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Link-HF, Phase II: Multisensor Non-invasive Telemonitoring System for Prediction of Heart Failure Exacerbation (LINK-HF)

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ClinicalTrials.gov Identifier: NCT03037710
Recruitment Status : Completed
First Posted : January 31, 2017
Last Update Posted : January 9, 2018
Sponsor:
Information provided by (Responsible Party):
Josef Stehlik, University of Utah

Tracking Information
First Submitted Date January 27, 2017
First Posted Date January 31, 2017
Last Update Posted Date January 9, 2018
Study Start Date June 2015
Actual Primary Completion Date January 26, 2017   (Final data collection date for primary outcome measure)
Current Primary Outcome Measures
 (submitted: January 27, 2017)
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
Original Primary Outcome Measures Same as current
Change History Complete list of historical versions of study NCT03037710 on ClinicalTrials.gov Archive Site
Current Secondary Outcome Measures Not Provided
Original Secondary Outcome Measures Not Provided
Current Other Pre-specified Outcome Measures Not Provided
Original Other Pre-specified Outcome Measures Not Provided
 
Descriptive Information
Brief Title Link-HF, Phase II: Multisensor Non-invasive Telemonitoring System for Prediction of Heart Failure Exacerbation
Official Title Link-HF, Phase II: Multisensor Non-invasive Telemonitoring System for Prediction of Heart Failure Exacerbation
Brief 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. 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 Type Observational
Study Design Observational Model: Other
Time Perspective: Prospective
Target Follow-Up Duration Not Provided
Biospecimen Not Provided
Sampling Method Non-Probability Sample
Study Population Individuals with heart failure, NYHA Class II-IV
Condition Cardiac Failure
Intervention Device: HealthPatch
A multi-sensor device to collect continuous vital signs
Study Groups/Cohorts Not Provided
Publications * Not Provided

*   Includes publications given by the data provider as well as publications identified by ClinicalTrials.gov Identifier (NCT Number) in Medline.
 
Recruitment Information
Recruitment Status Completed
Actual Enrollment
 (submitted: January 27, 2017)
100
Original Actual Enrollment Same as current
Actual Study Completion Date January 26, 2017
Actual Primary Completion Date January 26, 2017   (Final data collection date for primary outcome measure)
Eligibility Criteria

Inclusion Criteria:

  1. Subject must be 18 years old or older
  2. NYHA( New York Heart Association Functional Classification) Class II-IV, documented in site's medical record system.
  3. Subject able and willing to sign Informed Consent Document.
  4. Subject willing and able to perform all study related procedures.

Exclusion Criteria:

  1. Expected LVAD (Left Ventricular Assist Device) implantation or heart transplantation in the next 30 days.
  2. Skin damage or significant arthritis, preventing wearing of device.
  3. Uncontrolled seizures or other neurological disorders leading to excessive abnormal movements or tremors in the upper body.
  4. Pregnant women or those who are currently nursing.
  5. Visual/cognitive impairment that as judged by the investigator does not allow the subject to independently follow rules and procedures of the protocol.
Sex/Gender
Sexes Eligible for Study: All
Ages 18 Years and older   (Adult, Older Adult)
Accepts Healthy Volunteers No
Contacts Contact information is only displayed when the study is recruiting subjects
Listed Location Countries United States
Removed Location Countries  
 
Administrative Information
NCT Number NCT03037710
Other Study ID Numbers 81833
Has Data Monitoring Committee No
U.S. FDA-regulated Product Not Provided
IPD Sharing Statement
Plan to Share IPD: No
Responsible Party Josef Stehlik, University of Utah
Study Sponsor Josef Stehlik
Collaborators Not Provided
Investigators
Principal Investigator: Josef Stehlik, MD University of Utah
PRS Account University of Utah
Verification Date January 2018