Abstract:
Background and Objective: Preseptal and orbital cellulitis are common periorbital infections in children, and early differentiation is crucial because their treatment and potential complications differ substantially. This study aimed to investigate the diagnostic value of clinical, laboratory, and imaging findings in differentiating these two conditions and to identify independent markers predictive of orbital involvement.
Materials and Methods: A total of 157 patients (119 with preseptal cellulitis and 38 with orbital cellulitis) followed between January 2016 and December 2025 were retrospectively reviewed. Demographic, clinical, laboratory, and radiological data were compared between the two groups. Independent predictors were evaluated using logistic regression analysis, and diagnostic performance was assessed by receiver operating characteristic (ROC) analysis.
Results: Symptom duration was significantly longer in the orbital cellulitis group and demonstrated the highest discriminative performance among clinical markers (AUC = 0.717). Painful and restricted eye movements and decreased visual acuity were significantly more frequent in orbital cellulitis (high specificity, lower sensitivity). Neutrophil count, C-reactive protein (cut-off >37.28 mg/L), erythrocyte sedimentation rate, systemic immune-inflammation index (SII), and systemic inflammatory response index (SIRI) were significantly higher in orbital cellulitis. Multivariable analysis identified symptom duration and orbital fat stranding on CT as independent predictors of orbital involvement (overall model accuracy = 82.8%).
Conclusion: Symptom duration, ocular findings suggestive of orbital involvement, and readily available inflammatory markers are key parameters assisting clinicians in differentiating preseptal from orbital cellulitis. Comprehensive clinical and laboratory evaluation helps prevent unnecessary radiation exposure in low-risk cases while reserving CT for persistent diagnostic uncertainty.
Keywords: Orbital Cellulitis; Child; Tomography, X-Ray Computed; Biomarkers; Diagnosis, Differential

