Artificial Intelligence-Augmented Electrocardiogram Detection of Left Ventricular Systolic Dysfunction in the General

被引:16
|
作者
Kashou, Anthony H. [1 ]
Medina-Inojosa, Jose R. [1 ]
Noseworthy, Peter A. [1 ]
Rodeheffer, Richard J. [1 ]
Lopez-Jimenez, Francisco [1 ]
Attia, Itzhak Zachi [1 ]
Kapa, Suraj [1 ]
Scott, Christopher G. [2 ]
Lee, Alexander T. [2 ]
Friedman, Paul A. [1 ]
McKie, Paul M.
机构
[1] Mayo Clin, Dept Med, Rochester, MN USA
[2] Mayo Clin, Div Biostat, Rochester, MN USA
基金
美国国家卫生研究院;
关键词
HEART-FAILURE; NATRIURETIC PEPTIDE; COMMUNITY; DIAGNOSIS; HISTORY; ECG; MORTALITY; SURVIVAL; ACCURACY;
D O I
10.1016/j.mayocp.2021.02.029
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Objective: To validate an artificial intelligence-augmented electrocardiogram (AI-ECG) algorithm for the detection of preclinical left ventricular systolic dysfunction (LVSD) in a large community-based cohort. Methods: We identified a randomly selected community-based cohort of 2041 subjects age 45 years or older in Olmsted County, Minnesota. All participants underwent a study echocardiogram and ECG. We first assessed the performance of the AI-ECG to identify LVSD (ejection fraction <40%). After excluding participants with clinical heart failure, we further assessed the AI-ECG to detect preclinical LVSD among all patients (n=1996) and in a high-risk subgroup (n=1348). Next we modelled an imputed screening program for preclinical LVSD detection where a positive AI-ECG triggered an echocardiogram. Finally, we assessed the ability of the AI-ECG to predict future LVSD. Participants were enrolled between January 1, 1997, and September 30, 2000; and LVSD surveillance was performed for 10 years after enrollment. Results: For detection of LVSD in the total population (prevalence, 2.0%), the area under the receiver operating curve for AI-ECG was 0.97 (sensitivity, 90%; specificity, 92%); in the high-risk subgroup (prevalence 2.7%), the area under the curve was 0.97 (sensitivity, 92%; specificity, 93%). In an imputed screening program, identification of one preclinical LSVD case would require 88.3 AI-ECGs and 8.7 echocardiograms in the total population and 65.7 AI-ECGs and 5.5 echocardiograms in the high-risk subgroup. The unadjusted hazard ratio for a positive AI-ECG for incident LVSD over 10 years was 2.31 (95% CI, 1.32 to 4.05; P=.004). Conclusion: Artificial intelligence-augmented ECG can identify preclinical LVSD in the community and warrants further study as a screening tool for preclinical LVSD. (c) 2021 Mayo Foundation for Medical Education and Research center dot Mayo Clin Proc. 2021;96(10):2576-2586
引用
收藏
页码:2576 / 2586
页数:11
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