首页 | 本学科首页   官方微博 | 高级检索  
检索        

无症状性颅内动脉狭窄患者发生脑梗死预测评分模型的建立及其效果的初步评价
引用本文:沈达勇,伏文杰,张卫,王星智,时宏娟.无症状性颅内动脉狭窄患者发生脑梗死预测评分模型的建立及其效果的初步评价[J].卒中与神经疾病,2023,30(2):149-153.
作者姓名:沈达勇  伏文杰  张卫  王星智  时宏娟
作者单位:221000 江苏省徐州医科大学附属医院神经内科[沈达勇 伏文杰 张卫 王星智 时宏娟(通信作者)]
摘    要:目的 探讨无症状性颅内动脉狭窄(Asymptomatic intracranial arterial stenosis,AIAS)患者发生脑梗死的影响因素,构建预测评分模型并进行初步评价。方法 选取2019年1月-2020年12月于本院诊断为AIAS患者共340例,随访1年依据患者随访期间是否发生脑梗死分为脑梗死组(58例)和非脑梗死组(282例); 对2组患者的临床资料进行单因素分析,Logistic多元回归分析AIAS患者发生脑梗死的影响因素,受试者工作特征(Receiver operating characteristics,ROC)曲线对模型的预测效能进行评价。结果 脑梗死组患者饮酒史、吸烟史、高血压病史占比显著高于非脑梗死组(χ2=4.810,5.041,5.970,P<0.05),体重指数(Body mass index,BMI)、尿酸(Uric acid,UA)、三酰甘油(Triacylglycerol,TG)、同型半胱氨酸(Homocysteine,Hcy)水平显著高于非脑梗死组(t=2.304,4.116,8.410,2.006,P<0.05),高密度脂蛋白(High density lipoprotein cholesterol,HDL-C)水平显著低于非脑梗死组(t=2.116,P<0.05); Logistic多元回归分析显示饮酒史、吸烟史、TG水平≥1.98 mmol/L、HDL-C水平<1.18 mmol/L均是AIAS患者发生脑梗死的独立危险因素(P均<0.05); ROC曲线分析显示,模型ROC曲线下面积为0.837,95%置信区间为0.781~0.872,灵敏度、特异度分别为85.47%和87.84%。结论 AIAS往往得不到足够重视,进而引发脑梗死,因此临床应早期积极采取措施进行干预,必要时给予药物治疗,以降低脑梗死的发生风险。

关 键 词:脑梗死  无症状性颅内动脉狭窄  预测模型  初步评价

Establishment of prediction scoring model forcerebral infarction in patients with asymptomatic intracranial artery stenosis and its preliminary evaluation
Shen Dayong,Fu Wenjie,Zhang Wei,et al..Establishment of prediction scoring model forcerebral infarction in patients with asymptomatic intracranial artery stenosis and its preliminary evaluation[J].Stroke and Nervous Diseases,2023,30(2):149-153.
Authors:Shen Dayong  Fu Wenjie  Zhang Wei  
Institution:Department of Neurology, Affiliated Hospital of Xuzhou Medical University, Xuzhou Jiangsu 221000
Abstract:ObjectiveTo investigate the influencing factors of cerebral infarction in patients with asymptomatic intracranial artery stenosis(AIAS), and to construct a predictive scoring model and make a preliminary evaluation.Methods A total of 340 patients with AIAS diagnosed in our hospital from January 2019 to December 2020 were selected and followed up for 1 year. According to whether the patients had cerebral infarction during the follow-up period, they were divided into a cerebral infarction group(58 cases)and a non-cerebral infarction group(282 cases). Of the two groups of patients,univariate analysis was used to perform on the clinical data, Logistic multiple regression was used to analyze the influencing factors of cerebral infarction in AIAS patients.The receiver operating characteristics(ROC)curve was used to evaluate the predictive performance of the model.Results In the infarction group, the proportion of history of drinking,smoking and hypertension in patients was significantly higher than that in patients of the non-cerebral infarction group(χ2=4.810, 5.041, 5.970, P<0.05); The contents of body mass index(BMI), uric acid(UA), triacylglycerol(TG)and homocysteine(Hcy)in the infarction group were significantly higher than those in the non-cerebral infarction group(t=2.304, 4.116, 8.410, 2.006, P<0.05), and the level of high density lipoprotein cholesterol(HDL-C)in the infarction group was significantly lower than that in the non-cerebral infarction group(t=2.116, P<0.05); It showed that the history of drinking, smoking, TG content≥1.98 mmol/L, and HDL-C content <1.18 mmol/L were independent risk factors for cerebral infarction in patients with AIAS by Logistic multiple regression analysis(all P<0.05). The results indicated that the area under the ROC curve of the model was 0.837, the 95% confidence interval(CI)was 0.781~0.872, and the sensitivity and specificity were 85.47% and 87.84% respectively by the ROC curve analysis.Conclusion AIAS is often not paid enough attention to, which leads to cerebral infarction. Therefore, clinical early measures should be taken actively and drug treatment should be given necessarily to reduce the risk of cerebral infarction.
Keywords:Cerebral infarction Asymptomatic intracranial arterial stenosis(AIAS)Prediction model Preliminary evaluation
点击此处可从《卒中与神经疾病》浏览原始摘要信息
点击此处可从《卒中与神经疾病》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号