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Evaluation of Trauma Severity Scores in Electric Scooter Related Injuries

Year: 2025
Type: article
Study design: Observational Study
Abstract: Aim: Our study aimed to identify injuries related to electric scooters (e-scooters) in the emergency department (ED) and to compare trauma severity scores. Materials and Methods: This prospective, single-center study was conducted during the 3-month summer period between June 1 and August 31, 2023, on adult and pediatric patients who presented to the ED with e-scooter-related injuries. ROC analyses were performed for the injury severity score (ISS), revised trauma score (RTS), and trauma and injury severity score (TRISS). Results: A total of 106 patients were included, with a mean age of 21.5 years (interquartile range: 15–39.5), and 69.8% (n=74) were male. The three most commonly injured areas in patients admitted to the ED with e-scooter injuries were the head (50.9%, n=54), knee (34.9%, n=37), and forearm-elbow (26.4%, n=28). The median ISS of patients admitted to the intensive care unit was higher than that of patients admitted to the ward or discharged (NISS: 18 vs. 2), whereas the median RTS and TRISS values were lower (RTS: 7.64 vs. 7.84; TRISS: 4.39 vs. 5.72). The median ISS of deceased patients was higher than that of surviving patients (ISS: 29 vs. 2), while the RTS and TRISS values were lower (RTS: 7.11 vs. 7.84; TRISS: 3.48 vs. 5.72). The TRISS (area under the curve =0.991) had the highest discriminatory ability in predicting mortality (p<0.001). When the TRISS was ≤4.47, the sensitivity for predicting mortality was 100%, specificity 96.97%, positive predictive value 70%, negative predictive value 100%, positive likelihood ratio 33, and negative likelihood ratio 0.0. Conclusion: E-scooter-related injuries were common among young people and males. The most frequent injury sites were the head, knee, and forearm–elbow region. The TRISS was the most successful score in predicting mortality in e-scooter-related injuries.
DOI: 10.4274/eajem.galenos.2025.56244
Language: English
Field: Medicine
Open Access status: diamond
OpenAlex ID: W4416166918
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