Monitoring and Self-management of Sleep Fatigue and Dyspnea
1 other identifier
interventional
20
1 country
1
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.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at below P25 for not_applicable
Started Aug 2019
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
Study Start
First participant enrolled
August 15, 2019
CompletedFirst Submitted
Initial submission to the registry
March 11, 2020
CompletedFirst Posted
Study publicly available on registry
June 17, 2020
CompletedPrimary Completion
Last participant's last visit for primary outcome
April 30, 2021
CompletedStudy Completion
Last participant's last visit for all outcomes
April 30, 2021
CompletedJune 17, 2020
June 1, 2020
1.7 years
March 11, 2020
June 12, 2020
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Measure if the Readiband is able to measure Sleep and Fatigue
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.
42 days
Secondary Outcomes (1)
Correlation between data from the Readiband and the PROMIS scales
42 days
Study Arms (1)
Feasibility of Wearing a Readiband
OTHERParticipants 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.
Interventions
On day one of the study participants will complete a demographic survey. On day one, every seventh day and at the end of the study each participant will complete all the scales; The Minnesota Living with Heart Failure Questionnaire (MLHFQ) and Self-Care of Heart Failure Index will be completed on day one and day 60. At the end of the intervention an Interview will be conducted to assess participants experiences using the Readiband: On a scale of 0-10, how would you rate your digital literacy? 2) Why that number? 3) Tell me about a day using the readiband? 4) Were there any challenges to wearing the band, forgetting to wear it, level of comfort wearing the band? Anything else etc..? 5) How did the digital tools enhance your health? 6) Did the use of digital tools cause you to take a proactive approach rather than a reactive approach to your health? 7) As I use the readiband in a next study, what suggestions do you have for me?
Eligibility Criteria
You may qualify if:
- Age 30-85years.
- Diagnosis of heart failure based on patient's medical record.
- Meets the criteria for New York Heart Failure (NYHF) classification for stage I-III heart failure.
- Meets the criteria for ACA/AHA HF classification Stage A and B (Patient with clinical HF).
You may not qualify if:
- list and stage IV HF.
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
University of Massachusetts Amherst
Amherst, Massachusetts, 01003, United States
Related Publications (9)
Benjamin, E.J., Muntner. P., Alonso, A., Bittencourt, M.S., Callaway, C.W., Carson, A.P., Chamberlain, A.M., Chang, A.R., Cheng, S., Das, S.R., Delling, F.N., Djousse, L., Elkind, M.S.V., Ferguson, J.F., Fornage, M., Jordan, L.C., Khan, S.S., Kissela, B.M., Knutson, K.L.,Kwan, T.W., Lackland, D.T., Lewis, T.T., Lichtman, J.H., Longenecker, C.T., Loop, M.S., Lutsey, P.L., Martin, S.S., Matsushita, K., Moran, A.E., Mussolino, M.E., O'Flaherty, M., Pandey, A., Perak, A.M., Rosamond, W.D., Roth, G.A., Sampson, U.K.A., Satou, G.M., Schroeder, E.B., Shah, S.H., Spartano, N.L., Stokes, A., Tirschwell, D.L., Tsao, C.W., Turakhia, M.P., VanWagner, L.B., Wilkins, J.T., Wong, S.S., Virani, S.S. (2019); on behalf of the American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee. Heart disease and stroke statistics-2019 update: a report from the American Heart Association [published online ahead of print January 31, 2019]. Circulation. doi: 10.1161/CIR.0000000000000659.
BACKGROUNDBibbins-Domingo K, Pletcher MJ, Lin F, Vittinghoff E, Gardin JM, Arynchyn A, Lewis CE, Williams OD, Hulley SB. Racial differences in incident heart failure among young adults. N Engl J Med. 2009 Mar 19;360(12):1179-90. doi: 10.1056/NEJMoa0807265.
PMID: 19297571BACKGROUNDBui AL, Fonarow GC. Home monitoring for heart failure management. J Am Coll Cardiol. 2012 Jan 10;59(2):97-104. doi: 10.1016/j.jacc.2011.09.044.
PMID: 22222071BACKGROUNDFatigue Science(2018)Retrieved from https://www.fatiguescience.com
BACKGROUNDHealth Measures (2019).http://www.healthmeasures.net/explore-measurement-systems/promis Heart failure Society of America.(2018)Patient Application. Retrieved from
BACKGROUNDHeart Failure Society of America (20190 HEART FAILURE HEALTH STORYLINES. Retrieved from hfsa.org/patient/patient-tools/patient
BACKGROUNDChen LH, Li CY, Shieh SM, Yin WH, Chiou AF. Predictors of fatigue in patients with heart failure. J Clin Nurs. 2010 Jun;19(11-12):1588-96. doi: 10.1111/j.1365-2702.2010.03218.x.
PMID: 20579199BACKGROUNDRiegel B, Dickson VV, Lee CS, Daus M, Hill J, Irani E, Lee S, Wald JW, Moelter ST, Rathman L, Streur M, Baah FO, Ruppert L, Schwartz DR, Bove A. A mixed methods study of symptom perception in patients with chronic heart failure. Heart Lung. 2018 Mar-Apr;47(2):107-114. doi: 10.1016/j.hrtlng.2017.11.002. Epub 2018 Jan 3.
PMID: 29304990BACKGROUNDU.S. Food and Drugs Administration (2018). Human Factors and Medical Devices. Retrieved from https://www.fda.gov/MedicalDevices/DeviceRegulationandGuidance/Huma
BACKGROUND
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Heather M Hamilton, PhD, RN
University of Massachusetts, Amherst
Central Study Contacts
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- NA
- Masking
- NONE
- Purpose
- DEVICE FEASIBILITY
- Intervention Model
- SINGLE GROUP
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
March 11, 2020
First Posted
June 17, 2020
Study Start
August 15, 2019
Primary Completion
April 30, 2021
Study Completion
April 30, 2021
Last Updated
June 17, 2020
Record last verified: 2020-06