Monitoring and Self-management of Sleep Fatigue and Dyspnea
- Conditions
- Heart Failure Patients
- Interventions
- Device: Feasibility of wearing a Readiband to monitor Sleep and Fatigue
- Registration Number
- NCT04434716
- Lead Sponsor
- University of Massachusetts, Amherst
- Brief Summary
African Americans have the highest risk for developing heart failure. When African Americans are diagnosed with heart failure (AAHF) it is usually more advanced HF compared to other races. African-Americans have the highest rate of hospitalization for HF compared to any other ethnic groups. Thus, life style modification, awareness of signs and symptoms of HF by continuous, rather than intermittent monitoring, is essential in beginning to develop HF interventions that can provide early detection. Early interventions would lead to reduced re-hospitalization, prevent hospital readmission and reduce the mortality rate associated with HF.
- Detailed Description
Symptoms of heart failure due to circulatory fluid overload: Signs of circulatory fluid overload are theleading to cardiac decompensation or worsening heart failure are: orthopnea, dyspnea, fatigue, weight gain, abdominal swelling, fluid retention, extended jugular vein, leg edema, crackles, and ascites. Identifying early signs of CFO in HF would provide patients more time to respond and self-manage symptoms at home.
Currently most HF patients are monitored intermittently for changes in symptoms
. According to the American Heart Association establishing self- monitoring practices is the best method for improving health behaviors and health outcomes in individuals.
Fatigue and sleep in HF and gaps in symptom self-management: Fatigue in heart failure patients was previously measured using a self-reported questionnaire and concluded that identifying fatigue early could result in initiation of treatment to prevent HF decompensation. A study by also concluded that severe HF symptoms are associated with higher levels of fatigue in HF patients. found that increases in fatigue in cardiovascular patients resulted in poorer self-care and poorer cardiovascular outcomes, but fatigue was not an indication of disease severity. . Similarly another study concluded that there is a relationship between sleep, fatigue and functional performance in HF patients. However, sleep, fatigue and HF symptoms were only intermittently, rather than continuously, monitored in these studies to assess its impact on HF patient outcomes.
The wrist-worn wearable device, Readiband (Fatigue Science)has a 93 accuracy rate in measuring sleep. The Readiband and the biomathematical fatigue model SAFTE (Sleep, Activity, Fatigue, and Task Effectiveness)have being successfully used to measure sleep and fatigue in multiple areas of research The Readiband has a one month battery life and has the ability to sync to mobile phones, or iPads via a Sync app. It allows for Minute-by-minute actigraphy values and sleep/wake classification. The Readiband has the ability to track, high recurring wake episodes, frequency of daytime sleep episodes, high sleep latency, wake after sleep onset and total sleep quantity. The Readiband has been used successfully to measure fatigue in athletes and law enforcement officers In the following studies the Readiband was use to assess the correlation between sleep and fatigue: risk for accidents in medical residents risk for making medical errors, and to predict football player's risk for injury Each study has shown some level of statistical significance of the relationship between sleep and fatigue. This study is adding another component of assessing if sleep and fatigue correlates with increase severity of HF symptoms.The SAFTE Fatigue Model (Sleep, Activity, Fatigue, and Task Effectiveness)will interpret the data collected from the Readiband. The SAFTE Fatigue Model and the Readiband has never been use to monitor the correlation between sleep, fatigue and decompensation in HF symptoms. The data from the Readiband will be transmitted to the SAFTE Fatigue model. The data will analyze the patient sleep wake pattern to detect patient's level of fatigue and data will be provided with the patient.
Recruitment & Eligibility
- Status
- UNKNOWN
- Sex
- All
- Target Recruitment
- 20
Not provided
Not provided
Study & Design
- Study Type
- INTERVENTIONAL
- Study Design
- SINGLE_GROUP
- Arm && Interventions
Group Intervention Description Feasibility of Wearing a Readiband Feasibility of wearing a Readiband to monitor Sleep and Fatigue Participants will wear the Fatigue Science Readiband for 42 consecutive day. On day one, every seventh day and at the end of the study each participant will complete the Dyspnea-Characteristic scale, BRICS NINR PROMIS Fatigue Short Form6a scale , Modified Pulmonary Functional Status, Dyspnea Questionnaire and the BRICS NINR PROMIS SF v1.0-Sleep Disturbance 6a scale.The Minnesota Living with Heart Failure Questionnaire and Self-Care of Heart Failure Index will be completed on day one and day 60. The purpose of this intervention is to assess the Feasibility of Wearing a Readiband. Semi-structured Interview will be conducted at the end of 42 days to assess patient comfort and challenges with wearing the Readiband.
- Primary Outcome Measures
Name Time Method Measure if the Readiband is able to measure Sleep and Fatigue 42 days Specific Aim #1: To evaluate the ability of HF patients to continuously wear a wrist-worn device (Readiband) for up to 42 days to monitor fatigue, activity and sleep.
These data will be gathered via the Readiband which is a wrist-worn device. It is not an instrument or a scale. The wrist-worn wearable device, Readiband (Fatigue Science) has a 93% accuracy rate in measuring sleep The Readiband and the biomathematical fatigue model SAFTE (Sleep, Activity, Fatigue, and Task Effectiveness) have being successfully used to measure sleep and fatigue in multiple areas of research.
- Secondary Outcome Measures
Name Time Method Correlation between data from the Readiband and the PROMIS scales 42 days Specific Aim #2: To determine if HF patients can use and interpret the data obtained from a wrist-worn device on their level of fatigue, activity, sleep, and other symptoms to self-manage symptoms. This aim will be addressed via descriptive statistics that will present items completed by study participants that reflect the use and ability of study participants to interpret data the data obtained from a wrist-worn device on their level of fatigue and sleep(BRICS NINR PROMIS Fatigue Short Form6a scale and the BRICS NINR PROMIS SF v1.0-Sleep Disturbance 6a scale) Readiband will be worn for 42 days and data will be generated on a daily basis.
Trial Locations
- Locations (1)
University of Massachusetts Amherst
🇺🇸Amherst, Massachusetts, United States