在中国人群中开发和验证一个简单的模型来预测功能显著的冠状动脉疾病:一项两中心的回顾性研究
Wen-Qian Shen1, Guo-Qing Du2, Xin Duan1
1Department of Ultrasound, The Second Affiliated Hospital of Harbin Medical University, Ultrasound Molecular Imaging Joint Laboratory of Heilongjiang Province, Harbin, China.
Heliyon
|October 13, 2023
概括
一个结合临床因素,hs-cTnI和LVEF的新模型准确地预测了中国人群的冠状动脉疾病 (CAD). 这种工具有助于临床医生对显著的CAD进行风险分层.
科学领域:
- 心脏病学 心脏病学
- 医学诊断 医学诊断 医学诊断
- 生物标志物 生物标志物
背景情况:
- 冠状动脉疾病 (CAD) 是一个重大的健康挑战.
- 准确预测功能显著的CAD对于有效的患者管理至关重要.
- 现有的风险模型可能无法完全捕捉像中国人这样的特定人群中的疾病患病率.
研究的目的:
- 开发和验证一个简单,有效的模型,用于预测功能上重要的CAD.
- 将传统的临床风险因素与易于获得的生物标志物和成像指标相结合.
- 为中国人口量身定制预测模型.
主要方法:
- 使用导出队列 (320名患者) 开发了五种预测模型.
- 模型歧视 (AUC),重新分类 (IDI,NRI),校准 (Hosmer-Lemeshow) 和临床益处 (DCA) 的评估.
- 通过引导和外部验证在单独的队列 (96名患者) 中进行内部验证.
主要成果:
- 合并年龄,性别,超脂血症,hs-cTnI和LVEF的最佳模型在导出队列中实现了0.807的AUC.
- 该模型显示了良好的适应性,校准性和临床净益处.
- 内部验证给出了0.798的C统计值,外部验证显示了可接受的性能 (AUC=0.704).
结论:
- 一个简单的模型将临床因素与hs-cTnI和LVEF结合起来,可以提高中国人群的CAD预测.
- 开发的模型为CAD的临床风险分层提供了有价值的工具.
- 创建了一个名ogram,以简化模型在实践中的应用.
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