Influencing Factors of Ventilator-Associated Pneumonia in Preterm Infants with Respiratory Distress Syndrome and Construction of Nomogram Model for Predicting Its Risk
Objective To explore the influencing factors for ventilator-associated pneumonia(VAP)in preterm infants with respiratory distress syndrome(RDS),and construct and validate the nomogram model for predicting its risk.Methods A total of 224 premature infants with RDS admitted to Affiliated Hospital of Yangzhou University from August 2020 to August 2023 were selected.Preterm infants were divided into the modeling set(156 cases)and the validation set(68 cases)in a 7∶3 ratio by the random number table method.The information of mothers and preterm infants were collected.The preterm infants were divided into VAP group and non-VAP group according to whether VAP occurred or not in the modeling set.Multivariate Logistic regression analysis was used to explore the influencing factors of VAP in preterm infants with RDS;R software and rms package were used to establish the risk prediction nomogram model for VAP in preterm infants with RDS;Hosmer-Lemeshow goodness-of-fit test was used to evaluate the degree of the fit of the nomogram model;and ROC curves were used to analyze the predictive value of the nomogram model for VAP in preterm infants with RDS.Results VAP occurred in 74 of 156 preterm infants in the modelling set,with an incidence rate of 47.44%.There was significant difference in Neonatal Critical Illness Score(NCIS),invasive mechanical ventilation time,non-invasive ventilation time after extubation,and the number of repeated intubation on the machine between the two groups(P<0.05).Multivariate Logistic regression analysis showed that NCIS,invasive mechanical ventilation time,non-invasive ventilation time after extubation,and the number of repeated intubation on the machine were independent influencing factors for VAP in preterm infants with RDS(P<0.05).Based on the above factors,the nomogram model was constructed to predict the risk of VAP in preterm infants with RDS.The results of the Hosmer-Lemeshow goodness-of-fit test showed that the nomogram model fitted better in the modeling set and validation set(P<0.05).ROC curve analysis showed that the AUC of nomogram model for predicting VAP in preterm infants with RDS in modeling set and verification set was 0.958[95%CI(0.914-0.999)]and 0.875[95%CI(0.723-0.951)],respectively.Conclusion NCIS,invasive mechanical ventilation time,non-invasive ventilation time after extubation,and number of repeated intubation on the machine are independent influencing factors for VAP in preterm infants with RDS.The nomogram model constructed based on above factors has a better discriminatory ability for VAP in premature infants with RDS.
Respiratory distress syndrome,newbornInfant,prematurePneumonia,ventilator-associatedRoot cause analysisNomograms
万方数据
维普
