在稳定冠心病患者中开发和验证基于蛋白质的心血管风险评分
Peter Ganz1, Bettina Heidecker2, Kristian Hveem3
1Department of Medicine, University of California-San Francisco2Division of Cardiology, San Francisco General Hospital.
JAMA
|June 22, 2016
概括
与现有模型相比,新的9蛋白风险评分显示了冠心病患者心血管事件的预测效果有所改善. 需要进一步研究以评估其在较低风险人群中的准确性.
科学领域:
- 心血管医学
- 蛋白质组学
- 生物标志物发现
背景情况:
- 精确的心血管风险分层对于治疗冠心病患者至关重要.
- 现有的风险预测模型可能需要改进,以提高患者管理的准确性.
研究的目的:
- 开发和验证心血管疾病患者的新风险评分.
- 用大规模的循环蛋白质分析来预测风险.
主要方法:
- 一个前性队列研究,涉及衍生 (Heart and Soul) 和验证 (HUNT3) 队列.
- 使用修改后的aptamer测量了1130种血蛋白.
- 为预测4年内心肌梗塞,中风,心力衰竭和全因死亡的9蛋白风险评分的推导和验证.
主要成果:
- 与Framingham重新调整模型 (C统计0. 64- 0. 66) 相比,9蛋白风险得分显示出更高的预测性能 (C统计0. 74- 0. 75).
- 将9蛋白评分添加到Framingham模型中显著改善了导出和验证队列中的风险预测.
- 9蛋白模型显示,患有心血管事件的患者年化风险增加更大.
结论:
- 与Framingham二次事件风险得分相比,9蛋白风险得分在稳定的心血管疾病患者中提供了更好的心血管事件预测.
- 目前,9蛋白分辨率的准确性很小,需要进一步研究.
- 建议在较低风险患者群体中进行额外的研究以评估评分的有效性.
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