在冠状动脉疾病患者中预测多血管疾病
Suko Adiarto1, Luthfian Aby Nurachman2, Raditya Dewangga3
1Department of Cardiology and Vascular Medicine, Faculty of Medicine, Universitas Indonesia, National Cardiovascular Center Harapan Kita, Jakarta, Indonesia.
F1000Research
|September 25, 2023
概括
一个新的预测模型识别了高风险的冠状动脉疾病患者,用于多血管疾病查. 这种有针对性的方法大大减少了选所需的数量,提高了效率和特异性.
科学领域:
- 心血管医学 心血管医学
- 医学诊断 医学诊断 医学诊断
- 公共卫生查 公共卫生查
背景情况:
- 冠状动脉疾病 (CAD) 表明系统性动脉样硬化,构成其他血管疾病的风险.
- 目前对CAD患者多血管疾病的查是无效的.
- 在CAD患者中多血管疾病的危险因素仍未得到充分研究.
研究的目的:
- 开发一种预测模型和评分系统,用于针对性地对CAD患者进行多血管疾病查.
- 为了确定与多血管疾病相关的关键风险因素在这个人群中.
主要方法:
- 通过冠状动脉血管学或PCI诊断的CAD患者的横截面研究.
- 使用多普勒超声波和ABI评分诊断冠状动脉狭窄 (CAS),腹腔大动脉动脉瘤 (AAA) 和外周动脉疾病 (PAD).
- 用于模型构建和风险得分计算的多变量逻辑回归,通过ROC分析和Hosmer-Lemeshow测试进行验证.
主要成果:
- 年龄超过60岁,糖尿病,脑血管疾病和带有三血管疾病的CAD (CAD3VD) 是多血管疾病的显著预测因素.
- 预测模型显示了良好的能力 (AUC = 0.659) 和校准 (霍斯默-莱梅斯显示p = 0.379).
- 有针对性的查将查所需的数量 (NNS) 从6个减少到3个,具有96.5%的特异性.
结论:
- 基于临床风险评分的有针对性的查策略对于CAD患者的多血管疾病是有效的.
- 这种方法通过减少NNS来提高选效率.
- 该模型提供了良好的预测能力和高特异性,用于识别有风险的个体.
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