12导联穿戴心电设备在院前诊断急性ST段抬高型心肌梗死中的应用

目的 探索12导联穿戴心电设备在院前诊断急性ST段抬高型心肌梗死（STEMI）的应用价值。方法 选取2019年1月～2021年8月“全国心电一张网”中使用12导联穿戴心电设备危急值预警ST改变的441例患者心电图，回顾性分析STEMI病例的基本特点、响应时间及被检者主诉；分析院前穿戴心电图人工判读的STEMI病例、穿戴设备AI智能诊断的STEMI病例的诊断准确性。结果 院前穿戴心电图医生判读为STEMI的患者共89例，其中58例线上预警后去医院就诊，转诊率为65.17%。心电图诊断评估平均用时为153.02 s，心电图诊断审核平均用时为178.06 s。院前穿戴心电图人工判读STEMI、院前穿戴心电设备AI诊断STEMI的敏感度分别为100%、88.37%，特异度分别为95.40%、79.31%。院前穿戴心电图人工判读STEMI、穿戴心电设备AI智能诊断STEMI与临床确诊STEMI具有较高的一致性。结论 12导联穿戴心电设备能够在医院外场景准确记录STEMI患者的心电图，并实现短时间内上传且快速获得诊断。院前穿戴心电图无论是人工判读还是AI诊断STEMI的准确性率均较高。

Application of wearable 12-lead electrocardiogram devices in pre-hospital diagnosis of acute ST segment elevation myocardial infarction

Objective To assess the value of wearable 12-lead electrocardiogram (ECG) devices in pre-hospital diagnosis of acute ST segment elevation myocardial infarction (STEMI). Methods This analysis was conducted among 441 patients selected from the "National ECG Network", who used wearable 12-lead ECG device with critical situation warning of ST change between January 2019, and August, 2021. The general characteristics, response time and complaints of the patients with STEMI were analyzed. The accuracy of pre-hospital diagnosis of STEMI was compared between clinician's interpretation of ECGs and AI diagnosis by the wearable ECG device. Results In 89 of the patients, a pre-hospital diagnosis of STEMI was made by physicians based on ECGs from the wearable devices, and 58 of them sought medical attention after online warning, with a referral rate of 65.17% . The average time for diagnostic assessment of the ECGs was 153.02 s, and the average time for confirmation of the diagnosis was 178.06 s. The sensitivity for pre-hospital diagnosis of STEMI by clinician's interpretation of the ECGs and by AI diagnosis was 100% and 88.37%, respectively, with a specificity of 95.40% and 79.31%, respectively. The pre-hospital diagnosis by clinicians and AI diagnosis of STEMI both showed a high consistency with the subsequent definite clinical diagnosis of STEMI. Conclusion Wearable 12-lead ECG devices can accurately record ECG characteristics of STEMI patients outside the hospital and allow immediate data uploading for an early diagnosis. The diagnoses of STEMI made based on AI technology are highly consistent with those by clinicians, demonstrating excellent clinical performance of the wearable ECG devices.