Department of Clinical Medicine, University of Copenhagen, Blegdamsvej 3B, 2200, Copenhagen, Denmark.
Department of Cardiology, Copenhagen University Hospital Bispebjerg, Copenhagen, Denmark.
Heart Fail Rev. 2023 Mar;28(2):419-430. doi: 10.1007/s10741-022-10283-1. Epub 2022 Nov 8.
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.
筛查左心室收缩功能障碍（LVSD），即左心室射血分数（LVEF）降低，值得重新关注，因为预防和延缓心力衰竭的医学治疗方法正在不断进步。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 中搜索了 2010 年 1 月至 2022 年 4 月间“心电图”、“心力衰竭”、“收缩功能障碍”和“人工智能”等术语的变体，并选择了报告使用 AIeECG 检测 LVSD 的诊断准确性和混杂因素的研究。在 40 篇文章中，我们确定了 15 篇相关研究；11 项回顾性队列研究、3 项前瞻性队列研究和 1 项病例系列研究。虽然使用了各种 LVEF 阈值，但 AIeECG 检测 LVSD 的 AUC 中位数为 0.90（0.85 至 0.95 的 IQR），敏感性为 83.3%（73 至 86.9%的 IQR），特异性为 87%（84.5 至 90.9%的 IQR）。AIeECG 算法在广泛的性别、年龄和合并症范围内都取得了成功，并且在非心脏病学环境中以及与利钠肽检测联合使用时似乎特别有用。此外，假阳性的 AIeECG 表明未来会发生 LVSD。没有研究调查其对治疗或患者结局的影响。本系统评价证实了一种新的通用生物标志物 AIeECG 的出现，该标志物可改善 LVSD 的检测。AIeECG 将与利钠肽和超声心动图一起，改善 LVSD 的筛查，但需要进行前瞻性随机实施试验，附加治疗，以显示成本效益和临床意义。
