Association between craniofacial trauma and traumatic brain injury in patients admitted to a tertiary care hospital: a prospective cross-sectional study.

PURPOSE: Craniofacial trauma and traumatic brain injuries (TBIs) frequently coexist due to their close anatomical proximity, making it essential to understand their correlation for optimal patient management. This study examines the association between specific types of craniofacial fractures and corresponding brain injuries in patients admitted to a tertiary care hospital.

METHODS

A prospective cross-sectional study was carried out in the Department of Neurosurgery, Liaquat University of Medical and Health Sciences, from October 2024 to February 2025. Fifty-six patients with both craniofacial and brain injuries were included. Data collection involved systematic clinical evaluation, imaging studies, and statistical analyses using Pearson correlation coefficients, Spearman correlation coefficients, and ordinal logistic regression.

RESULTS

The most common mechanism of injury was road traffic accidents (87.5%), and the most frequent craniofacial injuries were midface fractures (82.1%), with zygomaticomaxillary complex and naso-orbito-ethmoid fractures showing a significant association with pneumocephalus (P<0.05). Le Fort type I fractures were associated with subarachnoid hemorrhage. Patients with more than two midface fractures were 4.16 times more likely to sustain brain injuries (B=1.069; 95% confidence interval [CI], 0.301-1.837; P=0.006). Frontal air sinus fractures, especially with bilateral and both-table involvement, were strongly correlated with contusions and pneumocephalus (B=1.627; 95% CI, 0.569-2.684; P=0.003). Palatal fractures demonstrated a significant association with diffuse axonal injury (P=0.032).

CONCLUSIONS

The study highlights a significant correlation between craniofacial fractures and TBI severity, highlighting the importance of early detection and multidisciplinary management. Further large-scale studies are warranted to refine predictive models and improve clinical outcomes.