Heart Failure Reviews ( IF 4.5 ) Pub Date : 2022-11-08 , DOI: 10.1007/s10741-022-10283-1 Laura Vindeløv Bjerkén 1 , Søren Nicolaj Rønborg 2 , Magnus Thorsten Jensen 3, 4, 5 , Silas Nyboe Ørting 6 , Olav Wendelboe Nielsen 1, 2
Screening for left ventricular systolic dysfunction (LVSD), defined as reduced left ventricular ejection fraction (LVEF), deserves renewed interest as the medical treatment for the prevention and progression of heart failure improves. We aimed to review the updated literature to outline the potential and caveats of using artificial intelligence–enabled electrocardiography (AIeECG) as an opportunistic screening tool for LVSD.
We searched PubMed and Cochrane for variations of the terms “ECG,” “Heart Failure,” “systolic dysfunction,” and “Artificial Intelligence” from January 2010 to April 2022 and selected studies that reported the diagnostic accuracy and confounders of using AIeECG to detect LVSD.
Out of 40 articles, we identified 15 relevant studies; eleven retrospective cohorts, three prospective cohorts, and one case series. Although various LVEF thresholds were used, AIeECG detected LVSD with a median AUC of 0.90 (IQR from 0.85 to 0.95), a sensitivity of 83.3% (IQR from 73 to 86.9%) and a specificity of 87% (IQR from 84.5 to 90.9%). AIeECG algorithms succeeded across a wide range of sex, age, and comorbidity and seemed especially useful in non-cardiology settings and when combined with natriuretic peptide testing. Furthermore, a false-positive AIeECG indicated a future development of LVSD. No studies investigated the effect on treatment or patient outcomes.
This systematic review corroborates the arrival of a new generic biomarker, AIeECG, to improve the detection of LVSD. AIeECG, in addition to natriuretic peptides and echocardiograms, will improve screening for LVSD, but prospective randomized implementation trials with added therapy are needed to show cost-effectiveness and clinical significance.
中文翻译:
人工智能支持心电图筛查左心室收缩功能障碍:系统评价
随着心力衰竭预防和进展的药物治疗的改善,左心室收缩功能障碍(LVSD)(定义为左心室射血分数(LVEF)降低)的筛查值得重新引起人们的兴趣。我们旨在回顾最新文献,概述使用人工智能心电图 (AIeECG) 作为 LVSD 机会性筛查工具的潜力和注意事项。
我们在 PubMed 和 Cochrane 上搜索了 2010 年 1 月至 2022 年 4 月期间术语“ECG”、“心力衰竭”、“收缩功能障碍”和“人工智能”的变体,并选择了报告使用 AIeECG 检测的诊断准确性和混杂因素的研究。左室舒张末期。
在 40 篇文章中,我们确定了 15 篇相关研究;十一个回顾性队列、三个前瞻性队列和一个病例系列。尽管使用了各种 LVEF 阈值,AIeECG 检测到的 LVSD 中位 AUC 为 0.90(IQR 从 0.85 至 0.95),敏感性为 83.3%(IQR 从 73 至 86.9%),特异性为 87%(IQR 从 84.5 至 90.9%) )。 AIeECG 算法在广泛的性别、年龄和合并症中取得了成功,并且在非心脏病学背景下以及与利尿钠肽测试相结合时似乎特别有用。此外,假阳性 AIeECG 表明 LVSD 的未来发展。没有研究调查其对治疗或患者结果的影响。
这项系统评价证实了一种新的通用生物标志物 AIeECG 的出现,可以改善 LVSD 的检测。除了利钠肽和超声心动图之外,AIeECG 将改善 LVSD 的筛查,但需要进行前瞻性随机实施试验并增加治疗,以显示成本效益和临床意义。