发表机构
Walkky LLC; Northwell Cardiovascular Institute; Lenox Hill Hospital; Weiss Consulting Groups; St. Lawrence Health; Clemson University（沃基有限责任公司; 诺斯韦尔心血管研究所; 伦诺克斯山医院; 魏斯咨询集团; 圣劳伦斯医疗; 克莱姆森大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究训练视觉Transformer集成模型，利用多站点12导联心电图数据检测LVEF降低，在外部队列中表现优异，为常规心电图用于左心室收缩功能障碍分诊提供支持。
AI 中文摘要
左心室射血分数（LVEF）降低常无症状，往往在心力衰竭进展后才被发现。心电图虽常规记录却未充分用于该病症，因LVEF降低无单一诊断波形。我们从头训练视觉Transformer集成模型，分析每一次心跳，从12导联心电图检测LVEF降低（≤40%），所用数据来自美国三个医疗系统七个站点的10142名患者。在来自三个地理独立美国临床站点的4092名患者的保留外部队列中，该队列真实世界LVEF降低患病率为8.72%，模型达到0.88的AUROC（95%置信区间0.86-0.89）、81.2%的灵敏度、81.0%的特异性和97.8%的阴性预测值。在性别、种族、族裔和合并症亚组中灵敏度保持较高，而在老年患者及心房颤动或心肌病患者中特异性较低。心跳级注意力图为模型预测提供可解释性，显示其一致关注QRS波群而非P波。这些发现支持常规心电图作为可扩展的初步分诊步骤，用于识别应接受超声心动图检查以评估不同患者群体射血分数降低的患者的潜力。
英文摘要
Reduced left ventricular ejection fraction (LVEF) is frequently asymptomatic and often detected only after advanced heart failure develops. Electrocardiograms are recorded routinely yet underused for this condition, because reduced LVEF has no single diagnostic waveform. We trained an ensemble of vision transformers from scratch to detect reduced LVEF ($\leq$40%) from 12-lead ECGs, analyzing each heartbeat individually, using 10,142 patients across seven sites in three US health systems. In a held-out external cohort of 4,092 patients from three geographically independent US clinical sites at a real-world reduced-LVEF prevalence of 8.72%, the model achieved an AUROC of 0.88 (95% CI 0.86-0.89), sensitivity 81.2%, specificity 81.0%, and negative predictive value 97.8%. Sensitivity remained high across sex, race, ethnicity, and comorbidity subgroups, while specificity was lower in older patients and those with atrial fibrillation or cardiomyopathy. Beat-level attention maps provided interpretability into the model's predictions, showing consistent focus on the QRS complex rather than the P wave. These findings support the potential of routine ECGs as a scalable first-pass triage step to identify patients who should undergo echocardiography for reduced ejection fraction across diverse patient populations.
Comments19 pages, 5 figures, 5 tables; includes supplementary material with 3 additional figures
