河北医学2024，Vol.30Issue(9)：1519-1525,7.DOI:10.3969/j.issn.1006-6233.2024.09.020
基于膈肌超声心脏参数血气指标构建重症肺炎脱机拔管失败的nomogram预测模型
Construction of a Nomogram Prediction Model for Failure of Extubation in Severe Pneumonia Based on Diaphragmatic Ultrasound Cardiac Parameters and Blood Gas Indices
摘要
Abstract
Objective:To explore the value of combined phrenic ultrasonography,cardiac parameters,and blood gas indexes in predicting the failure of offline extubation of severe pneumonia,and to construct a no-mogram prediction model for early clinical intervention.Methods:A total of 210 patients with severe pneumo-nia in the Affiliated Hospital of Guizhou Medical University from March 2021 to December 2023 were selected as the study subjects,and the study subjects were randomly divided into a training set(70%,147 cases)and a verification set(30%,63 cases).The general information of the patients was analyzed.The lasso-Logistic regression equation was used to screen the predictors of offline extubation failure for severe pneumonia,and a nomogram prediction model was constructed.The receiver operating characteristic curve(ROC),decision curve(DCA),and calibration curve were used to analyze the efficacy of the model.Results:In the training set and the validation set,the differences in age,mechanical ventilation time,APACHE Ⅱ score,ICU stay,CRP/ALB,cardiac parameters,diaphragm ultrasound parameters,PaO2,PaCO2,P/F,PA-aO-2,and his-tory of underlying cardiopulmonary disease were statistically significant when comparing the case group(failed extubation off the machine)with the control group(successful extubation off the machine)(P<0.05);Logis-tic regression equation showed that age,DTF,DE,E/A,PaO2,PaCO2,CRP/ALB,and basic history of cardiopulmonary disease were all influencing factors for the failure of offline extubation of severe pneumonia(P<0.05).The nomogram prediction model for offline extubation failure for severe pneumonia was obtained by visualization using R language software.The AUC of the nomogram prediction model was 0.866(95%CI:0.801-0.930)in the training set and 0.917(95%CI:0.853-0.982)in the verification set,respectively.The calibration curve was close to the 48° reference line,the prediction points were evenly distributed,and the DCA curve was within the range of 0.35～0.8.The nomogram prediction model could obtain the greatest benefits in both the training set and the verification set.Conclusion:This nomogram prediction model based on diaphragm ultrasound,heart parameters,and blood gas indexes can be used to predict the risk of offline extu-bation of severe pneumonia at an early stage.Accordingly,appropriate intervention plans can be made and the prognosis is improved.关键词
重症肺炎/脱机拔管/膈肌超声/心脏参数/血气指标/nomogram预测模型Key words
Severe pneumonia/Off-line tube extraction/Diaphragm ultrasound/Cardiac pa-rameters/Blood gas index/Nomogram prediction model引用本文复制引用
韦卫琴,胡晓纯,房东海,张运铎,代传扬,张燕,周永芳..基于膈肌超声心脏参数血气指标构建重症肺炎脱机拔管失败的nomogram预测模型[J].河北医学,2024,30(9):1519-1525,7.基金项目
2021年贵州省科教青年英才培训工程项目,[编号:黔省专合字(2021)260号] （2021）
