Artificial intelligence-guided screening for atrial fibrillation using electrocardiogram during sinus rhythm: a prospective non-randomised interventional trial

心房颤动 医学 窦性心律 内科学 正常窦性心律 随机对照试验 心脏病学 节奏 心电图
作者
Peter A. Noseworthy,Zachi I. Attia,Emma Behnken,Rachel Giblon,Katherine A. Bews,Sijia Liu,Tara Gosse,Zachery D Linn,Yihong Deng,Jun Yin,Bernard J. Gersh,Jonathan Graff‐Radford,Alejandro A. Rabinstein,Konstantinos C. Siontis,Paul A. Friedman,Xiaoxi Yao
出处
期刊:The Lancet [Elsevier BV]
卷期号:400 (10359): 1206-1212 被引量:225
标识
DOI:10.1016/s0140-6736(22)01637-3
摘要

Summary

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.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
米米发布了新的文献求助10
刚刚
多年以后发布了新的文献求助10
刚刚
Hello应助稳重的tutu采纳,获得10
1秒前
kuang发布了新的文献求助10
1秒前
向北游发布了新的文献求助10
1秒前
上官若男应助自然白猫采纳,获得10
1秒前
marstar完成签到,获得积分10
2秒前
2秒前
卡卡发布了新的文献求助10
3秒前
qiuqiu发布了新的文献求助10
4秒前
4秒前
keke完成签到,获得积分10
4秒前
酷酷珠发布了新的文献求助10
4秒前
4秒前
sss发布了新的文献求助10
5秒前
5秒前
醋醋完成签到,获得积分20
6秒前
多年以后完成签到,获得积分10
6秒前
zm完成签到,获得积分10
7秒前
柔弱翎完成签到,获得积分10
7秒前
8秒前
8秒前
9秒前
9秒前
9秒前
小方发布了新的文献求助10
9秒前
10秒前
10秒前
11秒前
whiskyzz完成签到,获得积分10
11秒前
11秒前
12秒前
Pw完成签到,获得积分10
12秒前
12秒前
12秒前
风趣小蜜蜂完成签到 ,获得积分10
12秒前
Arlon发布了新的文献求助10
13秒前
13秒前
稳重的tutu发布了新的文献求助10
15秒前
高分求助中
Principles of Economics, 11th Edition 10000
University Physics with Modern Physics, 16th edition 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Matrix Methods in Data Mining and Pattern Recognition 510
Reading and Understanding Health Research 500
Social Skills Improvement System-Rating Scales--Chinese Version 500
Dynamische Polarisation von H-1 und B-11 in (CH-3)-3NBH-3 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7251374
求助须知:如何正确求助?哪些是违规求助? 8873928
关于积分的说明 18730169
捐赠科研通 6931147
什么是DOI,文献DOI怎么找? 3199392
关于科研通互助平台的介绍 2374325
邀请新用户注册赠送积分活动 2174032