Development and Validation of a Predictive Model for Complicated Appendicitis in the Elderly: A Retrospective Comparative Study

Objective The clinical manifestations of acute appendicitis in the elderly population frequently present as atypical, resulting in delayed diagnosis and a significantly increased risk of progression to complicated appendicitis. This progression complicates treatment strategies and adversely affects prognostic outcomes. Presently, there exists a deficiency of simple and reliable early prediction tools for complicated appendicitis in this demographic. The objective of this study was to investigate independent risk factors associated with complicated appendicitis in the elderly and to develop a clinical prediction model. Methods Clinical data from 288 elderly patients with acute appendicitis admitted to the General Surgery Department of Jiangsu Province (Suqian)Hospital, between January 2016 and December 2024 were retrospectively analyzed. Patients were categorized into a complicated appendicitis (CA) group (n = 117) and an uncomplicated appendicitis (UCA) group (n = 171) based on postoperative pathology. Univariate and multivariate logistic regression analyses were performed to identify independent predictors and to develop a predictive model. Model performance was evaluated using the Hosmer-Lemeshow (H-L) test, calibration curves, and receiver operating characteristic (ROC) curves. Results Multivariate analysis identified white blood cell count (WBC) ≥ 12.81×10⁹/L (OR = 2.78), lymphocyte count ≤ 0.955×10⁹/L (OR = 0.27), and C-reactive protein (CRP) ≥ 56.085 mg/L (OR = 20.42) as independent predictors of CA. The constructed predictive model exhibited an area under the curve (AUC) of 0.85, with a sensitivity of 81.2%, and a specificity of 84.8%. The H-L test indicated satisfactory model calibration (P = 0.933). Conclusion The predictive model based on WBC, lymphocyte count, and CRP exhibits strong predictive performance for complicated appendicitis in the elderly population. This model enhances the early identification of high-risk patients and serves as a valuable reference for clinical decision-making.