中国全科医学 ›› 2024, Vol. 27 ›› Issue (26): 3227-3231.DOI: 10.12114/j.issn.1007-9572.2024.0012

所属专题: 脑健康最新研究合辑

• 论著 • 上一篇    下一篇

残余胆固醇水平与缺血性脑卒中复发风险的关联性及其预测价值研究

刘星雨1, 杜慧杰1, 莫佳丽1, 徐明欢1, 刘祖婷1, 杨学智1, 张慧琴1, 易应萍2, 况杰1,*()   

  1. 1.330006 江西省南昌市,南昌大学公共卫生学院流行病学教研室 江西省预防医学重点实验室
    2.330006 江西省南昌市,南昌大学第二附属医院医疗大数据研究中心
  • 收稿日期:2024-02-10 修回日期:2024-04-20 出版日期:2024-09-15 发布日期:2024-06-14
  • 通讯作者: 况杰

  • 作者贡献:
    况杰提出研究选题方向,负责研究设计,论文审校;刘星雨负责统计分析及论文撰写;杜慧杰、莫佳丽、徐明欢、刘祖婷负责数据处理、统计方法协助;杨学智、张慧琴负责数据收集、数据整理;易应萍负责研究可行性分析,文章质量控制;所有作者确认了论文的最终稿。
  • 基金资助:
    国家自然科学基金资助项目(82160645,82360667); 江西省自然科学基金(20212BAB206091); 南昌大学2023年科研训练项目(2023)

Correlation between Remnant Cholesterol and the Risk of Ischemic Stroke Recurrence and Its Predictive Value

LIU Xingyu1, DU Huijie1, MO Jiali1, XU Minghuan1, LIU Zuting1, YANG Xuezhi1, ZHANG Huiqin1, YI Yingping2, KUANG Jie1,*()   

  1. 1.Department of Epidemiology, School of Public Health, Nanchang University/Jiangxi Provincial Key Laboratory of Preventive Medicine, Nanchang 330006, China
    2.Medical Big Data Center, the Second Affiliated Hospital of Nanchang University, Nanchang 330006, China
  • Received:2024-02-10 Revised:2024-04-20 Published:2024-09-15 Online:2024-06-14
  • Contact: KUANG Jie

摘要: 背景 血清残余胆固醇(RC)与缺血性脑卒中发病相关,然而RC水平与缺血性脑卒中复发的相关性研究较少,且尚少有研究探讨RC在缺血性脑卒中患者脑卒中复发中的预测价值。目的 通过检测缺血性脑卒中患者血清RC水平,探讨RC水平与脑卒中复发的相关性及其预测价值。方法 纳入2019年3月—2021年3月在南昌大学第一附属医院、南昌大学第二附属医院、南昌市第二医院和南昌市第三医院住院且确诊为缺血性脑卒中的住院患者为研究对象,收集入院后48 h内的相关临床信息,并对其随访12个月,明确脑卒中复发情况。采用Cox比例风险回归模型及限制性立方样条(RCS)分析RC水平与缺血性脑卒中复发的相关性。通过受试者工作特征(ROC)曲线分析RC水平对缺血性脑卒中复发的预测价值。结果 研究共纳入1 023例患者,其中107例(10.46%)缺血性脑卒中患者1年内复发。多因素Cox比例风险回归模型分析结果显示,高RC水平是缺血性脑卒中复发的独立危险因素(HR=2.709,95%CI=1.150~6.382,P<0.05)。RC水平与缺血性脑卒中患者复发风险存在非线性的正性剂量-反应关系(P-Nonlinear=0.019 3)。RC预测缺血性脑卒中患者1年内复发的ROC曲线下面积为0.687(95%CI=0.631~0.743),最佳截断值为0.58 mmol/L。RC联合Essen卒中风险评分量表(ESRS)与单独ESRS预测缺血性脑卒中患者1年内复发的ROC曲线下面积比较,差异有统计学意义(Z=2.356 2,P<0.05)。结论 高RC水平是缺血性脑卒中患者复发的独立危险因素,并对于缺血性脑卒中复发具有一定的预测价值。

关键词: 缺血性脑卒中, 残余胆固醇, 复发, Cox比例风险回归模型, 预后

Abstract:

Background

Serum remnant cholesterol (RC) is associated with the onset of ischemic stroke (IS). However, studies on the correlation between RC levels and recurrent IS are limited, and the predictive value of RC in recurrent IS has not been analyzed.

Objective

To investigate the correlation between serum RC and the recurrence of IS, and to evaluate the predictive value of RC levels in recurrent IS by detecting serum RC levels in patients with IS.

Methods

Patients diagnosed as IS and hospitalized in the First Affiliated Hospital of Nanchang University, the Second Affiliated Hospital of Nanchang University, the Second Hospital of Nanchang, and the Third Hospital of Nanchang from March 2019 to March 2021 were included in the study. Relevant clinical information within 48 hours of admission was collected. All patients were followed up for 12 months to record the cases of recurrent IS. Cox regression and Restricted Cubic Spline (RCS) were performed to identify the correlation between RC levels and recurrent IS. Receiver operating characteristic (ROC) curves were plotted to evaluate the predictive value of RC levels in recurrent IS.

Results

A total of 1 023 eligible patients were included in the study, and 107 (10.46%) of them experienced IS recurrence within 1 year. Multivariable Cox regression analysis showed that high RC was an independent risk factor for recurrent IS (HR=2.709, 95%CI=1.150-6.382; P<0.05). There was a nonlinear positive dose-response relationship between RC levels and the risk of recurrent IS (P-Nonlinear=0.019 3). The area under the curve (AUC) of RC in discriminating 1-year recurrence of IS was 0.687 (95%CI=0.631-0.743), with the optimal cutoff of 0.58 mmol/L. There was a significant difference in the AUC between the combination detection of RC and the Essen Stroke Risk Score (ESRS) versus ESRS alone in discriminating 1-year recurrence of IS (Z=2.356 2, P<0.05) .

Conclusion

High RC is an independent risk factor for recurrent IS, showing a predictive value in the recurrence of IS.

Key words: Ischemic stroke, Remnant cholesterol, Recurrence, Cox proportional hazards regression model, Prognosis

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