检验医学 ›› 2023, Vol. 38 ›› Issue (11): 1052-1056.DOI: 10.3969/j.issn.1673-8640.2023.11.009

• 论著 • 上一篇    下一篇

HDL-C对T2DM患者缺血性脑卒中发病风险的预测价值

吴颖1, 张立红2, 高吟2()   

  1. 1.南京医科大学附属南京医院 南京市第一医院核医学科,江苏 南京 210006
    2.南京中医药大学附属无锡市中医医院医学检验科,江苏 无锡 214000
  • 收稿日期:2022-05-14 修回日期:2023-03-23 出版日期:2023-11-30 发布日期:2024-01-10
  • 通讯作者: 高 吟,E-mail:gjyg024@126.com
  • 作者简介:吴 颖,女,1986年生,学士,检验师,主要从事临床检验工作。

Predictive value of high-density lipoprotein cholesterol on the risk of cerebral ischemic stroke in type 2 diabetes mellitus patients

WU Ying1, ZHANG Lihong2, GAO Yin2()   

  1. 1. Department of Nuclear Medicine,Nanjing First Hospital,Nanjing Medical University,Nanjing 210006,Jiangsu,China
    2. Department of Clinical Laboratory,Wuxi Hospital of Traditional Chinese Medicine,Nanjing University of Chinese Medicine,Wuxi 214000,Jiangsu,China
  • Received:2022-05-14 Revised:2023-03-23 Online:2023-11-30 Published:2024-01-10

摘要:

目的 探讨高密度脂蛋白胆固醇(HDL-C)在2型糖尿病(T2DM)患者缺血性脑卒中(CIS)发病风险中的预测价值。方法 选取2020年1月—2022年2月南京市第一医院T2DM患者298例,其中单纯T2DM患者150例(对照组),T2DM合并CIS患者148例(CIS组)。收集所有患者临床资料和实验室指标检测结果。采用多因素Logistic回归分析评估影响T2DM患者CIS发病的危险因素。采用受试者工作特征(ROC)曲线评价HDL-C判断T2DM患者发生CIS的效能。采用R软件构建预测T2DM患者发生CIS的列线图模型。结果 多因素Logistic回归分析结果显示,HDL-C、非高密度脂蛋白胆固醇(non-HDL-C)、三酰甘油(TG)/HDL-C比值、血清淀粉样蛋白A(SAA)/载脂蛋白A1(apo A1)比值、糖化血红蛋白(HbA1c)、高血压史、年龄是T2DM患者发生CIS的危险因素(P<0.05)。以HDL-C为预测变量绘制ROC曲线,结果显示,HDL-C判断T2DM患者发生CIS的曲线下面积(AUC)为0.62,最佳临界值为0.63,敏感性、特异性分别为34.5%、93.3%。将危险因素纳入列线图模型,C-index为0.859。ROC曲线分析结果显示,列线图模型判断T2DM发生CIS的AUC为0.859,校正曲线分析结果显示,预测结果与实际结果具有较好的一致性,且具有较好的拟合优度(P=0.180)。结论 构建的列线图模型可识别T2DM患者中的CIS高危人群,应重点关注低HDL-C水平的T2DM患者。

关键词: 高密度脂蛋白胆固醇, 2型糖尿病, 脑卒中

Abstract:

Objective To investigate the predictive value of high-density lipoprotein cholesterol(HDL-C) on the risk of cerebral ischemic stroke(CIS) in patients with type 2 diabetes mellitus(T2DM). Methods From January 2020 to February 2022,298 patients with T2DM were enrolled from Nanjing First Hospital,which included 150 patients with T2DM only(control group) and 148 patients with T2DM complicated with CIS(CIS group). The clinical data and clinical laboratory determination results were collected. Multivariate Logistic regression analysis was used to evaluate the risk factors of CIS in T2DM patients. Receiver operating characteristic(ROC) curve was used to evaluate the efficacy of HDL-C in determining CIS in T2DM patients. R software was used to establish a nomogram model for predicting CIS in T2DM patients. Results HDL-C,non-high-density lipoprotein cholesterol(non-HDL-C),triglyceride(TG)/HDL-C,serum amyloid A(SAA)/apolipoprotein A1(apo A1),glycated hemoglobin A1c(HbA1c),hypertension and age were independent risk factors for CIS in T2DM patients. ROC curve was drawn using HDL-C as the predictor. The area under curve(AUC) of HDL-C on the risk of CIS in T2DM patients was 0.62,the optimal cut-off value was 0.63,and the sensitivity and specificity were 34.5% and 93.3%,respectively. When risk factors were included in the nomogram model,the C-index was 0.859. ROC curve analysis results showed that the AUC of CIS judged by the nomogram model for T2DM was 0.859,and the calibration curve analysis results showed that the predicted results were in good agreement with the actual results,which had good goodness of fit(P=0.180). Conclusions The established nomogram model can identify the high-risk group of CIS in T2DM patients,and it is necessary to focus on the group of T2DM with low HDL-C level.

Key words: High-density lipoprotein cholesterol, Type 2 diabetes mellitus, Cerebral ischemic stroke

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