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1.四川大学华西医院科技部临床研究方案设计与统计办公室,成都 610041
2.四川大学华西医院临床流行病学与循证医学研究中心,成都 610041
刘慧珍,Email:liuhuizhen@scu.edu.cn,研究方向:流行病学与卫生统计学。
康德英,Email:deyingkang12@163.com。
收稿:2025-09-25,
修回:2025-11-28,
录用:2025-12-09,
纸质出版:2026-01-22
移动端阅览
刘慧珍, 周小芹, 王婷, 等. 累积C反应蛋白-甘油三酯葡萄糖指数与中国中老年人新发卒中风险的前瞻性研究[J/OL]. 重庆医科大学学报, 2026,1-7.
Liu Huizhen,Zhou Xiaoqin,Wang Ting,et al.Cumulative C-reactive protein-triglyceride-glucose index and the risk of new-onset stroke in middle-aged and elderly Chinese adults: a prospective study[J].Journal of Chongqing Medical University,
刘慧珍, 周小芹, 王婷, 等. 累积C反应蛋白-甘油三酯葡萄糖指数与中国中老年人新发卒中风险的前瞻性研究[J/OL]. 重庆医科大学学报, 2026,1-7. DOI:
Liu Huizhen,Zhou Xiaoqin,Wang Ting,et al.Cumulative C-reactive protein-triglyceride-glucose index and the risk of new-onset stroke in middle-aged and elderly Chinese adults: a prospective study[J].Journal of Chongqing Medical University, DOI:10.13406/j.cnki.cyxb..
目的
2
探讨C反应蛋白-甘油三酯-葡萄糖指数(C-reactive protein-triglyceride-glucose index,CTI)的累积水平及动态变化与新发卒中风险的关联。
方法
2
研究基于中国健康与养老追踪调查(China Health and Retirement Longitudinal Study,CHARLS)前瞻性队列数据,纳入了3 428名基线无卒中的45岁及以上参与者。暴露指标为2011-2012年至2015年间的累积CTI(Cumulative C-reactive protein-triglyceride-glucose index,CumCTI),采用曲线下面积法计算及基于K均值聚类分析的CTI动态变化轨迹。主要结局为新发卒中事件。采用多变量logistic回归模型分析CumCTI及CTI轨迹与新发卒中之间的关联。
结果
2
截止到2020年,共172例新发卒中事件。K均值聚类分析识别出2种CTI变化轨迹:稳定低值组(Cluster 1,
n
=2 008)和稳定高值组(Cluster 2,
n
=1 248)。经协变量矫正后,CTI动态变化与新发卒中的关联无统计学意义。然而,CumCTI分析显示,与最低三分位数组相比,中间三分位数组的卒中风险显著增加60%(
OR
=1.60,95%CI=1.05~2.46,
P
=0.031)。最高三分位数组亦显示出风险升高趋势,但未达到统计学显著性(
OR
=1.20,95%CI=0.74~1.96,
P
=0.459)。
结论
2
在中老年人群中,CTI的累积暴露可能是新发卒中的一个独立危险因素,提示维持较低的长期炎症和代谢综合水平对于卒中预防具有潜在重要意义。CTI的绝对水平而非其短期动态变化,在风险评估中可能更具价值。
Objective
2
To investigate the cumulative level and dynamic change of C-reactive protein-triglyceride-glucose index(CTI) and their association with the risk of new-onset stroke.
Methods
2
Based on the prospective cohort data from China Health and Retirement Longitudinal Study,a total of 3428 participants aged 45 years or above who had no history of stroke at baseline were enrolled. Exposure indicators included cumulative CTI(CumCTI,calculated based on the area under the curve) and the dynamic change trajectories of CTI identified by the K-means clustering analysis from 2011-2012 to 2015. The primary outcome was new-onset stroke events. The multivariable logistic regression model was used to analyze the association of CumCTI and CTI trajectories with new-onset stroke.
Results
2
A total of 172 new-onset stroke cases were recorded up to 2020. The K-means clustering analysis identified two CTI trajectories,i.e.,a stable low-level group(Cluster 1,
n
=2008) and a stable high-level group(Cluster 2,
n
=1248). After adjustment for covariates,the identified CTI trajectories were not significantly associated with new-onset stroke; however,the analysis of CumCTI showed that compared with the lowest tertile group,the middle tertile group had a significant increase in the risk of stroke by 60%(odds ratio[
OR
]=1.60,95%CI=1.05-2.46,
P
=0.031). There was also a trend of increase in the risk of stroke in the highest tertile group,but without statistical significance(
OR
=1.20,95%CI=0.74-1.96,
P
=0.459).
Conclusion
2
In middle-aged and elderly adults,cumulative exposure to CTI may be an independent risk factor for new-onset stroke,suggesting that maintaining relatively low long-term levels of inflammation and metabolic dysregulation may have an important significance for stroke prevention. The absolute level of CTI,rather than its short-term dynamic change,may have a higher value in risk assessment.
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