开发和验证一个名图,以预测心血管疾病的未来风险
Xuechun Shen1, Wei He2, Jinyu Sun3
1Department of Cardiology, The Second Affiliated Hospital of Nanjing Medical University, 210011 Nanjing, Jiangsu, China.
Reviews in cardiovascular medicine
|July 30, 2024
概括
这项研究开发了一种名谱来预测心血管疾病 (CVD) 风险,使用心脏肌酸结合蛋白-C (cMyBP-C),年龄,血压,吸烟和家族史. 该模型显示了早期CVD识别的高预测准确度.
科学领域:
- 心脏病学 心脏病学
- 预防医学 预防医学
- 生物标志物研究 生物标志物研究
背景情况:
- 早期识别心血管疾病 (CVD) 风险较高的个体对于及时干预至关重要.
- 心血管疾病仍然是全球死亡的主要原因,需要改进风险预测策略.
研究的目的:
- 在一般人群中构建和验证一个名谱来预测未来心血管疾病 (CVD) 事件的风险.
- 确定CVD事件的关键预测因子,以提高风险分层.
主要方法:
- 对537名患者进行了回顾性分析,数据分为培训和验证队列 (7:3比率).
- 使用最少绝对收缩和选择操作员 (LASSO) 方法和多变量后勤回归来确定重要的心血管疾病风险因素.
- 心血管疾病事件被定义为突然心脏死亡,心肌梗塞,急性心力衰竭恶化或中风.
主要成果:
- 这项研究确定了心脏肌结合蛋白-C (cMyBP-C),年龄,透气血压,吸烟频率和心血管疾病家族史作为未来心血管疾病事件的重要预测因素.
- 开发的名图表显示出高的预测能力,在培训队列中,曲线下的面积 (AUC) 为0.816,在验证队列中为0.774.
- 较高的cMyBP-C水平与较高的心血管疾病事件发生率显著相关 (p=0.001).
结论:
- 纳米图包括cMyBP-C,年龄,透气血压,吸烟和家族史,为预测心血管疾病风险提供了有价值的工具.
- 诺米图表表现出强大的预测性能,有助于早期识别高风险个体.
- 该工具可以支持临床决策和实施针对心血管疾病的个性化预防策略.
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