Association Between Skull Base Fracture Location and Likelihood of Developing a Traumatic CSF Leak

Abstract

Background: Skull base fractures (SBFs) pose a significant risk for traumatic cerebrospinal fluid (CSF) leaks, which can lead to serious complications if undetected. Despite anatomical correlations, the predictive value of fracture location on CSF leak development remains inadequately explored in contemporary clinical settings. Objective: To evaluate the association between specific skull base fracture locations (anterior, middle, posterior) and the likelihood of developing a traumatic CSF leak in adult head-injured patients. Methods: This cross-sectional observational study was conducted at the Neurosurgery Department of Shaheed Mohtarma Benazir Bhutto Institute of Trauma (SMBBIT), Karachi, from July to December 2024, including 200 patients with radiographically confirmed skull base fractures. Adults over 18 years were included, excluding those with pathological, surgical, or congenital causes of CSF leaks. Clinical diagnosis of CSF rhinorrhea or otorrhea was supported by bedside glucose testing, and fracture location was confirmed via CT/MRI. Ethical approval was obtained, and all participants provided informed consent per the Declaration of Helsinki. Statistical analyses were conducted using SPSS v25, employing chi-square tests, Pearson correlation, and linear regression to assess associations. Results: CSF leaks occurred in 10% of cases, predominantly in anterior fractures (12/75), but the chi-square test showed no statistically significant association (p = 0.118). Regression analysis revealed fracture location (β = -0.234, p = 0.005) and gender (β = -0.180, p = 0.030) as significant predictors, while age was not. Conclusion: Although anterior skull base fractures were more frequently associated with CSF leaks, fracture location alone did not predict leakage in univariate analysis. Gender and anatomical site, however, emerged as significant predictors in multivariate modeling. These findings support a multifactorial risk assessment approach to enhance early CSF leak detection and improve outcomes in head trauma management.