人工智能估计了心电图性别作为在心房动导管切除后的复发预测因素
Hanjin Park1, Oh-Seok Kwon1,2, Jaemin Shim3
1Division of Cardiology, Department of Internal Medicine, Yonsei University College of Medicine, Yonsei University Health System, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 120-752, Republic of Korea.
European heart journal. Digital health
|July 24, 2025
概括
人工智能启用心电图 (ECG) 的性别差异预测了导管切除后心房 (AF) 的复发,特别是在女性中. 这一发现为个性化AF管理提供了一个新的预后工具.
科学领域:
- 心脏病学 心脏病学
- 人工智能的人工智能
- 医学诊断 医学诊断 医学诊断
背景情况:
- 导管切除后心房 (AF) 复发仍然是一个临床挑战.
- 预测AF复发的标志物对于优化患者管理至关重要.
- 人工智能 (AI) 提供了新的方法来分析复杂的医疗数据,如心电图 (ECG).
研究的目的:
- 研究人工智能启用心电图性别差异的预后价值,预测AF复发后导管切除 Paroxysmal AF.
- 为了确定心电图性别差异是否与经过切除的AF患者的临床特征和结果有关.
主要方法:
- 一个AI-ECG性别预测模型被开发并在大型队列 (MIMIC-IV,CODE-15%,英国生物库) 上验证.
- 从4385名经历了导管切除的阳性AF患者的手术前鼻节律ECG分析了ECG性别差异.
- 在中位数24个月的随访期间,评估了患者特征,手术数据和AF复发率.
主要成果:
- 经心电图性别不一致的患者年龄较大,心力衰竭较多,腹缩充压升高.
- 电脑心电图性别差异与女性左心房扩大有显著的相关性 (经调整的OR 1.67).
- 在ECG性别不一致的女性中,AF复发的5年风险显著更高 (HR1.42),但在男性中并非如此.
结论:
- 术前AI-ECG性别差异是女性导管切除后AF复发的重要独立预测因素.
- 这一发现突显了人工智能衍生的心电图特征在AF管理中的风险分层的潜力.
- 电脑心电图性别差异可能作为一种新的预后生物标志物,用于偏激性AF的个性化治疗策略.
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