RESUMO
Objective To study the main influence factors of nosocomial infection(NI) and establish a model to predict and forecast the risk of NI on patients in hospitals. Methods Clinical data of 27352 inpatients extracted from hospital information system were sorted out and coded, and a logistic regression model about the probability of NI was established. The risk of NI was divided into four scales. Results With multiple factor analysis,16 risk factors of NI were identified, which were age, high body temperature, numbers of diagnosis, days of staying in hospital and seriousness, numbers of routine test for urine, times of blood transfusion, use or without use of antibiotic and radiotherapy, turning over the bodies or not, relationships between infection and interventional operations, with or without diabetes, categories of diseases based on ICD-9, numbers of interventional operations, type of anesthesia and department of admission. If NI was judged when predicted probability(Pr)of logistic regression model exceeded 0 35, the specificity and false diagnostic rate of diagnostic test were 0 995 and 0 005 respectively, and the area under ROC curve was 0 986. According to decision tree method, the risk of NI was classified into four degrees: low (Pr