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Atrial Fibrillation Risk Estimation With Single-lead Handheld Electrocardiograms

Atrial Fibrillation Risk Estimation With Single-lead Handheld Electrocardiograms

Status
Enrolling by invitation
Phases
Unknown
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT07468123
Acronym
AFRESHE
Enrollment
200
Registered
2026-03-12
Start date
2025-07-30
Completion date
2027-12-31
Last updated
2026-03-12

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Atrial Fibrillation (AF)

Keywords

atrial fibrillation, digital health, screening

Brief summary

The goal of this prospective, non-randomized pilot study is to learn whether predictions from a previously validated 12-lead ECG-based artificial intelligence (AI) algorithm (ECG-AI) identify people more likely to have undiagnosed atrial fibrillation (AF). The main questions it aims to answer are: Do people predicted to have high risk of AF using ECG-AI have a higher rate of new AF diagnosis using 1L ECG screening compared with people predicted to have a low risk? Do AI-based AF risk estimates from the 12-lead ECG correlate with AF risk estimates from the 1L ECG? Do people find 1L ECG screening for AF acceptable and useful? Participants will: Undergo screening with 1L ECG mailed to their home Complete a survey assessing attitudes toward 1L ECG screening Complete a 14-day patch monitor on 1 or 2 occasions depending on 1L ECG results

Detailed description

This is a prospective, non-randomized pilot study designed to assess whether our 12-lead ECG algorithm can identify individuals with AF detectable using 1L ECG. We will also assess whether AF risk estimates from the 1L ECG correlate with those using the 12-lead ECG. We also plan to assess participant attitudes toward the use of 1L ECGs for AF risk estimation. Using our AF risk algorithm on existing 12-lead ECGs, will categorize prospective participants into low AF risk (\<1% 1-year AF risk) versus high AF risk (\>10% 1-year AF risk). We will mail 1L ECG devices to participants and ask them to obtain 3 tracings which we will then use to estimate AF risk using a 1L ECG version of our AF risk algorithm. We will then screen perform patch monitor screening for AF and compare the rates of AF detection between the two groups. This study involves use of two consumer digital devices. The AliveCor KardiaMobile 1L ECG device is an FDA cleared cardiac rhythm assessment device capable of producing a 1L ECG in conjunction with a compatible smartphone. The Zio®XT is an FDA cleared medical-grade 1L ECG rhythm monitor. This pilot study has three main outcomes: 1) prospectively ascertained estimated AF risk using the handheld 1L ECG algorithm, 2) incident AF at 12 months, ascertained using the linked EHR and/or the results of the study patch monitors, and 3) perceived acceptability and usefulness of the handheld ECG. No physical study visits are required according to this protocol.

Interventions

DIAGNOSTIC_TEST1L ECG screening

Individuals will undergo 1L ECG screening using the AliveCor KardiaMobile 1L ECG device

DIAGNOSTIC_TESTPatch monitor

Individuals who are found to have evidence of AF on 1L ECG will undergo assessment with 14-day patch monitor at the time of initial screen. Otherwise all study participants will undergo 14-day patch monitor at the 1-year timepoint.

Sponsors

Massachusetts General Hospital
Lead SponsorOTHER

Study design

Allocation
NON_RANDOMIZED
Intervention model
PARALLEL
Primary purpose
DIAGNOSTIC
Masking
SINGLE (Outcomes Assessor)

Intervention model description

High-risk versus low-risk comparison

Eligibility

Sex/Gender
ALL
Age
18 Years to 90 Years
Healthy volunteers
Yes

Inclusion criteria

* Men and women aged 50-90 who are new or established patients in an MGH primary care or ambulatory cardiology practice * Willing to provide consent to participate in the study to access data from electronic health records (EHR) * At least 1 12-lead ECG obtained within 5 years prior to study start date for AF risk estimation * Have access to a smart phone or tablet to use with the AliveCor KardiaMobile 1L ECG device

Exclusion criteria

* History of atrial fibrillation or atrial flutter as documented in the patient's current electronic health record medical problem list or self-reported diagnosis * Implanted cardiac devices (pacemakers, implantable cardiac defibrillators, or cardiac resynchronization therapy, and implantable loop recorders) * History of allergy to adhesive

Design outcomes

Primary

MeasureTime frameDescription
New AF diagnosis (%)1 yearRate of new AF diagnosis
Acceptability and usefulness0Survey-based acceptability and usefulness of 1L ECG screening process
AI-based AF risk correlation0Correlation between 12-lead ECG-based AF risk and 1L ECG-based AF risk using AI model

Countries

United States

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Mar 13, 2026