Health eHeart BEAT-AFib - Health eHeart Biomarkers of Early Atrial Transformation in Atrial Fibrillation
Study Details
Study Description
Brief Summary
Atrial fibrillation (also known as AFib or AF) is the most common abnormal heart rhythm and results in an irregular beating of the heart. Currently, there is no way of identifying patients at most risk for the development or progression of AFib or those that will best respond to treatment. The purpose of this study is to improve our understanding of AFib and to find new ways of identifying those patients most at risk for developing AFib, have progressive AFib or be less responsive to treatment. For this reason, the investigators are studying imaging, blood, and digital markers that may contribute to AFib
Subjects will receive mobile devices (uch as an AliveCor Kardia and a VivaLnk Wearable ECG patch or similar devices) for remote electrocardiographic (ECG) monitoring. Additionally, subjects will use features using a smartphone research app (on the Eureka Research Platform) to monitor other important things such as activity, sleep, heart rate and others as they are developed. All subjects will receive serial blood draws and saliva sample collections once a year. Subjects will also undergo annual imaging in the form of an echocardiogram (Echo). Evaluations will be taken at baseline and once a year for three years from the baseline visit. Additionally, electronic surveys will be administered periodically (eVisits occurring every 3-6 months) using the mobile app.
Condition or Disease | Intervention/Treatment | Phase |
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Detailed Description
This is a single center, longitudinal, observational cohort study. 3000 subjects are planned to be enrolled. Each subject will be consented, enrolled and assigned to a group based on AF diagnosis (AF Group, AF Risk Group and Control Group). All subjects will be given mobile devices (such as an AliveCor Kardia and a VivaLnk Wearable ECG patch or similar devices) for remote ECG monitoring. Additionally, sleep and activity can be monitored through a smartphone app (on the Eureka Research Platform). All subjects will receive serial blood draws and saliva sample collections to collect serum, plasma, whole blood, DNA and RNA in order to observe/identify any changes in blood-borne AF markers. Subjects will also undergo serial imaging in the form of an Echo to observe/identify markers and/or changes in cardiovascular structure and functioning. Evaluations will be taken at baseline and once a year for three years from their baseline visit. Additionally, electronic surveys will be administered periodically (eVisits occurring every 3-6 months) using the mobile app to observe any changes in participant reported symptoms.
Any participant who receives an AF ablation as part of clinical care will additionally receive one in-person follow-up three months post-ablation procedure and an electronic survey one month post-ablation procedure to observe changes in symptoms after ablation.
Subjects will be followed for at least 3 years. The total duration of the study is expected to be at least 10 years. It is expected that it will take 3-4 years for subject recruitment and at least 3 years for subject follow-up (3 yearly in-person visits), but anticipate the digital follow-up to go beyond that (at least 10 years of digital follow-up)
Study Design
Arms and Interventions
Arm | Intervention/Treatment |
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Control Group Participants undergoing electrophysiologic (EP) study or ablation for supraventricular tachycardia (SVT) with no history of AF and does not meet criteria of At Risk Group or AF Group |
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At Risk Group Participants with no prior diagnosis of AF and have: two or more of the following criteria: Age >65 years of age A diagnosis of hypertension A diagnosis of diabetes A diagnosis of sleep apnea A body mass index (BMI) ≥30 Stable heart failure (HF) with preserved or reduced ejection fraction (New York Heart Association Class I, II or III) Chronic kidney disease (CKD) not requiring dialysis AND/ OR More than 5% premature atrial complex (PAC) burden on ambulatory ECG monitoring (e.g. holter, ZioPatch, Lifewatch, etc.) |
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AF Group Participants who have a history of non-valvular AF or Atrial Flutter (AFL) documented on ECG or ambulatory monitoring within 1 year of enrollment |
Outcome Measures
Primary Outcome Measures
- Incident AF [At Risk Group] [10 years]
Incident AF is defined as the development of a new onset AF in subjects who do not have a previous AF diagnosis. This will be evaluated by detection of arrhythmias by use of ambulatory ECG monitoring (using an VivaLnk Wearable ECG patch and an AliveCor Kardia) and will be diagnosed by an automated algorithm that detects irregularly irregular rhythms. A random 50% of events will be overread by a cardiologist.
- Progression of AF [AF Group] [10 years]
Progression of AF is defined as increase in AF burden which is the amount of time spent in AF over the course of one month as determined by use of ambulatory ECG monitoring (using an VivaLnk Wearable ECG patch and an AliveCor Kardia) and will be diagnosed by an automated algorithm that detects irregularly irregular rhythms. A random 50% of events will be overread by a cardiologist.
Secondary Outcome Measures
- Recurrence of AF after treatment with direct current cardioversion (DCCV) or AF ablation [AF Group] [10 years]
Recurrence of AF will be evaluated by use of ambulatory ECG monitoring (using an VivaLnk Wearable ECG patch and an AliveCor Kardia) and will be diagnosed by an automated algorithm that detects irregularly irregular rhythms. A random 50% of events will be overread by a cardiologist.
- Symptom Burden [AF Group] [10 years]
Symptom Burden will be scored by use of the University of Toronto Atrial Fibrillation Symptom Severity Scale (AFSS) which includes seven questions for subjects to report severity of symptoms (i.e. palpitations, chest pain/discomfort, shortness of breath at rest/physical activity, exercise intolerance, fatigue at rest, and lightheadedness/dizziness) on a Likert scale from 0 (subject did not have this symptom) to 5 (symptom bothers subject a great deal). Total Symptom Burden score is a sum of these seven questions and can range from 0 to 35 with a higher score indicating greater burden.
Eligibility Criteria
Criteria
Inclusion Criteria:
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At least 18 years of age or older
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English speaking
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Able to consent
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ANY one of the following criteria:
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A history of non-valvular AF or AFL documented on ECG or ambulatory monitoring within 1 year of enrollment
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Two or more of the following criteria if no history of AF:
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Age > 65 years of age
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A diagnosis of hypertension
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A diagnosis of diabetes
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A diagnosis of sleep apnea
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A BMI ≥ 30
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Stable HF with preserved or reduced ejection fraction (NYHA Class I, II or III)
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CKD not requiring dialysis
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More than 5% PAC burden on ambulatory ECG monitoring (e.g. Holter, Ziopatch, Lifewatch, etc.)
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Patients undergoing EP study or ablation for SVT with no history of AF and not meeting any of the above criteria (a-c).
Exclusion Criteria:
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Life expectancy < 1 year
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Reversible causes of AF (e.g., post-operative AF, cardiac surgery, pulmonary embolism, untreated hyperthyroidism)
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Pregnant at the time of enrollment
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Unwilling/unable to perform follow-up using digital follow-up
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CKD requiring dialysis
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Presence of a condition or abnormality that, in the opinion of the Investigator, would compromise the safety of the patient or the quality of the data
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Patients undergoing active treatment for cancer or diagnosed with cancer requiring treatment in the last 2 years
Contacts and Locations
Locations
Site | City | State | Country | Postal Code | |
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1 | University of California, San Francisco | San Francisco | California | United States | 94143 |
Sponsors and Collaborators
- University of California, San Francisco
Investigators
- Principal Investigator: Jeffrey E Olgin, MD, University of California, San Francisco
- Principal Investigator: Edward P Gerstenfeld, MD, University of California, San Francisco
- Principal Investigator: Mark J Pletcher, MD, University of California, San Francisco
- Principal Investigator: Gregory Marcus, MD, University of California, San Francisco
Study Documents (Full-Text)
None provided.More Information
Additional Information:
Publications
- Everett TH 4th, Olgin JE. Atrial fibrosis and the mechanisms of atrial fibrillation. Heart Rhythm. 2007 Mar;4(3 Suppl):S24-7. Epub 2006 Dec 28. Review.
- January CT, Wann LS, Calkins H, Chen LY, Cigarroa JE, Cleveland JC Jr, Ellinor PT, Ezekowitz MD, Field ME, Furie KL, Heidenreich PA, Murray KT, Shea JB, Tracy CM, Yancy CW. 2019 AHA/ACC/HRS Focused Update of the 2014 AHA/ACC/HRS Guideline for the Management of Patients With Atrial Fibrillation: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines and the Heart Rhythm Society. J Am Coll Cardiol. 2019 Jul 9;74(1):104-132. doi: 10.1016/j.jacc.2019.01.011. Epub 2019 Jan 28. Erratum in: J Am Coll Cardiol. 2019 Jul 30;74(4):599.
- Kim AM, Olgin JE. Microfibrosis and complex fractionated atrial electrograms. Heart Rhythm. 2009 Jun;6(6):811-2. doi: 10.1016/j.hrthm.2009.03.006. Epub 2009 Mar 3.
- Lee KW, Everett TH 4th, Rahmutula D, Guerra JM, Wilson E, Ding C, Olgin JE. Pirfenidone prevents the development of a vulnerable substrate for atrial fibrillation in a canine model of heart failure. Circulation. 2006 Oct 17;114(16):1703-12. Epub 2006 Oct 9.
- Marcus GM, Yang Y, Varosy PD, Ordovas K, Tseng ZH, Badhwar N, Lee BK, Lee RJ, Scheinman MM, Olgin JE. Regional left atrial voltage in patients with atrial fibrillation. Heart Rhythm. 2007 Feb;4(2):138-44. Epub 2006 Oct 20.
- Rahmutula D, Marcus GM, Wilson EE, Ding CH, Xiao Y, Paquet AC, Barbeau R, Barczak AJ, Erle DJ, Olgin JE. Molecular basis of selective atrial fibrosis due to overexpression of transforming growth factor-β1. Cardiovasc Res. 2013 Sep 1;99(4):769-79. doi: 10.1093/cvr/cvt074. Epub 2013 Apr 23.
- Rahmutula D, Zhang H, Wilson EE, Olgin JE. Absence of natriuretic peptide clearance receptor attenuates TGF-β1-induced selective atrial fibrosis and atrial fibrillation. Cardiovasc Res. 2019 Feb 1;115(2):357-372. doi: 10.1093/cvr/cvy224.
- Sivalokanathan S, Zghaib T, Greenland GV, Vasquez N, Kudchadkar SM, Kontari E, Lu DY, Dolores-Cerna K, van der Geest RJ, Kamel IR, Olgin JE, Abraham TP, Nazarian S, Zimmerman SL, Abraham MR. Hypertrophic Cardiomyopathy Patients With Paroxysmal Atrial Fibrillation Have a High Burden of Left Atrial Fibrosis by Cardiac Magnetic Resonance Imaging. JACC Clin Electrophysiol. 2019 Mar;5(3):364-375. doi: 10.1016/j.jacep.2018.10.016. Epub 2018 Dec 26.
- Staerk L, Wang B, Preis SR, Larson MG, Lubitz SA, Ellinor PT, McManus DD, Ko D, Weng LC, Lunetta KL, Frost L, Benjamin EJ, Trinquart L. Lifetime risk of atrial fibrillation according to optimal, borderline, or elevated levels of risk factors: cohort study based on longitudinal data from the Framingham Heart Study. BMJ. 2018 Apr 26;361:k1453. doi: 10.1136/bmj.k1453.
- Verheule S, Sato T, Everett T 4th, Engle SK, Otten D, Rubart-von der Lohe M, Nakajima HO, Nakajima H, Field LJ, Olgin JE. Increased vulnerability to atrial fibrillation in transgenic mice with selective atrial fibrosis caused by overexpression of TGF-beta1. Circ Res. 2004 Jun 11;94(11):1458-65. Epub 2004 Apr 29.
- BEAT-AFib