Objective: Road traffic accidents (RTAs) are the first cause of abdominopelvic injuries (APIs). The objective of this study was to describe the characteristics and severity of APIs due to traffic accidents in a large French trauma registry and to identify risk factors for API.
Methods: All victims from the French Rhône registry of victims of RTAs were analyzed from 1996 to 2013. This registry contained data that were issued over a 20-year period from 245 medical departments, from prehospital care until re-adaptation, and forensic medicine departments. All APIs, defined as an injury between the diaphragm and the pelvic bone, were extracted and studied.
Results: Among 162,695 victims, 10,165 had an API (6.7%). Accidents frequently involved young men and 2 cars. Mean Injury Severity Score (ISS) was 8.7. Mortality rate was 5.6%. Soft tissue injuries largely predominated (n = 6,388; 54.4% of patients). Overall, 2,322 victims had a pelvic bone injury. Internal abdominal organs were involved in 2,425 patients; the most frequent were the spleen, liver, and kidney. Wearing of the seat belt appeared to be a significant protective factor in API, including serious injuries. A partial analysis over the past 2 years among the most severe patients hospitalized in the intensive care unit indicated that nonoperative management was carried out in two thirds of the wounded. In uni- or multivariate analysis, sex, age, type of user, antagonist, time of occurrence, associated severe lesions, or wearing of the seat belt were statistically associated with the occurrence of API, highlighting a more dangerous user profile.
Conclusions: Abdominopelvic injuries concern a minority of road traffic injuries, but they are responsible for significant mortality. Large solid organs are the most frequently affected. Women drivers wearing a seat belt and driving in town during the day appear to be more protected against API. 相似文献
Urban rail network safety is a critical sector of urban public safety. However, there is no uniform standard for the safety evaluation of the urban rail network. This paper presents a novel methodology by integrating a multilevel decision tree with a fuzzy analytical approach to enhance urban rail network safety. The proposed methodology overcomes serious limitations such as subjectivity in the data and independence of the variables in decision-making processes. The proposed methodology is applied to the risk evaluation of the selected Chongqing rail transit lines and the Expo Line. The risk analysis is considered using the field data collected from these transit lines. The applied case studies confirm the general applicability of the methodology and the multilevel decision tree network. The main risk factors identified for the Chongqing rail traffic system are the terrorist threat, emergency management, and aging infrastructure which need to be investigated as a priority to mitigate risk associated with these infrastructures. 相似文献