Establishment of prediction model for multidrug-resistant organisms infections in patients of intensive care unit of neurology department
OBJECTIVE To observe the prevalence of multidrug-resistant organisms(MDR)infections among the patients of intensive care unit(ICU)of neurology department,analyze the distribution of pathogens and establish the prediction model.METHODS A total of 598 patients who were treated in ICU of neurology department of the First People's Hospital of Lianyungang City from Jan 2020 to Jan 2023 were enrolled in the study and were divided into the MDR infection group with 42 cases and the no MDR infection group with 556 cases according to the status of MDR infection.The distribution of isolated MDR and risk factors for the MDR infections were analyzed,the prediction model was established,and the predictive efficiency was evaluated.RESULTS Totally 42 strains of MDR were isolated from the 598 ICU patients of neurology department,and the incidence of MDR infection was 7.02％.The old age,catheter indwelling,length of hospital stay no less than 10 days and combined use of broad spectrum antibiotics were the risk factors for the MDR infections in the ICU patients of neurology department(P＜0.05).The risk prediction model was established based on the risk factors,the result of Hosmer-Lemeshow test of good-ness of fit showed that the model had favorable goodness of fit(x2=5.785,P=0.671);the result of calibration curve indicated that the predicted probability was close to the actual probability,showing that the model had fa-vorable capability of differentiation,calibration and prediction.The result of receiver operating characteristic(ROC)curve analysis showed that area under curve(AUC)was 0.702,with 95％CI 0.616-0.788.The sensitivity of the model was 70.00％for diagnosis,with the specificity 77.50％,indicating that the model had favorable dis-crimination degree.CONCLUSION The incidence of MDR infection is high among the ICU patients of neurology department,there are a variety of risk factors for the MDR infections.The prediction model that is established based on the screened risk factors can provide basis for formulating prevention measures.
Neurology departmentIntensive care unitMultidrug-resistant organismRisk factorPrediction modelNomogram
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