EVALUATION OF CLINICAL AND LABORATORY PARAMETERS FOR HOSPITALIZATION IN ACUTE PAROTITIS: A ROC-BASED ANALYSIS

Kadir Sinasi BULUT, Burak CELIK, Serkan SERIFLER, Fatih GUL

Van Medical Journal - 2026;33(3):247-254

Ankara Yildirim Beyazit University, School of Medicine, Department of Otolaryngology, Head and Neck Surgery, Ankara, Türkiye

 

Introduction: Acute parotitis (AP) ranges from mild local inflammation to systemic complications. While some patients can be treated as outpatients, others require hospitalization and intravenous therapy. This study aimed to identify clinical and laboratory predictors of hospitalization and determine optimal cut-off values using receiver operating characteristic (ROC) curve analysis in patients presenting to the emergency department with AP. Materials and Methods: This retrospective study included 62 patients diagnosed with AP between 2019 and 2025. Demographic characteristics, clinical findings (oral feeding intolerance, purulent discharge from Stensen's duct, and comorbidities), and laboratory parameters were evaluated. Logistic regression analysis was used to identify independent predictors of hospitalization, and ROC analysis was performed to determine discriminatory performance and optimal cut-off values. Results: The mean age was 49.90+/-20.44 years, and 59.6% were female. Hospitalized patients were older and had higher WBC, neutrophil counts, CRP levels, and BUN/creatinine ratios, while lymphocyte counts were lower. Oral feeding intolerance and purulent discharge from Stensen's duct were more frequent among hospitalized patients. Multivariate analysis identified age (OR: 1.065, 95% CI: 1.018-1.114, p=0.006) and CRP (OR: 1.038, 95% CI: 1.006-1.071, p=0.021) as independent predictors of hospitalization. ROC analysis identified cut-off values of >=61.5 years for age (AUC=0.843) and >=22.95 mg/L for CRP (AUC=0.832). The combined model incorporating age and CRP showed good discriminatory performance (AUC=0.887). Conclusion: Older age and elevated CRP levels were independently associated with hospitalization in patients with AP. ROC-derived cut-off values and the combined predictive model may support clinical decision-making in the emergency management of AP.