心脏代谢疾病分期和主要不良心血管事件预测在2个潜在的队列
Carrie R Howell1, Li Zhang2, Tapan Mehta3
1Division of Preventive Medicine, Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA.
JACC. Advances
|May 20, 2024
概括
修改的心脏代谢疾病分期 (CMDS) 系统有效地预测主要心血管不良事件 (MACE),性能与既定的风险计算器相比. 该工具有助于识别心血管疾病进展高风险的个体.
科学领域:
- 心脏病学 心脏病学
- 代谢性疾病研究研究
- 流行病学 流行病学
背景情况:
- 结合代谢综合征特征的心脏代谢风险预测模型对于早期识别高风险人群至关重要.
- 早期识别有助于及时干预心脏代谢性疾病的进展.
研究的目的:
- 评估修改心脏代谢疾病分期 (CMDS) 系统对重大心血管不良事件 (MACE) 的预测能力.
- 将CMDS系统的性能与现有的心血管风险预测模型进行比较.
主要方法:
- 使用来自REGARDS研究的临床数据开发了一个预测模型,包括葡萄糖,血压,BMI,胆固醇,甘油三和吸烟状况.
- 该模型预测了MACE,定义为心血管死亡,非致命的心肌梗塞或非致命中风.
- 使用接收机运行特征曲线和曲线下的面积 (AUC) 统计数据来评估性能.
主要成果:
- 在平均10年随访期间,CMDS模型在20234名参与者中预测MACE的AUC为0.721.
- 该CMDS模型的预测性能与ACC/AHA的10年风险估计 (AUC 0.721与0.716) 相似.
- CMDS模型的表现优于弗雷明汉风险评分 (AUC 0.673).
结论:
- 该CMDS系统对MACE表现出良好的预测能力,性能与既有风险工具相似或更好.
- 这些发现凸显了胰岛素耐药性作为一种重要的心血管疾病风险因素.
- 该CMDS系统可以有效地识别心血管疾病进展高风险的个体.
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