摘要
目的:分析104例急性脑梗死(ACI)患者继发血管性认知障碍影响因素并构建回归模型。方法:回顾性收集2020年1月—2022年4月我院收治的104例ACI患者临床资料,根据患者是否继发血管性认知障碍将其分为认知障碍组(n=45)和非认知障碍组(n=59),统计ACI继发血管性认知障碍的单因素,采用多因素Logistic回归分析ACI继发血管性认知障碍的影响因素,并据其构建ACI继发血管性认知障碍的预测模型,采用MedCalc11.4绘制受试者工作特征曲线(ROC)分析预测模型对ACI继发血管性认知障碍的预测价值,获取曲线下面积(AUC)。结果:多因素Logistic回归分析结果显示,年龄较大、合并颈动脉粥样硬化、合并高血压、合并糖尿病、脑白质疏松、梗死部位为额叶/颞叶/丘脑、卒中后抑郁、血清Hcy水平较高均为ACI患者继发血管性认知障碍的独立危险因素(OR=3.827、2.713、3.501、3.271、3.010、2.192、4.764、2.672,P<0.05),受教育年限较长为ACI患者继发血管性认知障碍的保护因素(OR=0.349,P<0.05)。根据多因素Logistic回归分析结果建立预测模型为logit(P)=11.026+年龄×1.342+合并颈动脉粥样硬化×0.998+合并高血压×1.253+合并糖尿病×1.185+脑白质疏松×0.975+梗死部位为额叶/颞叶/丘脑×0.785+卒中后抑郁×1.561-受教育年限×1.053+血清Hcy水平×0.983,ROC曲线显示,当logit(P)>12.11时,回归模型预测ACI患者继发血管性认知障碍发生的AUC值为0.913,敏感度为91.11%,特异度为77.97%。结论:ACI患者继发血管性认知障碍的独立危险因素包括年龄较大、合并颈动脉粥样硬化、合并高血压、合并糖尿病、脑白质疏松、梗死部位为额叶/颞叶/丘脑、卒中后抑郁、血清Hcy水平较高,保护因素为受教育年限较长,同时相关回归模型对ACI患者继发血管性认知障碍的预测价值较好,临床可据此对ACI患者继发血管性认知障碍进行预测,降低ACI患者继发血管性认知障碍的风险。
Objective:To analyze the influencing factors of secondary vascular cognitive impairment in 104 patients with acute cerebral infarction(ACI)and to construct a regression model.Methods:The clinical data of 104 patients with ACI admitted to our hospital from January 2020 to April 2022 were retrospectively collected.According to whether the patients had secondary vascular cognitive impairment,they were divided into cognitive impairment group(n=45)and non-cognitive impairment group(n=59).The single factors of vascular cognitive impairment secondary to ACI were analyzed.Multivariate Logistic regression was used to analyze the influencing factors of vascular cognitive impairment secondary to ACI,and the prediction model of vascular cognitive impairment secondary to ACI was constructed according to it.The receiver operating characteristic curve(ROC)of MedCalc11.4 was used to analyze the predictive value of the prediction model for vascular cognitive impairment secondary to ACI,obtain the area under the curve(AUC).Results:Multivariate Logistic regression analysis showed that older age,carotid atherosclerosis,hypertension,diabetes mellitus,leukoaraiosis,frontal/temporal/thalamus Location of infarction,post-stroke depression,and high the level of serum Hcy are independent risk factors for secondary vascular cognitive impairment in patients with ACI(OR=3.827,2.713,3.501,3.271,3.010,2.192,4.764,2.672,P<0.05),longer years of education was the protective factor of vascular cognitive impairment secondary to ACI(OR=0.349,P<0.05).According to the results of multivariate Logistic regression analysis,the prediction model was established as logit(P)=11.026+age×1.342+carotid atherosclerosis×0.998+hypertension×1.253+diabetes×1.185+leukuarosis×0.975+frontal lobe/temporal lobe/thalamus×0.785+post-stroke depression×1.561-years of education×1.053+the level of serum Hcy×0.983,ROC curve showed that when logit(P)>12.11,the AUC value of the regression model to predict the occurrence of secondary vascular cognitive impairment in ACI patients was 0.913,and the sensitivity was 91.11%,the specificity was 77.97%.Conclusion:Patients with ACI were independent risk factors for the development of secondary vascular cognitive impairment including older age,carotid atherosclerosis,hypertension,diabetes mellitus,leukoaraiosis,frontal/temporal/thalamus location of infarction,post-stroke depression,and high the level of serum Hcy,longer years of education was the protective factor of vascular cognitive impairment secondary to ACI.At the same time,the correlation regression model had a good predictive value for the secondary vascular cognitive impairment in patients with ACI,which could be used to predict the secondary vascular cognitive impairment in patients with ACI and reduce the risk of secondary vascular cognitive impairment in patients with ACI.
作者
王文婷
WANG Wenting(The First People’s Hospital of Tianshui City,Gansu Province 741000)
出处
《医学理论与实践》
2023年第3期372-376,共5页
The Journal of Medical Theory and Practice
关键词
急性脑梗死
血管性认知障碍
影响因素
回归模型
受试者工作特征曲线
Acute cerebral infarction
Vascular cognitive impairment
Influencing factors
Regression model
Receiver operating characteristic curve
