The study is a multi-center, prospective, non-randomized, observational study to collect data to develop and validate a machine learning algorithm for early detection of worsening heart failure events using multi-parametric sensor data from wearable data capture device The VESTA study will enroll up to 552 subjects in up to 25 centers in order to collect data on a total of at least 56 worsening heart failure events (independently adjudicated hospitalizations or unscheduled intravenous administration of decongestive drugs).The duration of follow-up per participant will be between 3-6 months.
The study is an international, multicenter, prospective, open-label, non-randomized single group study, with no control group. The study has 2 phases: the first phase is to train and develop the automated learning algorithm; the second phase is to validate the algorithm. The participants will be assigned into two cohorts: 1. Cohort 1 will provide the data to be used for algorithm development and training. 2. Cohort 2 will provide data to be used for algorithm validation. It has been estimated that approximately 276 subjects are required for each cohort in order to accumulate the minimum number of cases for the study's primary objective. Sequential enrolment will be implemented by regional blocks according to an estimation of the regional distribution of subjects.The sample size and regional distribution of subjects are estimates and the study is endpoint driven to achieve at least 28 WHF events with corresponding analyzable device data. Fewer subjects may be enrolled should the required number of events be acquired at a faster rate than calculated and the regional proportions of subjects may vary according to regional enrollment rates. All participants will undergo the same study procedures, irrespective of their cohort assignment. Each subject will receive the study device kit (garment and smart phone with charger) at enrollment and will be followed up for up to 6 months, or until at least 28 worsening heart failure (WHF) events per cohort have been acquired. Even if the required number of events have been acquired, all participants will be followed up for a minimum of at least 3 months. The study will collect data; however no data collected by the device will be made available to clinical care personnel during the study and as such no medical action will be taken based on the device. Medical follow-up will be according to standard practice as per each investigational site, which will be documented AND there will be no additional medical intervention on the study participants. The participants are required to agree to be compliant with the use of the device. There is no masking of device allocation or procedures. However, the clinical investigators, treating physicians and the independent clinical events adjudication committee (IEAC) members will be blinded to all sensor data throughout the study. The investigators developing the algorithm will have no access to the validation cohort database before the parameters of the algorithm have been fixed by the training cohort.
System technology/Software
Detection of worsening heart failure (WHF) event
Sensitivity and Specificity of detection of WHF event by a machine-learning algorithm system using multi-parametric data captured by non-invasive telemonitoring. WHF event definition: * Any hospital admission for WHF(e.g. due to new or progressive symptoms/signs of decompensated HF including significant weight gain, worsening dyspnea or fatigue, newly elevated jugular venous pressure, new cardiac S3 gallop rhythm, the development of pulmonary rales, hepatic congestion or lower extremity edema), OR * Any administration of intravenous HF therapy in an unscheduled setting (e.g. clinic/office/emergency department, ED).
Time frame: 6 months
Hospitalizations for HF that did not meet WHF
Algorithm System Detection of HF-associated health care utilization events not eligible to be considered as primary events Number of days hospitalized for HF (total number of days and per hospitalization)
Time frame: 6 months
HF-hospitalization in number of days
System Detection of HF-associated health care utilization events not eligible to be considered as primary events Number of days hospitalized for HF (total number of days and per hospitalization)
Time frame: 6 months
Outpatient health encounters leading to changes or adjustments of oral HF medication
Algorithm System Detection of HF-associated health care utilization events not eligible to be considered as primary events
Time frame: 6 months
Other healthcare encounters do not meet criteria of WHF event, points a, b and c but are deemed related to HF
Algorithm System Detection of HF-associated health care utilization events not eligible to be considered as primary events
Time frame: 6 months
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Study Type
OBSERVATIONAL
Enrollment
552
Number of Adverse and Serious Adverse Events known to be associated with wearable devices with sensors
General device safety will be assessed through adverse event monitoring
Time frame: Occuring during the 6 month follow-up
Acceptability and usability of study data capture device assessed by Study Ergonomics and Usability Questionnaire
Patient-reported data in Ergonomics and Usability Questionnaire administered at monthly intervals. A Likert-like scale is used for scoring, with scores of 1-5, with higher scores signifying agreement with the questions.
Time frame: 6 months
Frequency and duration of study data capture device assessed by Study Frequency and duration of use Questionnaire
Patient-reported data in Frequency and duration of use Questionnaire administered at monthly intervals.
Time frame: 6 months