天津医药 ›› 2026, Vol. 54 ›› Issue (7): 710-715.doi: 10.11958/20253309

• 临床研究 • 上一篇    下一篇

TC/HDL-C、TyG、CysC、LAD对冠心病并发缺血性脑卒中的预测价值

叶奎1(), 褚文静2, 杜军义1   

  1. 1 陇南市第一人民医院心血管内科 (邮编746000)
    2 陇南市卫生学校基础教研室
  • 收稿日期:2025-11-11 修回日期:2025-12-14 出版日期:2026-07-15 发布日期:2026-07-13
  • 作者简介:叶奎(1982),男,副主任医师,主要从事心血管内科方面研究。E-mail:zolo8811@163.com
  • 基金资助:
    甘肃省科技计划项目(2023LQGR40)

A study on the prediction of TC/HDL-C, TyG, CysC and LAD for ischemic stroke in patients with coronary heart disease

YE Kui1(), CHU Wenjing2, DU Junyi1   

  1. 1 Department of Cardiovascular Medicine, Longnan First People's Hospital, Longnan 746000, China
    2 Basic Teaching and Research Section, Longnan Health School
  • Received:2025-11-11 Revised:2025-12-14 Published:2026-07-15 Online:2026-07-13

摘要:

目的 探讨血清总胆固醇/高密度脂蛋白胆固醇比值(TC/HDL-C)、甘油三酯葡萄糖指数(TyG)、胱抑素C(CysC)及左心房内径(LAD)对冠心病患者并发缺血性脑卒中的预测价值。方法 选取冠心病并发缺血性脑卒中患者100例作为合并症组,另择100例未发生脑卒中的冠心病患者作为冠心病组。回顾性收集2组基线资料及实验室指标,行超声心动图检查,测量左心室舒张末期内径(LVEDd)、LAD及左心室射血分数(LVEF)。采用二元Logistic回归分析冠心病并发缺血性脑卒中的影响因素,并基于影响因素构建列线图预测模型。通过受试者工作特征(ROC)曲线及决策曲线分析列线图预测模型的预测价值。结果 合并症组高血压占比、TC/HDL-C、TyG、CysC和LAD水平高于冠心病组(P<0.05)。Logistic回归分析结果显示,TC/HDL-C、TyG、CysC、LAD水平升高是冠心病患者并发缺血性脑卒中的独立危险因素。基于TC/HDL-C、TyG、CysC、LAD构建冠心病患者并发缺血性脑卒中的列线图预测模型,该模型具有良好区分度,C-index为0.880;ROC曲线分析结果显示,该模型预测冠心病患者并发缺血性脑卒中的曲线下面积为0.880(95%CI:0.834~0.927),最佳截断值为51.80分,特异度为0.760,敏感度为0.880,约登指数为0.640。决策曲线分析显示,当预测阈值为10%~30%时,该模型的净收益高于单一指标。结论 TC/HDL-C、TyG、CysC及LAD是冠心病患者并发缺血性脑卒中的影响因素,基于上述4个指标构建的列线图模型对预测冠心病患者并发缺血性脑卒中具有一定价值。

关键词: 冠心病, 缺血性卒中, 胆固醇,HDL, 甘油三酯类, 甘油三酯葡萄糖指数, 胱抑素C, 左心房内径

Abstract:

Objective To evaluate the predictive value of serum total cholesterol to high-density lipoprotein cholesterol ratio (TC/HDL-C), triglyceride-glucose index (TyG), cystatin C (CysC) and left atrial diameter (LAD) in patients with coronary heart disease (CHD) complicated with ischemic stroke. Methods One hundred patients with CHD complicated with ischemic stroke were enrolled as the comorbidity group, while another 100 CHD patients without a history of ischemic stroke were selected as the control group. Baseline characteristics and laboratory parameters were retrospectively collected in both groups. Echocardiography was performed to measure left ventricular end-diastolic diameter (LVEDd), LAD and left ventricular ejection fraction (LVEF). Binary Logistic regression analysis was performed to identify factors influencing ischemic stroke in CHD patients. Based on the identified factors, a nomogram prediction model was constructed. The predictive value of the nomogram model was then assessed using receiver operating characteristic (ROC) curve analysis and decision curve analysis. Results The proportion of hypertension, TC/HDL-C ratio, TyG, CysC and LAD were higher in the comorbidity group compared to those of the control group (P<0.05). Logistic regression analysis identified that elevated TC/HDL-C, TyG, CysC and LAD were independent risk factors for ischemic stroke in patients with CHD. A nomogram prediction model was subsequently constructed based on these four indicators. The model exhibited good discriminative ability, with a concordance index of 0.880. ROC curve analysis showed an area under the curve of 0.880 (95% CI: 0.834-0.927) for predicting ischemic stroke. The optimal cut-off value was 51.80 points, with a specificity of 0.760, sensitivity of 0.880 and the Youden's index of 0.640. Decision curve analysis revealed that the nomogram model provided a higher net benefit than any single indicator when the prediction probability threshold was set between 10% and 30%. Conclusion TC/HDL-C, the TyG, CysC and LAD are significant factors influencing ischemic stroke in patients with CHD. The nomogram model constructed based on these factors demonstrates potential utility for predicting this risk.

Key words: coronary disease, ischemic stroke, cholesterol, HDL, triglycerides, triglyceride-glucose index, cystatin C, left atrial diameter

中图分类号: