2024 年4 期 第32 卷
脑卒中预测模型![查看全文 查看全文](/Areas/201911120101/Content/img/icon_html.png)
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急性缺血性脑卒中患者脑动脉狭窄的影响因素 及其风险预测列线图模型构建
Influencing Factors of Cerebral Artery Stenosis in Patients with Acute Ischemic Stroke and Construction of Nomogram Model for Predicting Its Risk
作者:宋静,宋晶晶,陈文静
- 单位:
- 223003江苏省淮安市第二人民医院神经内科
- 单位(英文):
- Department of Neurology, the Second People's Hospital of Huai'an, Huai'an 223003, China
- 关键词:
- 卒中;脑动脉狭窄;影响因素分析;列线图
- 关键词(英文):
- Stroke; Cerebral artery stenosis; Root cause analysis; Nomograms
- 中图分类号:
- R 743.33
- DOI:
- 10.12114/j.issn.1008-5971.2024.00.085
- 基金项目:
- 江苏省卫生健康委2019年度医学科研立项项目(z2019060)
摘要:
目的 探讨急性缺血性脑卒中患者脑动脉狭窄(CAS)的影响因素,构建其风险预测列线图模型 并进行验证。方法 回顾性选取2019年1月—2023年7月淮安市第二人民医院神经内科收治的416例急性缺血性脑卒 中患者为研究对象,收集患者的临床资料,根据数字减影血管造影检查结果判定CAS情况。采用多因素Logistic回归 分析探讨急性缺血性脑卒中患者CAS的影响因素;采用R 3.6.3软件及rms程序包建立急性缺血性脑卒中患者CAS的风 险预测列线图模型;进行Hosmer-Lemeshow拟合优度检验,绘制校准曲线、ROC曲线。结果 416例急性缺血性脑 卒中患者中290例(69.71%)存在CAS。CAS与非CAS者年龄、高血压发生率、糖尿病发生率、冠心病发生率、高 脂血症发生率、有饮酒史者占比、有吸烟史者占比、同型半胱氨酸(Hcy)升高者占比、TC、收缩压比较,差异有 统计学意义(P<0.05)。多因素Logistic回归分析结果显示,高血压〔OR=2.294,95%CI(1.391~3.782)〕、糖尿 病〔OR=3.734,95%CI(1.865~7.476)〕、饮酒史〔OR=2.488,95%CI(1.512~4.093)〕、吸烟史〔OR=2.566, 95%CI(1.588~4.147)〕、Hcy升高〔OR=2.781,95%CI(1.534~5.040)〕是急性缺血性脑卒中患者CAS的独立影响 因素(P<0.05)。Hosmer-Lemeshow拟合优度检验及校准曲线分析结果显示,该列线图模型拟合较好(χ 2 =9.449, P =0.222)。ROC曲线分析结果显示,该列线图模型预测急性缺血性脑卒中患者CAS的AUC为0.753〔95%CI (0.707~0.800)〕。结论 高血压、糖尿病、饮酒史、吸烟史、Hcy升高是急性缺血性脑卒中患者CAS的独立影响因 素,基于上述因素构建的列线图模型对急性缺血性脑卒中患者CAS具有一定预测价值。
英文摘要:
Objective To explore the influencing factors of cerebral artery stenosis (CAS) in patients with acute ischemic stroke, and to construct and validate the nomogram model for predicting its risk. Methods A retrospective study was conducted on 416 patients with acute ischemic stroke admitted to Department of Neurology in the Second People's Hospital of Huai'an from January 2019 to July 2023. The clinical data of the patients were collected, and the occurrence of CAS was determined based on the results of digital subtraction angiography. Multivariate Logistic regression analysis was used to explore the influencing factors of CAS in patients with acute ischemic stroke. The nomogram model for predicting the risk of CAS in patients with acute ischemic stroke was constructed by using the R 3.6.3 software package and rms package. Hosmer-Lemeshow goodness of fit test was performed, calibration curve and ROC curve were drawn. Results Among 416 patients with acute ischemic stroke, 290 (69.71%) had CAS. There were significant differences in age, incidence of hypertension, incidence of diabetes, incidence of coronary heart disease, incidence of hyperlipidemia, proportion of patients with drinking history, proportion of patients with smoking history, proportion of patients with elevated homocysteine (Hcy) , TC, systolic blood pressure between the patients with and without CAS (P < 0.05) . Multivariate Logistic regression analysis showed that hypertension [OR=2.294, 95%CI (1.391- 3.782) ] , diabetes [OR=3.734, 95%CI (1.865-7.476) ] , drinking history [OR=2.488, 95%CI (1.512-4.093) ] , smoking history [OR=2.566, 95%CI (1.588-4.147) ] , elevated Hcy [OR=2.781, 95%CI (1.534-5.040) ] were the independent influencing factors of CAS in patients with acute ischemic stroke (P < 0.05) . The results of Hosmer-Lemeshow goodness of fit test and calibration curve analysis showed that the nomogram model fitted well (χ2 =9.449, P=0.222) . The results of ROC curve analysis showed that the AUC of the nomogram model for predicting CAS in patients with acute ischemic stroke was 0.753 [95 %CI (0.707-0.800) ] . Conclusion Hypertension, diabetes, drinking history, smoking history, elevated Hcy are the independent influencing factors of CAS in patients with acute ischemic stroke. The nomogram model constructed based on the above factors has certain value in predicting CAS in patients with acute ischemic stroke.
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