摘要
目的分析急性一氧化碳中毒迟发性脑病的危险因素,并基于SMOTE算法构建风险预警模型。方法将180例急性一氧化碳中毒患者根据是否发生一氧化碳中毒后迟发性脑病分组,分析患者的临床资料,筛选一氧化碳中毒后迟发性脑病的影响因素,再使用SMOTE算法重建影响因素的原始数据集,从而获得其风险预警模型,并验证模型的预测效能。结果180例患者中有32例发生一氧化碳中毒后迟发性脑病,发生率为17.78%;年龄>60岁、头颅MRI异常、未行高压氧治疗、格拉斯哥昏迷指数评分<9分、昏迷时间>24 h以及肌酸激酶>200 U/L是一氧化碳中毒后迟发性脑病发生的危险因素(P<0.05),从而获得原始数据预警模型P_(1)=1.491X_(1)+1.429X_(2)+1.053X_(3)+1.055X_(4)+1.292X_(5)+1.330X_(6)-4.157和基于SMOTE算法的预警模型P_(2)=1.433X_(1)+1.229X_(2)+1.215X_(3)+1.063X_(4)+1.402X_(5)+1.106X_(6)-5.224。原始数据预警模型AUC曲线下面积为0.805,低于基于SMOTE算法的预警模型0.834。结论年龄>60岁、头颅MRI异常、未行高压氧治疗、GCS评分<9分、昏迷时间>24 h以及肌酸激酶>200 U/L是一氧化碳中毒后迟发性脑病发生的危险因素,基于上述危险因素建立的SMOTE模型预测效能比传统Logistic回归模型更优。
Objective To build a risk prediction model for delayed encephalopathy after acute carbon monoxide poisoning(ACMP)based on the SMOTE algorithm.Methods A total of 180 ACMP patients were grouped according to whether or not they developed delayed encephalopathy after ACMP.The clinical data of the patients were analyzed to screen the influencing factors of delayed encephalopathy after ACMP,and then the original dataset of the influencing factors was reconstructed using the SMOTE algorithm in order to obtain its risk warning model and to validate the predictive efficacy of the model.Results Thirty two of 180 patients had delayed encephalopathy after ACMP,with an incidence rate of 17.78%.Age>60 years,abnormal head MRI,no hyperbaric oxygen therapy,GCS score<9 points,coma time>24 h and CK>200 U/L were risk factors for delayed encephalopathy after ACMP(P<0.05).The original data early warning model(P_(1)=1.491X_(1)+1.429X_(2)+1.053X_(3)+1.055X_(4)+1.292X_(5)+1.330X_(6)-4.157)and the early warning model based on SMOTE algorithm(P_(2)=1.433X_(1)+1.229X_(2)+1.215X_(3)+1.063X_(4)+1.402X_(5)+1.106X_(6)-5.224)were built.The area under AUC curve of the original data prediction model was 0.805,which was lower than the risk prediction model based on SMOTE algorithm 0.834.Conclusion Age>60 years old,abnormal brain MRI,no hyperbaric oxygen therapy,GCS score<9 points,coma time>24 h,and CK>200 U/L are risk factors for delayed encephalopathy after ACMP.The risk prediction model based on SMOTE algorithm has high predictive efficiency.
作者
谭倩梅
杨静
李秋萍
TAN Qianmei;YANG Jing;LI Qiuping(Department of Neurology,Mianyang Hospital Affiliated to Medical School of University of Electronic Science and Technology,Mianyang Central Hospital,Mianyang 621000,China)
出处
《护理管理杂志》
CSCD
2023年第9期760-763,780,共5页
Journal of Nursing Administration
关键词
SMOTE算法
一氧化碳中毒
危险因素
迟发性脑病
预测
SMOTE algorithm
carbon monoxide poisoning
risk factors
delayed encephalopathy
prediction
