ICU机械通气患者撤机风险预测模型的构建  

Construction of a risk prediction model for ventilator weaning in mechanically ventilated patients in ICU

作　　者：王建华 孙淑青[1] 张效东 杨筱筱 王友健 卢金宝 李赞武 WANG Jianhua;SUN Shuqing;ZHANG Xiaodong;YANG Xiaoxiao;WANG Youjian;LU Jinbao;LI Zanwu(Intensive Care Unit,Weifang People's Hospital,Weifang 261044,Shandong,China)

机构地区：[1]潍坊市人民医院重症医学科,山东潍坊261044

出　　处：《山东大学学报（医学版）》2023年第12期86-93,共8页Journal of Shandong University:Health Sciences

基　　金：潍坊市卫生健康委员会项目(WFWSJK-2023-295)。

摘　　要：目的探讨重症医学科(ICU)机械通气患者撤机失败的危险因素,建立风险预测模型,并进行内部验证检验预测效果。方法采用便利抽样方法,收集2020年1月至2022年1月潍坊市人民医院ICU机械通气患者546例,其中2020年1月至2021年1月就诊患者为建模组(n=358),2021年2月至2022年1月就诊患者为验模组(n=188),分析撤机失败的危险因素并建立预测模型,采用Hosmer-Lemeshow检验判断模型的拟合优度,接受者操作特性曲线(ROC)检测模型的预测效能,利用ROC曲线下面积(AUC)进行模型评价。结果ICU机械通气患者撤机风险预测模型纳入机械通气时间(OR=0.993)、膈肌移动度(OR=3.886)、膈肌厚度变异率(OR=65.917)、浅快呼吸指数(RSBI,OR=0.960)、下腔静脉变异度(OR=1.176)5个预测因子。模型公式:Z=-0.007×机械通气时间+1.357×膈肌移动度+4.188×膈肌厚度变异率-0.041×RSBI+0.162×下腔静脉变异度-3.183。ROC下面积为0.926,特异度为0.961,灵敏度为0.887。结论本研究构建的ICU机械通气患者撤机风险预测模型预测效果较好,为今后相关干预措施的制定与实施提供参考依据。Objective To investigate the risk factors of weaning failure in mechanically ventilated patients in the intensive care unit(ICU),develop a risk prediction model,and perform internal validation to assess the predictive performance.Methods A total of 546 cases of mechanically ventilated patients were collected during Jan.2020 and Jan.2022 with convenience sampling method from the ICU of Weifang People's Hospital,including 358 collected from Jan.2020 and Jan.2021 in the modeling group,and 188 collected from Feb.2021 to Jan.2022 in the model testing group.The risk factors of weaning failure were analyzed,based on which a prediction model was developed.The goodness of fit was assessed with Hosmer-Lemeshow test.The prediction performance was evaluated with receiver operating characteristic(ROC)curve,and the area under the ROC curve(AUC).Results The risk factors included mechanical ventilation time(OR=0.993),diaphragm mobility(OR=3.886),diaphragm thickness variability(OR=65.917),shallow fast respiratory index(RSBI,OR=0.960),and inferior vena cava variability(OR=1.176).The model equation was as follows:Z=-0.007×mechanical ventilation time+1.357×diaphragm mobility+4.188×diaphragm thickness variability-0.041×shallow fast respiratory index+0.162×inferior vena cava variability-3.183.The AUC was 0.926,with a specificity of 0.961 and a sensitivity of 0.887.Conclusion The risk prediction model demonstrates good performance,which can provide reference for the development and implementation of future interventions.

关 键 词：重症医学科 机械通气 撤机 预测模型 

分 类 号：R605.97[医药卫生—急诊医学]