Development and Validation of a Predictive Model for the Diagnosis of Acute Appendicitis in Children

Objective To develop a predictive model for diagnosing acute appendicitis in pediatric patients. Material and methods The study was conducted at the Surgical Department of Ulyanovsk Regional Children’s Clinical Hospital from September 1, 2023, to June 1, 2024. The analysis included patients admitted with suspected acute appendicitis. A total of 400 patients were included in the study, of which 300 were diagnosed with acute appendicitis, and 100 had functional bowel disorders. Patient characteristics were assessed using a standardized protocol. Results Univariate statistical analysis showed that the differential diagnosis of these conditions is most frequently required in children aged 6–12 years. Logistic regression analysis indicated that nausea (OR 11.586; 95% CI 3.347–40.125), white blood cell count (OR 1.52; 95% CI 1.343–1.721), lymphocyte count (OR 0.59; 95% CI 0.371–0.939), age (OR 1.207; 95% CI 1.079–1.350), appendix diameter of >6 mm (OR 32.691; 95% CI 12.846–83.179), and vomiting (OR 0.121; 95% CI 0.03–0.487) were independent risk factors for acute appendicitis in children during differential diagnosis. The identified variables were included in a nomogram using logistic regression analysis. The validation results showed that the area under the ROC curve was 0.967±0.008, with a 95% CI of 0.951–0.983. The developed model was statistically significant (p