• Peter A Noseworthy, Zachi I Attia, Emma M Behnken, Rachel E Giblon, Katherine A Bews, Sijia Liu, Tara A Gosse, Zachery D Linn, Yihong Deng, Jun Yin, Bernard J Gersh, Jonathan Graff-Radford, Alejandro A Rabinstein, Konstantinos C Siontis, Paul A Friedman, and Xiaoxi Yao.
• Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA; Robert D and Patricia E Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA. Electronic address: noseworthy.peter@mayo.edu.
• Lancet. 2022 Oct 8; 400 (10359): 1206-1212.

BackgroundPrevious 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.MethodsFor 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.Findings1003 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).InterpretationAn 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.FundingMayo Clinic Robert D and Patricia E Kern Center for the Science of Health Care Delivery.Copyright © 2022 Elsevier Ltd. All rights reserved.

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