Abstract
Objectives: Pediatric acute appendicitis (AA) is one of the most prevalent acute abdomens in the department of pediatric surgery. Children with complicated AA may need timely decisions on surgery and have a worse prognosis. We explored the risk factors and developed a predictive model for complicated AA in children.
Methods: A retrospective analysis was conducted on patient information from those hospitalized for acute appendicitis confirmed by post-surgery pathological results at Children's Hospital of Chongqing Medical University between September 2022 and October 2023. Lasso regression was performed to identify risk factors and multivariate logistic regression analysis was used for model establishment.
Results: Serum levels of IFN-γ, IL-5, IL-6, IL-8, and IL-10 before surgery are useful in the classification of acute appendicitis in children. IL-6, IL-8, and IL-10, on their own, had high predictive values for CA in children. Independent risk factors for CA were age, IL-10, and IFN-γ. A multifactorial logistic regression prediction model was so established, and it demonstrated good predictive efficacy. Its predictive sensitivity was 70.0%, and specificity was 73.9%, with an AUC of 0.7949. Furthermore, the results of the external validation indicated that the model's accuracy was good with an AUC of 0.8567.
Conclusions: It's imperative to identify CA early and make clinical decisions. Prediction models based on age, IL-10, and IFN-γ may be reliable and accurate in predicting the incidence of CA, which may lead to better clinical outcomes for kids with AA.