Development and validation of a diagnostic nomogram based on peripheral blood composite inflammatory markers for complicated acute appendicitis: a retrospective study

Background Accurate distinction between complicated acute appendicitis (CAA) and simple acute appendicitis (SAA) is crucial for guiding treatment decisions. This study aimed to systematically evaluate the diagnostic value of peripheral blood inflammatory composite markers and develop a predictive model for CAA. Methods In this retrospective study, 533 patients with acute appendicitis (429 in the training set and 104 in the validation set) admitted between January 2018 and December 2024 were enrolled. Various peripheral blood composite inflammatory markers were calculated. Multivariate stepwise logistic regression identified independent predictors. Based on these predictors, a diagnostic nomogram was constructed and its performance was evaluated using receiver operating characteristic (ROC) curve analysis, calibration curves, and decision curve analysis (DCA). Results The Systemic Inflammation Response Index (SIRI, OR = 2.972, 95% CI: 1.722–5.187, P < 0.001), Neutrophil-to-Albumin Ratio (NAR, OR = 3.099, 95% CI: 1.693–5.723, P < 0.001), and Prognostic Nutritional Index (PNI, OR = 0.553, 95% CI: 0.309–0.969, P = 0.041) were identified as independent predictors. The areas under the ROC curve (AUC) for SIRI, NAR, and PNI were 0.739, 0.742, and 0.535, respectively. The nomogram model incorporating these three markers showed an AUC of 0.758 (95% CI: 0.714–0.803) in the training set and 0.756 (95% CI: 0.656–0.857) in the validation set. Calibration curves indicated good agreement between predicted and observed outcomes (mean absolute error [MAE] = 0.022 and 0.025, respectively), and DCA confirmed the clinical utility of the model across a range of threshold probabilities in both cohorts. Conclusion This study demonstrates that SIRI, NAR, and PNI are independently associated with acute appendicitis severity. The developed nomogram, integrating these three markers, offers a simple, cost-effective tool with good diagnostic performance for distinguishing CAA from SAA, potentially aiding in timely clinical decision-making and individualized treatment planning.