Assessing mechanisms of injury as predictors of severe injury for adult car and truck occupants

Other conference contribution, 2015

This study evaluates Mechanisms of Injury (MOI) that can be rapidly assessed at the scene of accident and may be used as predictors of severe injury for traffic accidents involving occupants in cars or trucks. The objective is to increase the knowledge of how MOI can be used to differentiate whether a patient is severely injured or not. This knowledge can be used to improve trauma triage systems. Furthermore, an objective is to analyze safety differences between cars and light/heavy trucks. The scope is adult occupants of cars, light and heavy trucks injured in accidents registered in the Swedish Traffic Accident Data Acquisition (STRADA) database from 2003 to 2013. Partition between severe and non-severe injury was done according to the Injury Severity Score (ISS) with ISS > 15 as definition of severe injury. The MOIs considered were: belt use, airbag deployment, posted speed limit, elderly occupant (age ≥ 55 years), sex, type of accident (single, intersection, turning, head-on, overtaking, rear end, tram/train, wild animal or other) and location of the accident (urban or rural). The different MOI were evaluated individually using univariate chi-square tests and together using multivariate logistic regression models. Results show that belt use is the most crucial factor determining risk of severe injury for all vehicle types. Age is the second most important factor, with elderly occupants exhibiting a higher risk. Head-on accidents are the most dangerous for cars and light trucks while single accidents are the most dangerous for heavy trucks. Belt use compliance is much lower for truck occupants. This appears to be the main reason for the frequency of severe injury being higher for truck occupants than for car occupants.