人工智能在心电图信号中用于预测心脏突然死亡:系统性审查和元分析
Shuang He1, Ming Du1, Zhao Wang1
1Department of Cardiology, People's Hospital of Liaoning Province, Shenyang, Liaoning, China.
Systematic reviews
|December 20, 2025
概括
人工智能 (AI) 在使用心电图 (ECG) 分析预测突然心脏病死亡 (SCD) 方面表现有前途. 然而,目前的发现是初步的,需要在不同的临床环境中进一步验证.
科学领域:
- 心脏病学 心脏病学
- 医疗信息学 医疗信息学
- 人工智能的人工智能
背景情况:
- 突然心脏病死亡 (SCD) 仍然是死亡的一个重要原因.
- 电心电图 (ECG) 是心脏评估的主要工具.
- 为SCD开发准确的预测工具对于早期干预至关重要.
研究的目的:
- 系统地评估人工智能 (AI) 算法的诊断性能,从心电图 (ECG) 数据中检测突然心脏死亡 (SCD) 风险.
- 综合现有关于基于人工智能的心电图分析用于SCD预测的研究证据.
主要方法:
- 在主要数据库 (PubMed,科学网,Embase,IEEE Xplore) 进行了全面的文献搜索,截至2025年4月.
- 采用双变的随机效应元分析,将灵敏度,特异性和AUC值结合起来.
- 研究质量和证据确定性分别使用QUADAS-2和GRADE框架进行评估.
主要成果:
- 分析包括27项涉及2613名患者的研究.
- 人工智能模型在不同的心电图分析方法中实现了高诊断性能:灵敏度从0.87到0.96不等,特异性从0.91到0.99.
- 曲线下的面积 (AUC) 值始终很高,表明强大的预测能力 (0.93-0.99).
结论:
- 基于人工智能的心电图分析显示了预测突然心脏病死亡的巨大潜力.
- 目前的证据虽然有希望,但来源于研究环境中的异质研究.
- 使用标准化方法进行前性多中心研究对于确认可通用性和临床实用性至关重要.
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