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International Multi-center Study to Validate an Early Warning Algorithm for Worsening Heart Failure

NCT04758429 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 552

Last updated 2021-02-17

No results posted yet for this study

Summary

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.

Conditions

Interventions

DEVICE

Machine-learning Algorithm

System technology/Software

Sponsors & Collaborators

  • Chronolife

    lead INDUSTRY

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2021-05-31
Primary Completion
2022-05-31
Completion
2022-05-31

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04758429 on ClinicalTrials.gov