人工智能估计了心电图年龄作为心房动导管切除后的复发预测因子
Hanjin Park1, Oh-Seok Kwon1, Jaemin Shim2
1Yonsei University College of Medicine, Yonsei University Health System, Seoul, Republic of Korea.
NPJ digital medicine
|September 5, 2024
概括
应用于心电图 (ECG) 的人工智能 (AI) 算法可以预测年龄. 在AI-ECG年龄和实际年龄之间的差异可以预测导管切除后心房的复发.
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:
- 人工智能 (AI) 算法显示出使用12导电心电图 (ECG) 预测年龄的潜力.
- 在导管切除后预测心房 (AF) 复发仍然是一个临床挑战.
研究的目的:
- 调查AI估计的心电图年龄和时间年龄之间的差异是否可以预测AF复发后导管切除.
- 验证AI-ECG年龄预测模型并评估其预后价值.
主要方法:
- 一个预训练的残余网络模型在跨国数据集上进行了年龄预测的验证.
- AI-ECG年龄估计来自两个独立的AF切除队列的手术前鼻节律ECG.
- 参与者被分为"年龄-心电图" (≥10年年龄差距) 和"正常心电图年龄" (<10年年龄差距) 组.
主要成果:
- 与"正常ECG年龄"组相比",年龄-ECG"组显示AF复发的风险明显更高.
- 这种关联仍然显著,并且独立于时间年龄或左心房直径.
- AI-ECG年龄差异显示了AF复发的预后价值.
结论:
- 术前AI-ECG年龄作为一个有价值的预后指标,用于AF在导管切除后的复发.
- 人工智能-心电图年龄差距为AF患者的风险分层提供了一个新的,非侵入性的标志物.
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