Liu Wei-Ting, Lin Chin, Lee Chiao-Chin, Chang Chiao-Hsiang, Fang Wen-Hui, Tsai Dung-Jang, Lin Wen-Yu, Hung Yuan, Chen Kai-Chieh, Lee Chun-Ho, Tsai Tsung-Neng, Lin Wei-Shiang, Hung Yi-Jen, Lin Shih-Hua, Tsai Chien-Sung, Lin Chin-Sheng
Division of Cardiology, Department of Internal Medicine Tri-Service General Hospital, National Defense Medical Center Taipei Taiwan, R.O.C.
Medical Technology Education Center, School of Medicine National Defense Medical Center Taipei Taiwan, R.O.C.
J Am Heart Assoc. 2025 Jul 15;14(14):e042106. doi: 10.1161/JAHA.125.042106. Epub 2025 Jul 3.
Atrial fibrillation (AF) is often underdiagnosed and undertreated by noncardiologists. This study evaluated whether artificial intelligence-enabled ECG (AI-ECG) alerts could improve AF diagnosis and non-vitamin K antagonist oral anticoagulant prescriptions by noncardiologists.
In this open-label, cluster randomized controlled trial (NCT05127460) at 2 hospitals in Taiwan, noncardiologists were randomized to an intervention group (AI-ECG alerts) or control group (usual care). Alerts were sent to physicians when AI-ECG identified AF in emergency or hospitalized patients at risk of stroke (CHA₂DS₂-VASc ≥1 for men, ≥2 for women), excluding those with prior AF or oral anticoagulant use. Primary end points included a non-vitamin K antagonist oral anticoagulant prescription within 90 days after discharge, new AF diagnosis, echocardiogram arrangements, and cardiologist visits. Secondary end points were ischemic stroke, cardiovascular death, and all-cause death.
A total of 8857 and 8960 patients were treated by 120 and 113 noncardiologists in the intervention and control groups, respectively; 275 and 245 patients had AI-detected AF. The non-vitamin K antagonist oral anticoagulant prescription rate was significantly higher in the intervention group (23.3% versus 12.0%; hazard ratio [HR], 1.85 [95% CI, 1.11-3.07]). The intervention group also had a higher rate of AF diagnosis (HR, 1.40 [95% CI, 1.03-1.90]). No significant differences were observed in echocardiogram arrangements, cardiologist visits, or the rates of ischemic stroke, cardiovascular death, and all-cause death.
An AI-ECG alert for AF identification promoted non-vitamin K antagonist oral anticoagulant prescriptions among noncardiologists, thus reducing the disparity in AF care quality between cardiologists and noncardiologists.
URL: https://clinicaltrials.gov/; Unique identifier: NCT05127460.
心房颤动（AF）常被非心脏病专家漏诊和治疗不足。本研究评估了启用人工智能的心电图（AI-ECG）警报能否改善非心脏病专家对AF的诊断以及非维生素K拮抗剂口服抗凝药的处方情况。
在台湾两家医院进行的这项开放标签、整群随机对照试验（NCT05127460）中，非心脏病专家被随机分为干预组（AI-ECG警报）或对照组（常规护理）。当AI-ECG在有中风风险（男性CHA₂DS₂-VASc≥1，女性≥2）的急诊或住院患者中识别出AF时，会向医生发送警报，但排除既往有AF或使用过口服抗凝药的患者。主要终点包括出院后90天内非维生素K拮抗剂口服抗凝药的处方、新的AF诊断、超声心动图检查安排以及心脏病专家会诊。次要终点是缺血性中风、心血管死亡和全因死亡。
干预组和对照组分别有120名和113名非心脏病专家治疗了8857名和8960名患者；275名和245名患者被AI检测出AF。干预组非维生素K拮抗剂口服抗凝药的处方率显著更高（23.3%对12.0%；风险比[HR]，1.85[95%CI，1.11-3.07]）。干预组的AF诊断率也更高（HR，1.40[95%CI，1.03-1.90]）。在超声心动图检查安排、心脏病专家会诊或缺血性中风、心血管死亡和全因死亡的发生率方面未观察到显著差异。
用于识别AF的AI-ECG警报促进了非心脏病专家开具非维生素K拮抗剂口服抗凝药，从而缩小了心脏病专家和非心脏病专家在AF护理质量上的差距。
