Early prediction of severe acute cholecystitis using routine admission parameters: a study of 1,330 patients.

To evaluate routine clinical, demographic, and laboratory admission parameters as independent predictors of severe acute cholecystitis to facilitate early risk stratification. A total of 1,330 adult patients diagnosed with acute cholecystitis according to the Tokyo Guidelines 2018 (TG18) were analyzed in this single-center, retrospective study between 2019 and 2024. Patients were classified into mild/moderate (Group 1) and severe (Group 2) cohorts. Independent predictors of severe acute cholecystitis were determined using logistic regression and ROC analyses. To avoid incorporation bias, variables directly defining TG18 Grade 3 organ dysfunction were excluded from the multivariate models. Furthermore, internal validation was performed via bootstrap resampling (1000 iterations), and clinical utility was assessed using decision curve analysis (DCA). Group 2 (severe disease) comprised 12.9% (n = 172) of the cohort. The severe group was significantly older with a higher prevalence of diabetes. In multivariate analysis, the CRP/albumin ratio (CAR), age, diabetes mellitus, and hemoglobin level were identified as independent predictors The model demonstrated stable, moderate discriminatory power (AUC = 0.766). A Youden-derived CAR cut-off of > 1.10 significantly increased severe disease likelihood. DCA confirmed the model yielded superior net clinical benefit across relevant threshold probabilities. The combination of advanced age, diabetes mellitus, lower hemoglobin levels, and elevated CAR can provide a practical supportive framework for predicting severe acute cholecystitis. Within this multivariable approach, these routine admission parameters may enhance early bedside risk stratification and guide clinical vigilance alongside standard TG18 assessment.