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The Reconstructive Burden of E-Scooter Injuries: Risk Factors, Injury Patterns, and Surgical Implications From a
Nuh Evin1, Yusuf Sürücü2, Melih Kerem Sifil3
1Department of Plastic, Reconstructive and Aesthetic Surgery, Medical Park Hospital, Ordu, Turkey.
Introduction:
Electric scooter (e-scooter) use is popular, and there is an increase in related injuries. Our aim was to characterize facial injury patterns, surgical management, and modifiable risk factors.
Methods:
A retrospective case series was conducted, reviewing all e-scooter-related injury presentations between 2017 and 2025. Patients with life-threatening injuries were excluded. Data collected included demographics, details regarding the e-scooter use and accident, injury pattern, treatment modality, and hospitalization.
Results:
A total of 105 patients were included, who were predominantly male (81.9%) with a mean age of 20.5±5.1 years. Most patients used rental scooters (79%), and a minority of them used any protective equipment (14.3%), who are almost exclusively among private scooter owners. Substance use was documented in 23.8% of cases, confined entirely to rental users. Crashes peaked in summer (46.7%) and on weekends (54.3%), with evening hours accounting for 47.6% of all incidents. Night-hour crashes represented a high-risk convergence: all were rental users, none wore protective equipment, 70% involved substance use, and the surgical intervention rate was 30%. Facial injuries predominated; 41% of patients required procedural intervention. A composite risk score incorporating substance use, absence of protective equipment, and illegal speed (>25 km/h) demonstrated a clear dose-response relationship with surgical outcomes.
Conclusions:
E-scooter use poses a significant reconstructive burden, particularly among young male rental users riding without protective equipment. The convergence of substance use, helmet non-compliance, and illegal speeds in specific temporal windows identifies high-yield targets for regulatory intervention. Plastic surgeons represent an underutilized resource in e-scooter injury surveillance and prevention.
