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Article

Development, and Internal, and External Validation of a Scoring System to Predict 30-Day Mortality after Having a Traffic Accident Traveling by Private Car or Van: An Analysis of 164,790 Subjects and 79,664 Accidents

1
Department of Clinical Medicine, Miguel Hernández University, San Juan de Alicante, 03550 Alicante, Spain
2
Department of Pathology and Surgery, Miguel Hernández University, San Juan de Alicante, 03550 Alicante, Spain
*
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
Int. J. Environ. Res. Public Health 2020, 17(24), 9518; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17249518
Received: 23 November 2020 / Revised: 15 December 2020 / Accepted: 16 December 2020 / Published: 18 December 2020
(This article belongs to the Special Issue Predictive Models That Can Impact Public Health)
Predictive factors for fatal traffic accidents have been determined, but not addressed collectively through a predictive model to help determine the probability of mortality and thereby ascertain key points for intervening and decreasing that probability. Data on all road traffic accidents with victims involving a private car or van occurring in Spain in 2015 (164,790 subjects and 79,664 accidents) were analyzed, evaluating 30-day mortality following the accident. As candidate predictors of mortality, variables associated with the accident (weekend, time, number of vehicles, road, brightness, and weather) associated with the vehicle (type and age of vehicle, and other types of vehicles in the accident) and associated with individuals (gender, age, seat belt, and position in the vehicle) were examined. The sample was divided into two groups. In one group, a logistic regression model adapted to a points system was constructed and internally validated, and in the other group the model was externally validated. The points system obtained good discrimination and calibration in both the internal and the external validation. Consequently, a simple tool is available to determine the risk of mortality following a traffic accident, which could be validated in other countries. View Full-Text
Keywords: accidents; traffic; mortality; death; models; statistical accidents; traffic; mortality; death; models; statistical
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MDPI and ACS Style

Palazón-Bru, A.; Prieto-Castelló, M.J.; Folgado-de la Rosa, D.M.; Macanás-Martínez, A.; Mares-García, E.; Carbonell-Torregrosa, M.d.l.Á.; Gil-Guillén, V.F.; Cardona-Llorens, A.; Marhuenda-Amorós, D. Development, and Internal, and External Validation of a Scoring System to Predict 30-Day Mortality after Having a Traffic Accident Traveling by Private Car or Van: An Analysis of 164,790 Subjects and 79,664 Accidents. Int. J. Environ. Res. Public Health 2020, 17, 9518. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17249518

AMA Style

Palazón-Bru A, Prieto-Castelló MJ, Folgado-de la Rosa DM, Macanás-Martínez A, Mares-García E, Carbonell-Torregrosa MdlÁ, Gil-Guillén VF, Cardona-Llorens A, Marhuenda-Amorós D. Development, and Internal, and External Validation of a Scoring System to Predict 30-Day Mortality after Having a Traffic Accident Traveling by Private Car or Van: An Analysis of 164,790 Subjects and 79,664 Accidents. International Journal of Environmental Research and Public Health. 2020; 17(24):9518. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17249518

Chicago/Turabian Style

Palazón-Bru, Antonio, María J. Prieto-Castelló, David M. Folgado-de la Rosa, Ana Macanás-Martínez, Emma Mares-García, María d.l.Á. Carbonell-Torregrosa, Vicente F. Gil-Guillén, Antonio Cardona-Llorens, and Dolores Marhuenda-Amorós. 2020. "Development, and Internal, and External Validation of a Scoring System to Predict 30-Day Mortality after Having a Traffic Accident Traveling by Private Car or Van: An Analysis of 164,790 Subjects and 79,664 Accidents" International Journal of Environmental Research and Public Health 17, no. 24: 9518. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17249518

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