Heart Failure (HF) is a highly prevalent disease that also carries high morbidity and mortality. The Food and Drug Administration (FDA) recognizes the importance of developing patient-centric endpoints that are relevant to patients beyond mortality and hospitalizations. Although functional status can be objectively measured by peak exercise oxygen consumption, it is difficult and impractical to implement in large clinical studies, especially in an ambulatory real-world setting. Recently, new mobile health technologies have emerged as clinical tools and offer an opportunity to overcome these challenges in measuring functional capacity and recording symptoms. The goal of this observational study is to evaluate the feasibility of monitoring functional capacity among patients with heart failure (HF) using mobile health monitoring platforms. Everion® and Apple Watch Series 4 and above will be used for this study. The BiovitalsHF® mobile app can capture patients' key cardiopulmonary physiological parameters, functional capacity (using activity patterns, including guided mobile-based 6MWT, audio recording) and assessment of QoL through validated PROs.
Study Type
OBSERVATIONAL
Enrollment
67
Mayo Clinic
Jacksonville, Florida, United States
National University Hospital
Singapore, Singapore
National Heart Centre Singapore
Singapore, Singapore
Tan Tock Seng Hospital
Singapore, Singapore
Changi General Hospital
Singapore, Singapore
Khoo Teck Puat Hospital
Singapore, Singapore
Feasibility of monitoring functional capacity among patients using mobile health monitoring platform
Measurement of correlation between physiology and accelerometer (activity) data/derivatives with: * 6MWT * Patient-reported KCCQ * Lab results
Time frame: 8 weeks
Compliance rate
Compliance rate to measure the feasibility of collecting continuous, biometrics data and ePROs using mobile-health monitoring platform
Time frame: 8 weeks
Drop-out rate
Drop-out rate to measure the feasibility of collecting continuous, biometrics data and ePROs using mobile-health monitoring platform
Time frame: 8 weeks
Mean time worn/day
Mean time worn/day to measure the feasibility of collecting continuous, biometrics data and ePROs using mobile-health monitoring platform
Time frame: 8 weeks
Proportion of time worn that device produces reliable data
Proportion of time worn that device produces reliable data to measure the feasibility of collecting continuous, biometrics data and ePROs using mobile-health monitoring platform
Time frame: 8 weeks
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