Clinical and Radiological Predictors of Invasive Fungal Sinusitis.

Background: Invasive fungal sinusitis (IFS) is associated with high mortality rates, chiefly because it is often diagnosed late in the course of disease when infection has spread to the orbit, skull base, or intracranially. We aimed to define early clinical and radiologic indicators of IFS, which can be integrated into a prediction model and clinical management algorithms. Methods: Patients with proven or probable IFS were identified in 2 tertiary-level hospitals as part of prospective monitoring of invasive mycoses. Patients with similar underlying medical conditions who underwent sinus computed tomography (CT) and nasal endoscopy because of new-onset sinus symptoms served as controls. Computed tomography images were reviewed by 2 blinded radiologists, and features were scored on structured report forms. Computed tomography and clinical data were compared between cases and controls; variables associated with IFS were further assessed in multivariate regression models. Results: Twenty-seven patients with IFS were identified and matched 1:1 with control patients. Ocular pain, preauricular or premaxillary fat infiltration on sinus CT, and mucosal necrosis identified on nasal endoscopy were independently associated with IFS and were retained in the regression model. Model sensitivity and specificity were 0.77 and 0.96, respectively, with an area under the receiver-operating curve of 0.88. Conclusions: Integration of radiologic and clinical features allowed early prediction of IFS, suggesting that these criteria could be used in the context of a clinical diagnostic algorithm.