An interventional study of 1L ECG screening and Patch monitor in Atrial Fibrillation (AF), sponsored by Massachusetts General Hospital. Enrolling by invitation at 1 site in United States. Open to participants aged 18 Years to 90 Years, including healthy volunteers. Per ClinicalTrials.gov, last updated 2026-03-12.
Sponsored by Massachusetts General Hospital · Not applicable, Interventional, and Diagnostic
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
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.
3,870 studies on the registry are indexed under Atrial Fibrillation; 924 are open to participants now.
This study's planned enrollment of 200 is above the median of 144 across 2,380 interventional studies indexed under Atrial Fibrillation.
Browse Atrial Fibrillation studies →Massachusetts General Hospital is the lead sponsor of 2,536 studies on the registry; 446 are open to participants now.
Of its 214 completed or terminated interventional studies of FDA-regulated products, 161 (75%) have results posted.
Counted across the registry records on this site, refreshed daily.
Exclusion Criteria:
Low estimated risk for AF (\<1% 1-year AF risk)
Diagnostic Test: 1L ECG screening · Diagnostic Test: Patch monitor
Low estimated risk for AF (\>10% 1-year AF risk)
Diagnostic Test: 1L ECG screening · Diagnostic Test: Patch monitor
Individuals will undergo 1L ECG screening using the AliveCor KardiaMobile 1L ECG device
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.
New AF diagnosis (%)
Rate of new AF diagnosis
Time frame: 1 year
Acceptability and usefulness
Survey-based acceptability and usefulness of 1L ECG screening process
Time frame: 0
AI-based AF risk correlation
Correlation between 12-lead ECG-based AF risk and 1L ECG-based AF risk using AI model
Time frame: 0
Plan to share: No
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Massachusetts General Hospital