Risk factors for multidrug-resistant organisms pulmonary infections in patients with severe craniocerebral injury and establishment of prediction model
OBJECTIVE To explore the risk factors for multidrug-resistant organisms(MDROs)pulmonary infec-tions in the patients with severe craniocerebral injury,establish and validate the risk prediction model.METHODS A total of 430 craniocerebral injury patients with pulmonary infection who were treated in Ganzhou People's Hos-pital from Jan 2018 to Dec 2023 were enrolled in the study and were randomly divided into the modeling group with 301 cases and the validation group with 129 cases in a 7∶3 ratio.The logistic regression model was estab-lished based on the modeling data,the risk factors were assigned for score based on β value.The efficiency of the model in prediction of risk of MDROs pulmonary infection was validated by means of receiver operating character-istic(ROC)curves.RESULTS The result of logistic regression analysis showed that no less than 65 years of age,mechanical ventilation duration no less than 7 days,tracheotomy,length of hospital stay no less than 30 days,use of antibiotics for no less than 14 days and coma were the risk factors for the MDROs pulmonary infections in the craniocerebral injury patients(P＜0.05).2,1,2,2,1 and 1 point were respectively scored for the corresponding risk prediction model.The area under ROC curve(AUC)of the risk model was 0.776(95％CI:0.659-0.893,P＜0.001)in the modeling group,0.760(95％CI:0.643-0.877,P＜0.001)in the validation group.CONCLUSION The no less than 65 years of age,mechanical ventilation duration no less than 7 days,tracheotomy,length of hospital stay no less than 30 days,use of antibiotics for no less than 14 days and coma are the risk factors for the MDROs pulmonary infections in the patients with severe craniocerebral injury.The risk assessment system has favorable predictive effect for all the severe craniocerebral injury patients in both the modeling group and the validation group and may facilitate the identification of high-risk population and optimize the clinical diagnosis and treatment strate-gies.
Severe craniocerebral injuryMultidrug-resistant organismPulmonary infectionRisk factorPredic-tion model
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