Artificial intelligence-guided screening for atrial fibrillation using electrocardiogram during sinus rhythm: a prospective non-randomised interventional trial
Abstract
Background Previous atrial fibrillation screening trials have highlighted the need for more targeted approaches. We did a pragmatic study to evaluate the effectiveness of an artificial intelligence (AI) algorithm-guided targeted screening approach for identifying previously unrecognised atrial fibrillation.Methods For this non-randomised interventional trial, we prospectively recruited patients with stroke risk factors but with no known atrial fibrillation who had an electrocardiogram (ECG) done in routine practice. Participants wore a continuous ambulatory heart rhythm monitor for up to 30 days, with the data transmitted in near real time through a cellular connection. The AI algorithm was applied to the ECGs to divide patients into high-risk or low-risk groups. The primary outcome was newly diagnosed atrial fibrillation. In a secondary analysis, trial participants were propensity-score matched (1:1) to individuals from the eligible but unenrolled population who served as real-world controls. This study is registered with ClinicalTrials.gov, NCT04208971.Findings 1003 patients with a mean age of 74 years (SD 8·8) from 40 US states completed the study. Over a mean 22·3 days of continuous monitoring, atrial fibrillation was detected in six (1·6%) of 370 patients with low risk and 48 (7·6%) of 633 with high risk (odds ratio 4·98, 95% CI 2·11-11·75, p=0·0002). Compared with usual care, AI-guided screening was associated with increased detection of atrial fibrillation (high-risk group: 3·6% [95% CI 2·3-5·4] with usual care vs 10·6% [8·3-13·2] with AI-guided screening, p<0·0001; low-risk group: 0·9% vs 2·4%, p=0·12) over a median follow-up of 9·9 months (IQR 7·1-11·0).Interpretation An AI-guided targeted screening approach that leverages existing clinical data increased the yield for atrial fibrillation detection and could improve the effectiveness of atrial fibrillation screening.Funding Mayo Clinic Robert D and Patricia E Kern Center for the Science of Health Care Delivery.
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Contemporary examples of clinical applications in cardiology include the use of ECGs to predict left ventricular dysfunction or future development of atrial fibrillation (AF).
“Contemporary examples of these clinical applications in cardiology include the use of ECGs to predict left ventricular dysfunction or future development of atrial fibrillation (AF).[13][14][15][16]”
From Unlocking Tomorrow’s Health Care: Expanding the Clinical Scope of Wearables by Applying Artificial Intelligence (2024) · cites this paper as [15]
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References 26 · Cited by 257
- Authors
- Noseworthy, P. A., Attia, Z. I., Behnken, E. M., Giblon, R. E., Bews, K. A., Liu, S., Gosse, T. A., Linn, Z. D., Deng, Y., Yin, J., Gersh, B. J., Graff-Radford, J., Rabinstein, A. A., Siontis, K. C., Friedman, P. A., & Yao, X.
- Affiliations
- Mayo Clinic (US)
- Corresponding author
- Noseworthy, Peter A
- ORCID
- Venue
- The Lancet
- Publisher
- Elsevier BV
- Published
- 2022-10
- Volume
- 400
- Issue
- 10359
- Pages
- 1206-1212
- ISSN
- 0099-5355 (ISSN-L)
- 0140-6736
- OpenAlex
- W4297231385
- Cited by
- 257
- References
- 26
- Citations by year
- 2026: 65 · 2025: 70 · 2024: 71 · 2023: 46 · 2022: 5
- FWCI
- 33.40
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- The Lancet (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Mayo Clinic
- Topics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Atrial Fibrillation Management and Outcomes
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › ECG Monitoring and Analysis
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiac electrophysiology and arrhythmias
- Keywords
- atrial fibrillation, artificial intelligence, targeted screening, electrocardiogram, sinus rhythm, stroke risk factors, newly diagnosed atrial fibrillation, risk stratification, atrial fibrillation detection
- MeSH terms
- Aged, Artificial Intelligence, Atrial Fibrillation, Electrocardiography, Humans, Mass Screening, Prospective Studies
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