结合成像参数的新生物标记面板,用于预测糖尿病患者心血管并发症:一项回顾性队列研究
Jiaxing Guo1, Zhongchen Zhang2
1Internal Medicine Department, Shandong University Hospital, Jinan, No.91 Shanda North Road, 250100, Shandong Province, China.
结合生物标志物和成像的新型多式模式显著改善了糖尿病患者的心血管风险预测. 这种方法比现有的识别高风险个体的方法具有更好的临床实用性.
科学领域:
- 心脏病学 心脏病学
- 内分泌学 在内分泌学.
- 生物标志物和成像技术
背景情况:
- 糖尿病患者有患心血管疾病 (CVD) 的高风险.
- 目前的风险工具对于糖尿病人群来说是不理想的.
- 需要新的方法来改善DM中心血管疾病风险预测.
研究的目的:
- 开发和验证用于预测糖尿病患者心血管并发症的多式诊断模型.
- 整合新的生物标志物 (sST2,GDF-15) 与成像参数 (冠状动脉分数 [CACS],心血管斑块特征).
- 评估这个综合模型的临床实用性.
主要方法:
- 对600名患有2型糖尿病的成年人进行了回顾性队列研究.
- 收集的实验室生物标志物 (sST2,GDF-15,HbA1c),成像参数 (CACS,大脑斑) 和临床数据.
- 使用LASSO回归用于预测器选择和物流回归用于模型构建,经过ROC,NRI,IDI和DCA的验证.
主要成果:
- 最终的模型包括sST2,GDF-15,CACS,性动脉斑块,HbA1c和SGLT2i使用.
- 多式模式模型的AUC达到0.811,超过了仅使用生物标志物 (0.774) 和仅使用成像 (0.735) 的模型.
- 在重新分类 (NRI=0.52) 和歧视 (IDI=0.09) 中显著改善,具有优越的临床净益.
结论:
- 整合生物标志物和成像参数显著提高糖尿病患者心血管风险预测.
- 开发的多式联络模型为风险分层提供了更好的临床实用性.
- 建议进行进一步的多中心前性研究,以确认可概括性和成本效益.
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