| Literature DB >> 35727343 |
Eyal Gan-El1, William Ngatchou Djomo2, Andreea Monica Pascu Ciobanu2, Leonard Kaufman3, Francis Ndé Djiélé4, Maarten Ulrix2, Bernard Kreps2, Alain Plumacker2, Stefano Malinverni2, Magali Bartiaux2, Pierre Youatou Towo2.
Abstract
PURPOSE: This study aimed to describe the demographic and clinical characteristics of individuals involved in electric scooter (E-scooter) accidents and the factors associated with these incidents.Entities:
Keywords: E-scooters; Electric scooter injury; Emergency medicine; Micro-mobility; Trauma
Year: 2022 PMID: 35727343 PMCID: PMC9211049 DOI: 10.1007/s00068-022-02019-5
Source DB: PubMed Journal: Eur J Trauma Emerg Surg ISSN: 1863-9933 Impact factor: 2.374
Description of cohort: patient and accident characteristics associated with e-scooters
| Characteristics | 95% CI | Mean | Median | Std deviation | |
|---|---|---|---|---|---|
| Gender (man) | 116 (68.2%) | 60.4–74.6 | |||
| Age* | 32.33 | 29.48 (95% CI: 24.15–40.0) | 11.134 | ||
| Hour of admission* | |||||
| 7am–6 pm | 72 (42.6%) | 35.5–50.3 | |||
| 6 pm–11 pm | 46 (27.2%) | 20.1–34.9 | |||
| 11 pm–7am | 51 (30.2%) | 23.1–37.3 | |||
| Rented | 125 (73.5%) | 66.9–80.5 | |||
| Arrived by ambulance | 68 (40.0%) | 32.5–46.7% | |||
| Helmet usage | 11 (6.4%) | 3.0–10.1 | |||
| Alcohol consumption | 51 (30.0%) | 23.7–37.9 | |||
| Mechanism of the accident** | |||||
| Loss of balance | 142 (84.5%) | 77.5–88.8 | |||
| Two drivers on the e-scooter | 11 (6.5%) | 3.0–11.0 | |||
| Pedestrians hit by the e-scooter | 7 (4.1%) | 1.2–7.7 | |||
| Accident with another vehicle | 9 (5.3%) | 2.4–8.9 | |||
| Scanner in ER | 24 (14.1%) | 8.9–19.5 | |||
| ICU | 1 (< 1%) | ||||
| Temporary incapacity for work | 71 (41.7%, 1193 days in total) | 16.8 | 7.0 (95% CI: 3–21) | 20.08 | |
| Hospitalization | 20 (11.7%) | 7.1–16.5 | |||
*1 patient with missing data
**2 patients with missing data
Fig. 1Age distribution
Fig. 2Distributions of admissions based on time periods
Traumatic injury description
| Characteristics | Number % of the total | Number (%) in the subgroup | Total subgroup |
|---|---|---|---|
| Region of the body | |||
| Limbs | 103/170 (60.6%) | ||
| Upper limb | 34.1% | 58 (56.3%) | 103 |
| Lower limb | 31.2% | 53 (51.4%) | 103 |
| Both limbs | 8 (7.7%) | 103 | |
| Thorax | 9 (5.3%) | ||
| Head and neck | 78/170 (45.9%) | ||
| Cranial trauma | 11.8% | 20 (25.6%) | 78 |
| Maxilofacial trauma | 40.0% | 68 (87.2%) | 78 |
| Contusions and abrasions | 63/170 (37.1%) | ||
| Upper limb | 29 (46.0%) | 63 | |
| Lower limb | 24 (38.1%) | 63 | |
| Thorax | 6 (9.5%) | 63 | |
| Head and neck injuries | 29 (46.0%) | 63 | |
| Fractures | 45/170 (26.5%) | ||
| Upper limb | 20 (44.4%) | 45 | |
| Lower limb | 13 (28.9%) | 45 | |
| Thorax | 3 (6.7%) | 45 | |
| Head and neck | 14 (31.1%) | 45 | |
| Multiple fractures | 5 (11.1%) | 45 | |
| Sutures | 56/170 (32.9%) | ||
| Upper limb | 7 (12.5%) | 56 | |
| Lower limb | 11 (19.6%) | 56 | |
| Head and neck | 46 (82.1%) | 56 | |
| Sprain | 16/170 (9.4%) | ||
| Dislocation | 8/170 (4.7%) | ||
| Upper limb | 7 (87.5%) | ||
| Lower limb | 1 (12.5%) | ||
| Head and neck | 1 (12.5%) | ||
| Surgery | 23/170 (13.5%) | ||
| Upper limb | 8 (34.8%) | 23 | |
| Lower limb | 8 (34.8%) | 23 | |
| Thorax | 0 (0.0%) | 23 | |
| Head and neck | 9 (39.1%) | 23 | |
Risk factors and outcomes by personal and trip characteristics
| (a) Helmet usage | Use of helmet | No helmet | |
|---|---|---|---|
| Head and neck injuries | 2 (18.2%) | 76 (47.8%) | Fisher’s exact test |
| Cranial trauma | 0 (0.0%) | 20 (12.6%) | Fisher’s exact test |
| Maxillofacial trauma | 2 (18.2%) | 66 (41.5%) | Fisher’s exact test |
Risk factors for the occurrence of accidents during off-working hours (forward stepwise)
| Odds ratio | 95% CI | ||
|---|---|---|---|
| Helmet | 0.10 | 0.12–0.809 | |
| Alcohol | 4.67 | 2.07–10.54 |
Fig. 3Distribution of accidents by month