Acute appendicitis presenting as acute diarrhea accompanying hypokalemia

Development and Validation of a Differential Diagnosis Model for Acute Appendicitis and Henoch-Schonlein Purpura in Children

Objective: To study and develop a predictive model for the differential diagnosis of acute appendicitis (AA) and Henoch-Schonlein purpura (HSP) in children and to validate the model internally and externally. Methods: The complete data of AA and HSP cases were retrospectively analyzed and divided into internal and external verification groups. SPSS software was used for single-factor analysis and screening of independent variables, and R software was used for the development and verification of the diagnostic model. Lasso regression analysis was used to screen predictors and Lasso-logistic regression model was constructed, and K-fold cross-validation was used for the internal verification. In addition, nonfever patients were selected for model development and validation in the same way. Receiver operating characteristic (ROC) curves and calibration curves were drawn, respectively, to evaluate the 2 models. Results: Internal development and validation of the model showed that fever, neutrophil ratio (NEUT%), albumin (ALB), direct bilirubin (DBIL), C-reactive protein (CRP), and K were predictive factors for the diagnosis of HSP. The model was presented in the form of a nomogram, and the area under ROC curve of the development group and verification group was 0.9462 (95% confidence interval [CI] = 0.9402-0.9522) and 0.8931 (95% CI = 0.8724-0.9139), respectively. In the model of patients without fever, NEUT%, platelets (PLT), ALB, DBIL, alkaline phosphatase (ALP), CRP, and K were predictive factors for the diagnosis of HSP, and the area under ROC curve of the development group and verification group was 0.9186 (95% CI = 0.908-0.9293) and 0.8591 (95% CI = 0.8284-0.8897), respectively. Conclusion: In this study, 2 diagnostic models were constructed for fever or not, both of which had good discrimination and calibration, and were helpful to distinguish AA and HSP in children.