Mandibular fractures: An analysis of the epidemiology and patterns of injury in 4,143 fractures

Purpose: The objective of this study was to complete a comprehensive retrospective review of the epidemiology and patterns of injury in mandibular trauma based on the Parkland Memorial Hospital trauma database over a 17-year period. The authors identified 4,143 fractures in 2,828 patients from the databank. In mandibular trauma, the mechanism of injury and several other variables can be an important point of differentiation with regard to fracture pattern. By showing the statistical relation between these and fracture pattern, the authors hope to provide surgeons with a better understanding of such a relation. Materials and Methods: Mandibular fracture data were collected from the Parkland Memorial Hospital trauma registry using International Classification of Diseases, Ninth Revision codes (802.21 to 802.39). Information included fracture type, age, gender, mechanism of injury, and associated injuries. The Parkland Memorial Hospital trauma registry yielded 4,143 mandibular fractures in 2,828 patients managed at Parkland Memorial Hospital from 1993 through 2010. Results: Based on retrospective analysis, results were obtained for age, gender, monthly distribution, anatomic distribution, and mechanism of injury. The average age was approximately 38 years, with most patients (33%) in the third decade. An overwhelming majority of patients were men (83.27%), with only 16.27% consisting of women. Most injuries occurred in the summer months, with July being the most common month of occurrence. The mechanism of injury predominantly involved low-velocity blunt injuries (62%) compared with high-velocity blunt injuries (31%). The anatomic distribution of fractures evaluated was the angle (27%), symphysis (21.3%), condyle and subcondyle (18.4%), and body (16.8%). Conclusion: This study helps provide and support the relation between several variables associated with many common traumatic injuries seen in the mandible. This analysis can be used to help surgeons identify and anticipate injuries based on age, gender, and mechanism of injury.