Tulane iPredict, Prevent Study to Evaluate the Progression of Atrial Myopathy.

Official title

Tulane iPredict, Prevent (TiPP) Study

Overview

To evaluate the progression of atrial myopathy through wearable devices and cardiac imaging.

Detailed description

The Tulane iPredict Prevent (TiPP) project aims to study the aging of the heart in a diverse patient population using wearable digital health devices with the help of Samsung and Boston Scientific.

The innovative project seeks to correlate aging of the heart with daily biometric data obtained from wearable digital health devices, using Samsung's Galaxy Watch. Participants' biometric data, which include heart rate, step count, sleep patterns, and more, along with ECG readings from Preventice (Boston Scientific) Body Guardian Mini, will inform a machine learning model, providing real-time risk assessment of cardiovascular events.

In addition to monitoring biometric data, participants will undergo advanced cardiac imaging (CMR) scans at baseline and one-year follow-up to evaluate markers of aging of the heart (atrial myopathy). These scans, paired with the continuous data from the wearable devices, will offer a detailed understanding of the progression of atrial myopathy over time.

The TiPP study's unique approach of leveraging digital health technology represents an exciting innovation in cardiovascular research. This study's findings are expected to revolutionize our understanding of heart aging and, more importantly, the prediction and prevention of heart diseases in diverse patient populations.

Moreover, the study outcomes will allow us to accurately assess the clinical relevance of daily biometric data, leading to improved and personalized care. The insights gathered will be pivotal in informing early preventive interventions, significantly improving patient outcomes and transforming how we approach cardiovascular diseases and arrhythmias.

The primary outcome of the study will be evaluating the progression of atrial myopathy based on CMR scans. Meanwhile, secondary outcomes will include the incidence of heart failure, stroke, hospitalization, arrhythmias, and mortality during the study period.

With the increasing prevalence of cardiovascular diseases globally, the TiPP study, with its novel use of technology and inclusive approach, stands at the forefront of heart disease research, potentially altering the course of cardiovascular treatment and management.

Interventions

• Device Samsung Galaxy Watch Active2
  The Samsung wearable device will collect data; photoplethysmography (PPG) waveforms, heart rate, heart rate variability, step counts, oxygen saturation levels, sleep pattern and quality.

Primary outcome measures

• Atrial Myopathy Progression [Time frame: Based on results from CMR scan at baseline at 12-Months CMR scan]

Secondary outcome measures (5)

• Heart Failure Incidence [Time frame: Through study completion, up to 52 weeks]
• Cerebrovascular Incidence [Time frame: Through study completion, up to 52 weeks]
• Hospitalization Incidence [Time frame: Through study completion, up to 52 weeks]
• Arrhythmias Incidence [Time frame: Through study completion, up to 52 weeks]
• Death Incidence [Time frame: Through study completion, up to 52 weeks]

Eligibility criteria

Inclusion criteria

Participants must meet the following criteria to be enrolled in the trial:

• Participants with atrial fibrillation aged 18 to 79 years old, or
• Participants aged 40 to 79 years old, at moderate or high risk for CVD as defined by the 10-year risk Atherosclerotic Cardiovascular Disease (ASCVD), a validated risk calculation tool.
• Participants who have access to internet/e-mail in their homes.
• Participants who have access to a compatible Android mobile device or compatible iOS mobile device (iPhone 4S or newer, iPad 3 or newer).
• Participants who are able and willing to return to the study clinic one-year following their baseline CMR for a follow-up appointment and 12-month CMR.
• Participants who are able to read, understand, and sign the consent form.

Exclusion criteria

Participants will be excluded from enrollment if any of the following criteria are present:

• Any health-related gadolinium/MRI contraindications (e.g. allergy to gadolinium, pacemakers, Implantable Cardioverter Defibrillators (ICD's), other devices/implants contraindicated for use of MRI, etc.).
• Participants weighing >300 lbs. (MRI quality decreases as BMI increases).
• Participants with renal insufficiency (Glomerular Filtration Rate (GFR) <30 mL per minute per 1.73 m2) or acute/severe renal dysfunction/disease.
• Women who are pregnant at the time of enrollment/consent. (Should a participant become pregnant during the course of the study, no CMR will be performed until 10 days, postpartum).
• Participants who do not have access to the internet/e-mail.
• Participants who do not have a compatible Android mobile device or compatible iOS mobile device (iPhone 4S or newer, iPad 3 or newer).
• Participants with cognitive impairments affecting their ability to be compliant with wearing and maintaining wearable devices.
• Participants who are unable or unwilling to return to the study clinic one-year post baseline for their follow-up appointment and CMR.
• Participants with cognitive impairments who are unable to give informed consent.

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Observational model

Cohort

Study locations

United States · 1 center

• Tulane University School of Medicine — New Orleans

Publications

• Truong VT, Palmer C, Wolking S, Sheets B, Young M, Ngo TNM, Taylor M, Nagueh SF, Zareba KM, Raman S, Mazur W. Normal left atrial strain and strain rate using cardiac magnetic resonance feature tracking in healthy volunteers. Eur Heart J Cardiovasc Imaging. 2020 Apr 1;21(4):446-453. doi: 10.1093/ehjci/jez157. PMID 31504357
• Bieging ET, Morris A, Wilson BD, McGann CJ, Marrouche NF, Cates J. Left atrial shape predicts recurrence after atrial fibrillation catheter ablation. J Cardiovasc Electrophysiol. 2018 Jul;29(7):966-972. doi: 10.1111/jce.13641. Epub 2018 Jun 19. PMID 29846999
• Marrouche NF, Wilber D, Hindricks G, Jais P, Akoum N, Marchlinski F, Kholmovski E, Burgon N, Hu N, Mont L, Deneke T, Duytschaever M, Neumann T, Mansour M, Mahnkopf C, Herweg B, Daoud E, Wissner E, Bansmann P, Brachmann J. Association of atrial tissue fibrosis identified by delayed enhancement MRI and atrial fibrillation catheter ablation: the DECAAF study. JAMA. 2014 Feb 5;311(5):498-506. doi: 10. PMID 24496537
• Cochet H, Mouries A, Nivet H, Sacher F, Derval N, Denis A, Merle M, Relan J, Hocini M, Haissaguerre M, Laurent F, Montaudon M, Jais P. Age, atrial fibrillation, and structural heart disease are the main determinants of left atrial fibrosis detected by delayed-enhanced magnetic resonance imaging in a general cardiology population. J Cardiovasc Electrophysiol. 2015 May;26(5):484-92. doi: 10.1111/jce PMID 25727248
• Siebermair J, Suksaranjit P, McGann CJ, Peterson KA, Kheirkhahan M, Baher AA, Damal K, Wakili R, Marrouche NF, Wilson BD. Atrial fibrosis in non-atrial fibrillation individuals and prediction of atrial fibrillation by use of late gadolinium enhancement magnetic resonance imaging. J Cardiovasc Electrophysiol. 2019 Apr;30(4):550-556. doi: 10.1111/jce.13846. Epub 2019 Jan 24. PMID 30661270
• Perez MV, Mahaffey KW, Hedlin H, Rumsfeld JS, Garcia A, Ferris T, Balasubramanian V, Russo AM, Rajmane A, Cheung L, Hung G, Lee J, Kowey P, Talati N, Nag D, Gummidipundi SE, Beatty A, Hills MT, Desai S, Granger CB, Desai M, Turakhia MP; Apple Heart Study Investigators. Large-Scale Assessment of a Smartwatch to Identify Atrial Fibrillation. N Engl J Med. 2019 Nov 14;381(20):1909-1917. doi: 10.1056/ PMID 31722151
• Majumder S, Mondal T, Deen MJ. Wearable Sensors for Remote Health Monitoring. Sensors (Basel). 2017 Jan 12;17(1):130. doi: 10.3390/s17010130. PMID 28085085

Identifiers

NCT: NCT04703166 · 2849006

Primary sources (government registries)

• ClinicalTrials.gov (US NIH)

View this study on ClinicalTrials.gov ↗