Diagnostic value of leukocytosis in patients presenting to the emergency department with abdominal pain: A retrospective observational study

Background: Abdominal pain is one of the most common complaints in emergency departments (EDs) and poses diagnostic challenges due to its broad differential diagnosis. Leukocytosis is frequently used as a biomarker in clinical evaluation; however, its diagnostic value in predicting surgical conditions remains unclear. Aims and Objectives: This study aimed to assess the diagnostic value of leukocytosis in patients presenting to the ED with abdominal pain and determine its relationship with the need for surgical intervention. Materials and Methods: This retrospective, cross-sectional study was conducted at Esenyurt Necmi Kadıoğlu State Hospital ED, analyzing medical records of adult patients presenting with abdominal pain between January 1, 2023, and December 31, 2024. Patients were categorized based on white blood cell (WBC) count into four groups. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of leukocytosis in predicting surgical needs were calculated. Statistical analyses included receiver operating characteristic curve analysis, Chi-square tests, and logistic regression modeling. Results: A total of 750 patients were included in the final analysis. Leukocytosis was observed in 59.7% of patients. Surgical intervention was required in 41.2% of cases. A significant association was found between elevated WBC counts and the need for surgery (P=0.002). Leukocytosis showed 85% sensitivity, 75% specificity, 78% PPV, and 80% NPV. Patients with WBC >15.0×103/μL were 3.5 times more likely to require surgery. Conclusions: Leukocytosis is a useful diagnostic marker for identifying patients with abdominal pain who may require surgical intervention. However, due to its limited specificity, it should be interpreted alongside clinical and imaging findings. Further multicenter prospective studies are needed to validate these findings and improve diagnostic algorithms.