作者
Xiaoxi Yao, David R Rushlow, Jonathan W Inselman, Rozalina G McCoy, Thomas D Thacher, Emma M Behnken, Matthew E Bernard, Steven L Rosas, Abdulla Akfaly, Artika Misra, Paul E Molling, Joseph S Krien, Randy M Foss, Barbara A Barry, Konstantinos C Siontis, Suraj Kapa, Patricia A Pellikka, Francisco Lopez-Jimenez, Zachi I Attia, Nilay D Shah, Paul A Friedman, Peter A Noseworthy
发表日期
2021/5
期刊
Nature Medicine
卷号
27
期号
5
页码范围
815-819
出版商
Nature Publishing Group US
简介
We have conducted a pragmatic clinical trial aimed to assess whether an electrocardiogram (ECG)-based, artificial intelligence (AI)-powered clinical decision support tool enables early diagnosis of low ejection fraction (EF), a condition that is underdiagnosed but treatable. In this trial (NCT04000087), 120 primary care teams from 45 clinics or hospitals were cluster-randomized to either the intervention arm (access to AI results; 181 clinicians) or the control arm (usual care; 177 clinicians). ECGs were obtained as part of routine care from a total of 22,641 adults (N = 11,573 intervention; N = 11,068 control) without prior heart failure. The primary outcome was a new diagnosis of low EF (≤50%) within 90 days of the ECG. The trial met the prespecified primary endpoint, demonstrating that the intervention increased the diagnosis of low EF in the overall cohort (1.6% in the control arm versus 2.1% in the intervention …
学术搜索中的文章
X Yao, DR Rushlow, JW Inselman, RG McCoy… - Nature Medicine, 2021