摘要
目的探讨儿童重症监护病房(pediatric intensive care unit,PICU)患儿发生呼吸机相关性肺炎(ventilator-associated pneumonia,VAP)的影响因素,并构建预测模型。方法回顾性分析2015年1月~2019年6月本院PICU收治的600例行机械通气治疗的患儿,统计VAP发生率。采用Logistic回归法对影响VAP的危险因素进行分析,并根据分析结果构建预测模型,随后用ROC曲线法分析该模型预测VAP的价值。结果600例PICU患儿中54例发生VAP,占比9.00%。机械通气时间(OR=6.375,95%CI:3.298~12.32)、支气管镜检查(OR=1.979,95%CI:1.025~3.823)、再插管(OR=2.553,95%CI:1.329~4.906)、使用糖皮质激素(OR=4.758,95%CI:2.353~9.62)、使用质子泵抑制剂(OR=2.377,95%CI:1.124~5.025)是影响VAP发生的独立危险因素(P<0.05)。根据Logistic回归分析结果拟合预测模型:PI=1.852X1+0.683X2+0.937X3+1.56X4+0.866X5-0.476(X1:机械通气时间;X2:支气管镜检查;X3:再插管;X4:使用类固醇激素;X5:使用质子泵抑制剂)。PI越大,发生VAP的风险越高。以PI为检验变量,以实际VAP发生为状态变量,绘制ROC曲线,结果显示AUC为0.845(SE=0.026,95%CI:0.795~0.895,P<0.001),灵敏度为89.96%、特异度为77.50%。结论机械通气时间、支气管镜检查、再插管、使用糖皮质激素、使用质子泵抑制剂是影响VAP发生的因素。本研究建立的预测模型对VAP的防治有一定价值。
Objective To explore the influencing factors of ventilator-associated pneumonia(VAP)in pediatric intensive care unit(PICU),and to build a predictive model.Methods From January 2015 to June 2019,the incidence of VAP in 600 patients with mechanical ventilation in PICU was analyzed retrospectively.Logistic regression method was used to analyze the risk factors affecting VAP,and a prediction model was built based on the analysis results.Then ROC curve method was used to analyze the value of the model to predict VAP.Results VAP was found in 54 of 600 children with PICU,accounting for 9.00%.Mechanical ventilation time(OR=6.375,95%CI:3.298~12.32),bronchoscopy(OR=1.979,95%CI:1.025~3.823),intubation(OR=2.553,95%CI:1.329~4.906),steroid hormone(OR=4.758,95%CI:2.353~9.62),proton pump inhibitor(OR=2.377,95%CI:1.124~5.025)were independent risk factors for VAP(P<0.05).According to the Logistic regression analysis results,the prediction model was fitted:PI=1.852X1+0.683X2+0.937X3+1.56X4+0.866X5-0.476(X1:mechanical ventilation time;X2:bronchoscopy;X3:re intubation;X4:steroid hormone use;X5:proton pump inhibitor use).The greater the PI,the higher the risk of VAP.The ROC curve was drawn with PI as the test variable and actual VAP as the state variable.The results showed that AUC was 0.845(SE=0.026,95%CI:0.795~0.895,P<0.001),with 89.96%of sensitivity and 77.50%of specificity.Conclusion The time of mechanical ventilation,bronchoscopy,intubation,steroid hormone and proton pump inhibitor are the factors influencing VAP.The prediction model established in this study has certain value for the prevention and treatment of VAP.
作者
万有仓
潘秀娟
WAN You-cang;PAN Xiu-juan(Department of Intensive medicine,Women′s and Children′s Hospital of Qinghai Province,Xining,Qinghai 810000,China;Infection Digestive Department,Women′s and Children′s Hospital of Qinghai Province,Xining,Qinghai 810000,China)
出处
《临床肺科杂志》
2021年第1期36-39,44,共5页
Journal of Clinical Pulmonary Medicine
关键词
机械通气
儿科重症病房
呼吸机相关性肺炎
预测模型
mechanical ventilation
pediatric ICU
ventilator-associated pneumonia
predictive model
