急性脑梗死后继发血管性认知损害风险预警模型构建与验证  

Construction of early warning model for secondary vascular cognitive impairment after acute cerebral infarction and its validation

作　　者：倪芳琴 唐志仙 王佳敏 NI Fangqin;TANG Zhixian;WANG Jiamin(Department of Geriatrics,the Seventh People's Hospital of Shaoxing,Shaoxing 312000,Zhejiang,China)

机构地区：[1]绍兴市第七人民医院老年二科,浙江绍兴312000

出　　处：《护士进修杂志》2023年第21期1938-1942,共5页Journal of Nurses Training

摘　　要：目的分析患者急性脑梗死(ACI)后继发血管性认知功能障碍(VCI)的危险因素,构建风险预警模型并进行验证。方法回顾性分析2018年1月-2020年12月我院收治的符合研究标准的146例ACI患者为建模组,收集其临床资料,包括年龄、性别、BMI、受教育程度、吸烟史、饮酒史、既往基础病史、美国国立卫生研究院卒中量表(NIHSS)评分、Fazakas评分、既往脑梗病史、梗死部位、梗死面积、血同型半胱氨酸(hyc)水平。治疗3个月后复诊,根据临床诊断分为VCI组和无VCI组。采用单因素分析与二元logistic回归分析影响患者继发VCI的因素,并建立继发VCI预警模型;另选取2021年1月-2022年6月62例符合标准的患者为验证组,收集其临床资料,采用受试者工作特性曲线(ROC)对模型进行外部验证。结果146例ACI中,共有72例患者后续继发VCI,继发率为49.32%;单因素和多因素分析显示,年龄(OR=1.089,95%CI=1.001~1.184)、高血压(OR=3.962,95%CI=1.208~13.000)、既往梗死病史(OR=4.1668,95%CI=1.212~14.336)、中面积梗死(OR=9.254,95%CI=2.377~36.027)、大面积梗死(OR=12.342,95%CI=1.455~104.704)、NIHSS评分(OR=1.739,95%CI=1.245~2.429)、Fazakas评分(OR=2.873,95%CI=1.705~4.842)、hyc水平(OR=1.183,95%CI=1.055~1.327)均是影响ACI患者继发VCI的独立影响因素(P<0.05)。根据独立影响因素构建的logistic回归模型,模型ROC曲线下面积(AUC)为0.901(95%CI=0.849~0.954),灵敏度为83.8%,特异度为91.7%;模型验证灵敏度76.66%(23/30),特异度93.75%(30/32),阳性预测值92%(23/25),阴性预测值81.1%(30/37),总准确率85.5%(53/62)。结论急性脑梗死患者的年龄、高血压史、多发脑梗病史、梗死面积、hyc水平、NIHSS评分、Fazakas评分是影响继发VCI的独立影响因素。本研究构建的风险预警模型有较好的预测效能,有一定的临床应用价值。Objective To analyze the risk factors of secondary vascular cognitive impairment(VCI)after acute cerebral infarction(ACI),and to construct and validate a risk warning model.Methods The clinical data of 146 patients with ACI who met the research criteria in our hospital from January 2018 to December 2020 were retrospectively analyzed,including age,gender,body mass index(BMI),education level,smoking history,drinking history,previous basic medical history,National Institutes of Health Stroke Scale(NIHSS)score,Fazakas score,previous history of cerebral infarction,infarct location,infarct area,and blood homocysteine(hyc)level.After 3 months of treatment,patients were divided into VCI group and non-VCI group according to clinical diagnosis.Univariate analysis and binary logistic regression were used to analyze the factors affecting secondary VCI in patients and to establish an early warning model of secondary VCI;The clinical data of 62 eligible patients from January 2021 to June 2022 were selected for external validation of the model using the receiver operating characteristic curve(ROC).Results Among 146 patients with ACI,72 patients had subsequent secondary VCI,with a secondary rate of 49.32%.Univariate and multivariate analysis showed.age(OR=1.089,95%CI was 1.001-1.184),hypertension(OR=3.962,95%CI was 1.208-13.000),previous history of infarction(OR=4.1668,95%CI was 1.212-14.336),moderate area infarction(OR=9.254,95%CI was 2.377-36.027),large area infarction(OR=12.342,95%CI was 1.455-104.704),NIHSS Scale(OR=1.739,95%CI was1.245-2.429),Fazakas score(OR=2.873,95%CI was 1.705-4.842),hyc level(OR=1.183,95%CI was 1.055-1.327)were independent factors affecting secondary VCI in patients with ACI(P<0.05).The area under the ROC curve(AUC)of the logistic regression model was 0.901(95%CI was 0.849-0.954),the sensitivity was 83.8%,and the specificity was 91.7%;The sensitivity,specificity,the positive predictive value,the negative predictive value and the total accuracy of model validation were 76.66%(23/30),93.75%(30/32),92%(23

关 键 词：脑梗死 认知功能障碍 血管性认知损害 危险因素 风险预测 模型构建 护理 

分 类 号：R473.74[医药卫生—护理学]