Study to Develop a Wearable Device Algorithm to Predict Heart Failure Worsening Using a Non-Invasive Ring Sensor

What this Trial Is About

Researchers are conducting an observational pilot study to develop a mathematical algorithm that can predict worsening decompensation of congestive heart failure dCHF. The study focuses on participants who have a remote hemodynamic pulmonary artery pressure monitor. The goal is to use data from a non-invasive wearable device to identify patterns that signal an upcoming heart failure event. Participants with chronic congestive heart failure who use a pulmonary artery pressure monitor will wear a non-invasive ring device continuously for up to 12 months. This wearable collects various physiological data like heart rate, heart rate variability, sleep, activity, oxygen saturation, and temperature. The wearable data will be analyzed in relation to pressure readings from the implanted pulmonary artery sensor to detect early signs of heart failure worsening. Participants can also choose to provide biospecimens DNA, blood, urine and weekly voice samples to support future biomarker research. During the study, participants will be monitored for at least 6 months and up to 12 months. The wearable device collects data continuously, but this information is not used for clinical decisions. Researchers will measure changes in physiological parameters that correlate with heart failure decompensation events. Participants will continue their usual heart failure care while contributing data to help develop predictive tools for future use.

Observational Study Designed to Detect Decompensation of Congestive Heart Failure (dCHF) Using a Non-Invasive Wearable Device