Application of decision tree in the analysis and prediction of risk factors of severe hand, foot and mouth disease combined with meningocephalitis

Objective To explore the risk factors in the severity progress of children's hand-foot-mouth disease (HFMD) combined with meningocephalitis by the model of C5.0 mixing with the Logistic regression (C5.0 combined models for short). Methods The method of cluster sampling was used to recruit the 324 cases of HFMD children in Zhengzhou Children's Hospital from April 2015 to July 2017. SPSS 21.0 was used to conduct the analysis of Logistic regression. SPSS Modeler 18.0 was used to establish the C5.0 model, SPSS Modeler 18.0 was used to establish the C5.0 combined models based on single Logistic regression analysis. The three models were compared by the differences of the results. Results The results of the three models were as follows:The C5.0 combined models showed heart rate above 140 time per minute, elevated blood sugar, shake of hands and feet and dysphoria. The C5.0 model showed heart rate above 140 time per minute, disorder of consciousness, elevated blood sugar, shake of hands and feet and vomiting. The Logistic regression model showed heart rate above 140 time per minute, shake of hands and feet, elevated blood sugar, vomiting, dysphoria and the ratio of neutrophils. The sensitivity, specificity, Youden index and the area under the ROC of the three models were as follows:the C5.0 combined models were 95.7%, 94.2%, 0.90, 0.946, the model of C5.0 were 80.7%, 88.3%, 0.69 and 0.845 respectively, the Logistic regression model were 98.0%, 70.0%, 0.68 and 0.840 respectively. Conclusions The model of C5.0 combined with the single Logistic regression is better than the C5.0 model and the Logistic regression model which are used to predict the risk factors in the severity progress of HFMD combined with meningocephalitis.