TY  - CONF
A1  - Hannawald, Lars
A1  - Liers, Henrik
A1  - Brehme, H.
T1  - Prediction of severe injuries for the optimization of the pre-clinical rescue period of car occupants
N2  - The number of injured car occupants decreases constantly. Nevertheless, they account for nearly 50% of all fatalities and about 44% of all seriously injured persons in German traffic accidents. Further reductions of casualties require multiple efforts in all parts of traffic safety. In this paper a detailed analysis of the important pre-hospital rescue phase was done. The basis for future improvements is the knowledge about injury causation of car occupants in combination with other corresponding influence factors. For that reason more than 1.200 severe (AIS3+) injuries of frontal car occupants were analyzed. For the most relevant injuries of car occupants multivariate analysis models were created to predict the probability of these injuries in a real crash scenario. In addition to the collision severity different influence factors like impact direction, seat belt usage, age of the occupant, and gender were analyzed. Furthermore, the models were checked regarding the goodness of fit and all results all results were checked concerning their robustness. The prediction models were created on the basis of 5.000 car accidents. Afterwards, the models were validated using 4.000 different car accidents. The prediction of the probability of severe injuries could be used for different applications in the field of traffic safety. One possibility is the implementation of the models in a tool for the on-the-spot diagnosis. The background for the development of such applications is the fact, that there are only limited diagnostic possibilities available at the accident scene. Nevertheless, the rescue forces have to make essential decisions like the alerting of the necessary medical experts, appropriate treatment, the type of transportation and the choice of an adequate hospital. These decisions quite often decide between life and death or influence the long-term effects of injured persons. At this point, indications of expectable injuries could help enormously. To enable even persons with limited technical knowledge to use the tool, a procedure was developed that facilitates the assumption of the given crash severity. Another important possibility for the application of the prediction models is the use for the qualification of information sent by e-call systems.
KW  - Befreiung (Bergung)
KW  - Deutschland
KW  - Erste Hilfe
KW  - Konferenz
KW  - Prognose
KW  - Schweregrad (Unfall
KW  - Verletzung)
KW  - Untersuchung am Unfallort
KW  - Verbesserung
KW  - Verletzung
KW  - Conference
KW  - Extrication
KW  - First aid
KW  - Forecast
KW  - Germany
KW  - Improvement
KW  - Injury
KW  - On the spot accident investigation
KW  - Severity (accid
KW  - injury)
Y1  - 2013
UR  - https://bast.opus.hbz-nrw.de/frontdoor/index/index/docId/627
UR  - https://nbn-resolving.org/urn:nbn:de:hbz:opus-bast-6278
ER  -