不同卧位机械通气病毒性肺炎预后状况及影响因素和预测模型构建  

Analysis of Prognostic Status and Influencing Factors of Viral Pneumonia during Mechanical Ventilation in Different Decubitus Positions and Construction of Prediction Model

作　　者：柳娟娟 姚娜 张婷婷 LIU Juanjuan;YAO Na;ZHANG Tingting(The First Department of Respiratory and Critical Care Medicine,the First Hospital of Zhangjiakou City,Zhangjiakou,Hebei 075000,China)

机构地区：[1]张家口市第一医院呼吸与危重症医学一科,河北张家口075000

出　　处：《临床误诊误治》2024年第7期25-31,共7页Clinical Misdiagnosis & Mistherapy

基　　金：张家口市重点研发计划项目(2322043D)。

摘　　要：目的探究不同卧位机械通气病毒性肺炎患者预后及影响因素,并构建预测模型,为改善病毒性肺炎患者预后提供参考。方法选取2020年1月—2023年5月收治的363例行机械通气病毒性肺炎患者,统计不同卧位机械通气病毒性肺炎患者预后状况,据28 d预后情况分为预后不良和预后良好组,分析预后不良的影响因素,构建预后不良的Nomogram预测模型,并采用受试者工作特征(ROC)曲线、决策曲线分析(DCA)、临床影响曲线(CIC)行外部验证。结果行俯卧位机械通气病毒性肺炎患者28 d预后不良率为17.19%(33/192),预后良好率为82.81%(159/192);行仰卧位机械通气病毒性肺炎患者28 d预后不良率为28.65%(49/171),预后良好率为71.35%(122/171)。多因素Logistic回归分析结果显示,病原学情况、机械通气体位、机械通气时间、氧合指数、动态肺顺应性、并发急性呼吸窘迫综合征、淋巴细胞计数、淀粉样蛋白A均是机械通气病毒性肺炎患者预后不良的独立影响因素(P<0.01)。基于多因素Logistic回归分析所得的独立影响因素绘制机械通气病毒性肺炎患者预后不良的Nomogram预测模型,ROC曲线分析显示,该模型曲线下面积为0.903(95%CI:0.868,0.938),DCA曲线显示该模型具有较好的临床净获益,CIC曲线显示该预测模型可在阈值概率范围内有效区分机械通气病毒性肺炎预后不良高危患者。结论病毒性肺炎患者行俯卧位机械通气预后要好于仰卧位机械通气,机械通气病毒性肺炎患者预后不良受病原学情况、机械通气体位、机械通气时间、氧合指数、动态肺顺应性、并发急性呼吸窘迫综合征、淋巴细胞计数、淀粉样蛋白A影响,基于上述因素构建预测模型具有较高预测效能,临床效用良好。Objective To explore the prognosis and influencing factors of patients with viral pneumonia under mechanical ventilation in different supine positions,and to construct a prediction model,to provide reference for improving the prognosis of patients with viral pneumonia.Methods A total of 363 patients with viral pneumonia under mechanical ventilation from January 2020 to May 2023 were selected to analyze the prognostic status of the patients with viral pneumonia under mechanical ventilation in different supine positions.According to 28-day prognosis,they were divided into poor prognosis group and good prognosis group.and the influencing factors of poor prognosis were analyzed.A nomogram prediction model for poor prognosis was constructed,followed by external validation using receiver operating characteristic(ROC)curve,decision curve analysis(DCA),and clinical impact curve(CIC).Results The poor 28-day prognosis rate of patients with viral pneumonia under mechanical ventilation in prone position was 17.19%(33/192),and the good prognosis rate was 82.81%(159/192).The 28-day prognosis rate of patients with virus pneumonia under mechanical ventilation in supine position was 28.65%(49/171),and the good prognosis rate was 71.35%(122/171).Multivariate Logistic regression analysis showed that etiology,body position under mechanical ventilation,mechanical ventilation duration,oxygenation index,Cdyn,complicated acute respiratory distress syndrome,LYM and SAA were independent influencing factors for poor prognosis of patients with viral pneumonia under mechanical ventilation(P<0.01).Based on the independent influencing factors obtained by multivariate Logistic regression analysis,a nomogram model for predicting poor prognosis of patients with viral pneumonia under mechanical ventilation was established.ROC curve analysis showed that the area under the ROC curve(AUC)of the model was 0.903(95%CI:0.868,0.938),DCA curve showed that the model had a good clinical net benefit,and CIC curve showed that the prediction model could effect

关 键 词：病毒性肺炎 机械通气 仰卧位 俯卧位 Nomogram预测模型 氧合指数 动态肺顺应性 预测效能 

分 类 号：R563.1[医药卫生—呼吸系统]