
- Status last verified
- Aug 2020
- First submitted
- 27 Jan 2017
- Last updated
- 5 Aug 2020
- Results posted
- No
- Data monitoring committee
- No
- Individual data sharing
- No
Publications
Stehlik J, Schmalfuss C, Bozkurt B, Nativi-Nicolau J, Wohlfahrt P, Wegerich S, Rose K, Ray R, Schofield R, Deswal A, Sekaric J, Anand S, Richards D, Hanson H, Pipke M, Pham M. Continuous Wearable Monitoring Analytics Predict Heart Failure Hospitalization: The LINK-HF Multicenter Study. Circ Heart Fail. 2020 Mar;13(3):e006513. doi: 10.1161/CIRCHEARTFAILURE.119.006513. Epub 2020 Feb 25.
PubMed 32093506
Study at a glance
From the registry record, last updated by the sponsor on 5 Aug 2020. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Link-HF: Multisensor Non-invasive Telemonitoring System for Prediction of Heart Failure Exacerbation
- ClinicalTrials.gov ID
- NCT03037710
- Acronym / sponsor ID
- LINK-HF / 81833
- Conditions
- Cardiac Failure
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 100 participants (actual)
- Lead sponsor
- Josef StehlikUniversity, hospital or other
- Study start
- Jun 2015
- Primary completion
- 26 Jan 2017 (actual)
- Study completion
- 26 Jan 2017 (actual)
- First posted
- 31 Jan 2017 (estimated)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This is a multi-center, non-randomized, non-interventional study to evaluate the accuracy of a remote monitoring and analytical platform for prediction of heart failure exacerbation. The platform acquires continuous multivariate vital signs from HF patients using a new ambulatory wearable (attached by an adhesive) multi-sensor device and analyzes the data using a novel machine learning algorithm.
Detailed description
The analytics being investigated includes a Similarity-Based Modeling technique, that empirically estimates the expected physiological behavior of a subject based on prior learned dynamic data, for comparison to actual measured behavior from the subject, to reveal discrepancies hidden by normal variation. The measurements are typically an ensemble of vital signs that effectively characterizes the physiological "control system" of the subject. This technique is multivariate: multiple variables are leveraged, because single variables in isolation have little context - a high heart rate by itself could mean a person is exerting himself, or it could mean his physiology is in distress even though he is not exerting himself. With reference to several other variables, however, such as respiration rate, oximetry and motion/activity, a high heart rate might be recognized as a normal state when accompanied by the corroborating data showing a high respiration rate, a normal oximetry and a high level of motion - the person is exercising.
A wearable adhesive multi-sensor device will be used to collect continuous vital sign and other data from study subjects, including heart rate, respiration rate, bodily motion/activity, skin temperature, pulse, electrocardiogram and peripheral capillary oxygen saturation. Subjects are provided with a smartphone or cellular tablet that will be paired with the multi-sensor device to receive data and upload it to the analytics server via cellular network or WiFi internet. Study staff will interact with the subject during visits scheduled for routine heart failure follow-up to capture pre-specified heart failure medical events. All standard of care clinic and hospitalization notes and procedure reports including echocardiograms, right heart catheterizations, pulmonary function tests, six minute walk tests and radiology reports will be collected as they occur.
Study design
- Observational model
- Other
- Time perspective
- Prospective
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Individuals with heart failure, NYHA Class II-IV
Key inclusion criteria (4 listed)
- Subject must be 18 years old or older
- NYHA( 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.
- Subject willing and able to perform all study related procedures.
Key exclusion criteria (5 listed)
- Expected LVAD (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.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| HealthPatchA multi-sensor device to collect continuous vital signs | Device | – |
Primary outcome
Detection of Heart Failure Exacerbation Event
Time frame: 90 Days
Correlation of algorithmic alerts generated by a non-invasive telemonitoring system to a verified heart failure exacerbation event, measured in percent accuracy
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 5 Aug 2020.
- Results publication: PubMed 32093506Stehlik J, Schmalfuss C, Bozkurt B, Nativi-Nicolau J, Wohlfahrt P, Wegerich S, Rose K, Ray R, Schofield R, Deswal A, Sekaric J, Anand S, Richards D, Hanson H, Pipke M, Pham M. Continuous Wearable Monitoring Analytics Predict Heart Failure Hospitalization: The LINK-HF Multicenter Study. Circ Heart Fail. 2020 Mar;13(3):e006513. doi: 10.1161/CIRCHEARTFAILURE.119.006513. Epub 2020 Feb 25.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Josef Stehlik, MD principal investigator
University of Utah
4 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Cardiac Failure, run by Josef Stehlik at 4 sites in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 5 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 5 Aug 2020. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 4 sites in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Detection of Heart Failure Exacerbation Event (time frame: 90 Days). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT03037710, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 5 Aug 2020.