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| ID | Type | Description | Link |
|---|---|---|---|
| A534225 | Other Identifier | UW Madison | |
| Protocol Version 8/6/2024 | Other Identifier | UW Madison | |
| 1UL1TR002373 | U.S. NIH Grant/Contract | View source |
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| Name | Class |
|---|---|
| National Center for Advancing Translational Sciences (NCATS) | NIH |
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This study is being done to establish the feasibility of performing a clinical trial using a mHealth application named YouControl-AFib designed to improve the cardiovascular health of persons with atrial fibrillation. The study will obtain feedback on the app design to inform future versions and will collect preliminary data to support proof-of-concept and potential effect sizes for future trial design.
Primary Objective
Secondary Objectives
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| People using YouControl-A-Fib app | Experimental |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| YouControl-A-Fib mHealth Application | Device | Participants will use the app for 3 months, includes 1 month phone call with Health Coach |
|
| Measure | Description | Time Frame |
|---|---|---|
| Average Number of Participants Recruited Per Month | up to 5 months | |
| Maximum Number of Participants Recruited Per Month | up to 5 months | |
| Mobile App Rating Scale Scores | Mobile App Rating Scale contains several subscales that will each be scored on a scale of 1-5; B-functionality, C-aesthetics, and D-information. Higher scores indicate high levels of functionality, aesthetics, and information quality. | 3 months |
| Measure | Description | Time Frame |
|---|---|---|
| Change in 6-minute walk distance (compared to baseline for each participant) after using the mHealth app for 3 months | baseline, 3 months | |
| Change in daily step count (averaged over 7 days) after using the mHealth app for three months | baseline, 3 months |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Matthew M Kalscheur, MD | UW School of Medicine and Public Health | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| UW School of Medicine and Public Health | Madison | Wisconsin | 53792 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 31450977 | Background | Attia ZI, Friedman PA, Noseworthy PA, Lopez-Jimenez F, Ladewig DJ, Satam G, Pellikka PA, Munger TM, Asirvatham SJ, Scott CG, Carter RE, Kapa S. Age and Sex Estimation Using Artificial Intelligence From Standard 12-Lead ECGs. Circ Arrhythm Electrophysiol. 2019 Sep;12(9):e007284. doi: 10.1161/CIRCEP.119.007284. Epub 2019 Aug 27. |
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This study will comply with the NIH Data Sharing Policy and Policy on the Dissemination of NIH-Funded Clinical Trial Information and the Clinical Trials Registration and Results Information Submission rule. As such, this trial will be registered at ClinicalTrials.gov, and results information from this trial will be submitted to ClinicalTrials.gov. Every attempt will be made to publish results in peer-reviewed journals.
Data from this study may be requested from other researchers 7 years after the completion of the primary endpoint by contacting the PI.
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| ID | Term |
|---|---|
| D001281 | Atrial Fibrillation |
| D009043 | Motor Activity |
| ID | Term |
|---|---|
| D001145 | Arrhythmias, Cardiac |
| D006331 | Heart Diseases |
| D002318 | Cardiovascular Diseases |
| D010335 | Pathologic Processes |
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| Change in intentional activity time (in one week) after using the mHealth app for three months | baseline, 3 months |
| Change in general quality of life questionnaire: SF-12 Score | SF-12 measures the impact of health on the participant's life and is scored from 0-100 where higher scores indicates higher health related quality of life. | baseline, 3 months |
| Change in Patient Health Questionnaire (PHQ-9) Score | PHQ-9 is a 9-item questionnaire scored on a 4 point likert scale from 0-3 for a total possible range of scores from 0-27. Higher scores indicate increased depression. | baseline, 3 months |
| Change in Atrial Fibrillation Effect on Quality of Life Questionnaire (AFEQT) Score | AFEQT is a 20-item survey scored on a 7 point likert scale from 1-7 where higher scores indicate higher effect that atrial fibrillation has on the participant's quality of life. | baseline, 3 months |
| Change in Atrial Fibrillation Symptom Severity (AFSS) Score | AFSS is a 7-item survey scored on a likert scale from 0-5 for a total possible range of scores from 0-35 where higher scores indicate greater symptom severity. | baseline, 3 months |
| Change in Atrial Fibrillation Knowledge Assessment Tool (AFKAT) Score | AFKAT is a 21-item true / false assessment that measures knowledge about atrial fibrillation. Correct answers are scored with a 1 for a total possible range of scores from 0-21. Higher scores indicate increased knowledge of atrial fibrillation. | baseline, 3 months |
| Change in the Life's Essential 8 score after using the mHealth app for three months | Life's Essential 8 score (LE8) is a composite score between 0-100 that assesses a participant's adherence to 8 lifestyle recommendations with improve cardiovascular health: diet, physical activity, smoking habits, body mass index, cholesterol, blood glucose, and sleep duration. Higher scores are indicative of higher adherence to healthy lifestyle. | baseline, 3 months |
| Change in irregular heart rate notifications (in one week) after using the mHealth app for three months | baseline, 3 months |
| Change in ECG-age after using the mHealth app for three months | Participants will obtain single-lead ECGs at baseline and after three months. The time-voltage data are run through an ECG-AI model for estimating ECG-age. ECG-age is a novel metric developed by investigators at Wake Forest. See reference section for relevant publication describing a similar model. Summary results will be reported as ECG-age in years. | baseline, 3 months |
| D013568 |
| Pathological Conditions, Signs and Symptoms |
| D001519 | Behavior |