Development of a risk prediction model for adhesive intestinal obstruction following laparoscopic surgery for acute appendicitis based on clinical characteristics and laboratory indicators

BackgroundAdhesive intestinal obstruction (AIO) is a recognized complication following laparoscopic surgery for acute appendicitis (AA), although its overall incidence remains relatively low. This study aimed to develop a risk prediction model based on clinical characteristics and laboratory indicators to facilitate early identification and prevention of postoperative AIO.MethodsIn this retrospective cohort study, 298 AA patients who underwent laparoscopic surgery between January 2020 and November 2024 were enrolled. Patients were categorized into AIO (n = 32) and non-AIO (n = 266) groups. Data were collected from electronic medical records and telephone follow-ups. Univariate analysis compared clinical and laboratory variables between groups. Significant variables underwent collinearity analysis, and those without collinearity were entered into binary logistic regression to identify independent predictors. A nomogram prediction model was constructed and internally validated using bootstrap resampling. Model performance was assessed using calibration curves and the area under the receiver operating characteristic curve (AUC).ResultsCompared with the non-AIO group, the AIO group exhibited significantly longer disease duration, a higher prevalence of systemic inflammatory response syndrome (SIRS), elevated white blood cell count (WBC), increased neutrophil-to-lymphocyte ratio (NLR), and lower albumin (ALB) levels (p < 0.05). Logistic regression identified disease duration, SIRS, WBC, and NLR as independent risk factors for AIO (OR >1, p < 0.05), while ALB served as a protective factor (OR <1, p < 0.05). The resulting nomogram demonstrated excellent discrimination, with an AUC of 0.960 (95% CI: 0.912–1.000), and the calibration curve closely aligned with the ideal standard.ConclusionDisease duration, SIRS, WBC, NLR, and ALB are significantly associated with AIO occurrence after laparoscopic appendectomy. The developed prediction model effectively stratifies postoperative AIO risk in AA patients, potentially assisting clinicians in implementing timely preventive measures and reducing AIO incidence.