在心力衰竭患者中优化心脏突然死亡的初级预防
Nicolai Wallace1, Karren Wong1, Taylor Desmarais1
1Cardiology Department, University of California-San Diego, La Jolla, California, USA.
Journal of the American College of Cardiology
|July 30, 2025
概括
目前对心力衰竭 (HF) 中植入式心脏转换器-除器 (ICD) 的指导方针可能不是最佳的,因为突然心脏死亡 (SCD) 风险下降. 需要使用人工智能和机器学习的新预测模型,以便更好地将ICD的好处与个体患者的风险保持一致.
科学领域:
- 心脏病学 心脏病学
- 医疗技术 医疗技术 医学技术
- 预测分析是一种预测分析.
背景情况:
- 植入式心脏转换器-除器 (ICD) 对于预防心力衰竭 (HF) 患者的突然心脏死亡 (SCD) 至关重要.
- 目前的ICD植入指南主要依赖于左心室喷射率 (LVEF) 的减少,这一标准可能不再准确地反映SCD风险,因为医疗管理的改善.
- 尽管SCD是维护LVEF的高压患者死亡的主要原因,但ICD不建议在这个群体中进行初级预防.
研究的目的:
- 审查SCD发病率的下降以及SCD风险与当前ICD植入指南在HF患者之间日益增长的差异.
- 确定当前SCD风险预测的局限性,并讨论正在进行的临床试验对ICD建议的潜在影响.
- 探索患者相关变量,先进诊断测试,人工智能 (AI) 和机器学习 (ML) 的使用,以开发更准确的SCD风险预测模型.
主要方法:
- 关于ICD疗效和HF初级预防指南的里程碑性试验和当前文献的综述.
- 分析SCD发病率的趋势以及当代医疗管理对风险分层的影响.
- 讨论风险预测的新方法,包括应用到诊断测试数据的AI和ML算法.
主要成果:
- 由于改善的医疗疗法降低了SCD风险,ICDs在降低LVEF的HF中进行初级预防的有效性受到挑战.
- 在SCD的实际风险和当前关于HF患者使用ICD的指南建议之间存在很大的差距.
- 目前用于预测SCD风险的方法有限,需要开发更复杂的预测模型.
结论:
- 目前对HF患者使用ICD的建议需要重新评估,因为治疗环境不断变化和SCD风险概况的变化.
- 需要改进风险预测模型,能够准确地识别那些从ICD植入中获益最多的个体患者.
- 将AI和ML与全面的患者数据集成,有望创造动态,不断发展的风险预测工具,以优化HF患者的ICD治疗.
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