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心脏代谢指数与T2DM中功能恶化的关系:来自机器学习,生长混合模型的见解,以及基于网络的风险预测工具的开发
Quan Zhang1,2, Yuying Zhou1, Liyao Fu3
1Department of Cardiovascular Medicine, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China.
Diabetes, obesity & metabolism
|December 22, 2025
概括
升高的心脏代谢指数 (CMI) 预测2型糖尿病 (T2DM) 中功能恶化 (WRF). 将CMI纳入预测模型有助于早期识别高风险患者.
科学领域:
- 腎臟病學 (nephrology) 是一種醫學專業.
- 内分泌学 在内分泌学.
- 心脏病学 心脏病学
背景情况:
- 恶化功能 (WRF) 是2型糖尿病 (T2DM) 的重要并发症,由代谢失调驱动.
- 心脏代谢指数 (CMI) 是一种新的代谢状态标志物,但其在预测WRF中的作用尚未得到充分确立.
研究的目的:
- 调查CMI在T2DM患者预测WRF中的实用性.
- 开发和验证用于WRF预测的机器学习模型,包括CMI.
主要方法:
- 利用了来自10,094名T2DM参与者的数据 (Action to Control Cardiovascular Risk in Diabetes试验) 和来自中国队列的外部验证.
- 采用Boruta算法和随机森林来进行特征选择,六个机器学习算法用于模型构建,以及SHAP用于可解释性.
- 通过使用受限立方线评估CMI-WRF关联,并通过增长混合模型确定CMI轨迹.
主要成果:
- 一个机器学习模型包括CMI,eGFR,年龄,禁食血葡萄糖,尿动白蛋白和尿动肌素,证明了XGBoost的最佳性能.
- 较高的CMI与WRF风险有积极的关联;最高CMI的个人有16%的风险增加.
- 确定了三个CMI轨迹 ("低稳定"",中等稳定"",高增加"),其中"高增加"与显著增加的WRF风险有关.
结论:
- 升高的CMI是T2DM中WRF的一个显著的积极预测因素.
- 将CMI集成到预测模型中可以提高对WRF高风险T2DM患者的早期识别.
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