风险分层算法用于通过皮肤进行冠状动脉干预的贫血患者的临床结果
Bingbing Ke1, Renchun Gong2, Aidong Shen1
1Department of Cardiology, Cardiovascular Center, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Annals of medicine
|August 24, 2023
概括
穿皮冠状动脉干预 (PCI) 期间和之后的血红蛋白水平预测主要的心血管和大脑不良事件 (MACCE). 监测血红蛋白可以帮助贫血PCI患者分层风险.
科学领域:
- 心脏病学 心脏病学
- 血液学 血液学 血液学
- 医疗信息学 医疗信息学
背景情况:
- 穿皮冠状动脉干预 (PCI) 是冠状动脉疾病的常见程序.
- 贫血是接受PCI的患者中普遍存在的并发症.
- 血红蛋白水平与PCI后心血管不良结果之间的关系需要进一步调查.
研究的目的:
- 检查PCI患者的基线和访问血红蛋白水平与主要心血管和脑部不良事件 (MACCE) 之间的关联.
- 开发和验证风险分层模型,以预测该人群中的MACCE.
主要方法:
- 对8,298名PCI患者 (2013-2020年) 的回顾性队列研究.
- 多变量Cox比例危险模型和机器学习算法 (渐变增强) 用于分析.
- 模型性能使用布里尔分数和接收器操作特征曲线进行评估.
主要成果:
- 总共有1,636名患者 (19.71%) 在中位数为4年的随访期间经历了MACCE.
- 访问血红蛋白和血红蛋白变化与MACCE风险显著相关 (HR < 1).
- 低估计的淋巴细胞过率和高的HbA1c是关键预测因素;风险树模型确定了高风险患者.
结论:
- 在PCI期间和之后的血红蛋白水平比基线水平更能预测MACCE.
- 优化血红蛋白水平可能会改善贫血PCI患者的长期预后.
- 一种新的风险分层模型可以增强接受PCI的高风险贫血患者的查.
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