Related Experiment Video
Updated: Aug 16, 2026
A Test Bed to Examine Helmet Fit and Retention and Biomechanical Measures of Head and Neck Injury in Simulated Impact
Published on: September 21, 2017
Electric bicycle versus conventional bicycle crashes: comparative analysis of injury patterns, severity, and the
D Bauer1, J P Maier2, L Holzfurtner2
1Department of Orthopedics and Trauma Surgery, Faculty of Medicine, Medical Centre - Albert-Ludwig's- University of Freiburg, Albert-Ludwig's-University of Freiburg, Freiburg, Germany. david.bauer@uniklinik-freiburg.de.
Purpose:
E-bike trauma is often presumed to result in greater injury severity than conventional cycling, yet evidence remains inconsistent. Furthermore, the impact of factors such as Body Mass Index (BMI) on injury patterns is poorly understood. This study therefore evaluated whether e-bike trauma is associated with increased overall severity or distinct regional injury patterns.
Methods:
This retrospective single-center cohort study analyzed 261 adult trauma-bay patients (e-bike n = 37; conventional bicycle n = 224). Primary endpoints included Injury Severity Score (ISS) and regional maximum Abbreviated Injury Scale (AIS) scores. Secondary endpoints included physiological burden (SAPS II) and resource utilization (LOS, TISS-10). Multivariate logistic regression was used to identify independent predictors of intracranial hemorrhage, e-bike riding and extremity fractures. Event counts and events-per-variable (EPV) ratios are reported for each model.
Results:
E-bike riders had a significantly higher BMI than conventional cyclists (26.1 vs. 24.6 kg/m²; p = 0.029). However, the absolute difference of approximately 1.5 kg/m² is modest, and both group medians fall within the normal-to-overweight range. No statistically significant differences were observed in ISS, physiological burden, or resource utilization. Conventional cyclists had a higher proportion of patients with AIS Pelvis/Extremities ≥ 3 (14.3% vs. 5.4%; p = 0.045). In the multivariate binary logistic regression models, ISS (OR 1.042; 95% CI 1.014-1.071; p = 0.003) and BMI (OR 0.901; 95% CI 0.840-0.967; p = 0.004) were independent predictors of extremity fractures; age was not (OR 1.012; p = 0.134). Age was the only independent predictor of intracranial hemorrhage (ICH) (OR 1.033; 95% CI 1.017-1.050; p < 0.001). BMI was the only independent predictor of e-bike riding (OR 1.130; 95% CI 1.037-1.230; p = 0.005).
Conclusion:
In this selected cohort of trauma-bay patients, e-bike-related injuries showed no statistically significant difference in overall injury severity or treatment burden compared to conventional cycling injuries. Rather than being inherent to the bicycle type, injury patterns appear driven by overall trauma severity (ISS) and patient age, while higher BMI independently predicts both e-bike riding (demographic self-selection) and a reduced risk of extremity fractures. Larger prospective studies are required however, before conclusions regarding comparative e-bike injury risk can be further drawn.