Background Electric scooters are personal mobility devices that have risen in popularity worldwide since 2017. Emerging reports suggest that both riders and other road users, such as pedestrians and cyclists, have been injured in electric scooter-associated incidents. We undertook a scoping review of the current literature to evaluate the injury patterns and circumstances of electric scooter-associated injuries. Methods A scoping review of literature published from 2010 to 2020 was undertaken following accepted guidelines. Relevant articles were identified in Medline, Embase, SafetyLit and Transport Research International Documentation using terms related to electric scooters, injuries and incident circumstances. Supplemental searches were conducted to identify relevant grey literature (non-peer-reviewed reports). Results Twenty-eight peer-reviewed studies and nine grey literature records were included in the review. The current literature surrounding electric scooter-associated injuries mainly comprises retrospective case series reporting clinical variables. Factors relating to injury circumstances are inconsistently reported. Findings suggest that the head, upper extremities and lower extremities are particularly vulnerable in electric scooter falls or collisions, while injuries to the chest and abdomen are less common. Injury severity was inconsistently reported, but most reported injuries were minor. Low rates of helmet use among electric scooter users were noted in several studies. Conclusion Electric scooters leave riders vulnerable to traumatic injuries of varying severity. Future work should prospectively collect standardised data that include information on the context of the injury event and key clinical variables. Research on interventions to prevent electric scooter injuries is also needed to address this growing area of concern.

Aim: We conducted a responsibility analysis to determine whether drivers injured in motor vehicle collisions who test positive for Δ‐9‐tetrahydrocannabinol (THC) or other drugs are more likely to have contributed to the crash than those who test negative. Design: Prospective case–control study. Setting: Trauma centres in British Columbia, Canada. Participants: Injured drivers who required blood tests for clinical purposes following a motor vehicle collision. Measurements: Excess whole blood remaining after clinical use was obtained and broad‐spectrum toxicology testing performed. The analysis quantified alcohol and THC and gave semiquantitative levels of other impairing drugs and medications. Police crash reports were analysed to determine which drivers contributed to the crash (responsible) and which were ‘innocently involved’ (non‐responsible). We used unconditional logistic regression to determine the likelihood (odds ratio: OR) of crash responsibility in drivers with 0 < THC < 2 ng/ml, 2 ng/ml ≤ THC < 5 ng/ml and THC ≥ 5 ng/ml (all versus THC = 0 ng/ml). Risk estimates were adjusted for age, sex and presence of other impairing substances. Findings: We obtained toxicology results on 3005 injured drivers and police reports on 2318. Alcohol was detected in 14.4% of drivers, THC in 8.3%, other drugs in 8.9% and sedating medications in 19.8%. There was no increased risk of crash responsibility in drivers with THC < 2 ng/ml or 2 ≤ THC < 5 ng/ml. In drivers with THC ≥ 5 ng/ml, the adjusted OR was 1.74 [95% confidence interval (CI) = 0.59–6.36; P = 0.35]. There was significantly increased risk of crash responsibility in drivers with blood alcohol concentration (BAC) ≥ 0.08% (OR = 6.00;95% CI = 3.87–9.75; P < 0.01), other recreational drugs detected (OR = 1.82;95% CI = 1.21–2.80; P < 0.01) or sedating medications detected (OR = 1.45; 95%CI = 1.11–1.91; P < 0.01). Conclusions: In this sample of non‐fatally injured motor vehicle drivers in British Columbia, Canada, there was no evidence of increased crash risk in drivers with Δ‐9‐tetrahydrocannabinol < 5 ng/ml and a statistically non‐significant increased risk of crash responsibility (odds ratio = 1.74) in drivers with Δ‐9‐tetrahydrocannabinol ≥ 5 ng/ml.

The effect of cannabis legalization in Canada (in October 2018) on the prevalence of injured drivers testing positive for tetrahydrocannabinol (THC) is unclear. We studied drivers treated after a motor vehicle collision in four British Columbia trauma centers, with data from January 2013 through March 2020. We included moderately injured drivers (those whose condition warranted blood tests as part of clinical assessment) for whom excess blood remained after clinical testing was complete. Blood was analyzed at the provincial toxicology center. The primary outcomes were a THC level greater than 0, a THC level of at least 2 ng per milliliter (Canadian legal limit), and a THC level of at least 5 ng per milliliter. The secondary outcomes were a THC level of at least 2.5 ng per milliliter plus a blood alcohol level of at least 0.05%; a blood alcohol level greater than 0; and a blood alcohol level of at least 0.08%. We calculated the prevalence of all outcomes before and after legalization. We obtained adjusted prevalence ratios using log-binomial regression to model the association between substance prevalence and legalization after adjustment for relevant covariates. During the study period, 4339 drivers (3550 before legalization and 789 after legalization) met the inclusion criteria. Before legalization, a THC level greater than 0 was detected in 9.2% of drivers, a THC level of at least 2 ng per milliliter in 3.8%, and a THC level of at least 5 ng per milliliter in 1.1%. After legalization, the values were 17.9%, 8.6%, and 3.5%, respectively. After legalization, there was an increased prevalence of drivers with a THC level greater than 0 (adjusted prevalence ratio, 1.33; 95% confidence interval [CI], 1.05 to 1.68), a THC level of at least 2 ng per milliliter (adjusted prevalence ratio, 2.29; 95% CI, 1.52 to 3.45), and a THC level of at least 5 ng per milliliter (adjusted prevalence ratio, 2.05; 95% CI, 1.00 to 4.18). The largest increases in a THC level of at least 2 ng per milliliter were among drivers 50 years of age or older (adjusted prevalence ratio, 5.18; 95% CI, 2.49 to 10.78) and among male drivers (adjusted prevalence ratio, 2.44; 95% CI, 1.60 to 3.74). There were no significant changes in the prevalence of drivers testing positive for alcohol. After cannabis legalization, the prevalence of moderately injured drivers with a THC level of at least 2 ng per milliliter in participating British Columbia trauma centers more than doubled. The increase was largest among older drivers and male drivers. (Funded by the Canadian Institutes of Health Research.)

The osmole gap is used routinely as a screening test for the presence of exogenous osmotically active substances, such as the toxic alcohols ethylene glycol and methanol, particularly when the ability to measure serum concentrations of the substances is not available. The objectives of this study were: 1) to measure the diagnostic accuracy of the osmole gap for screening for ethylene glycol and methanol exposure, and 2) to identify whether a recently proposed modification of the ethanol coefficient affects the diagnostic accuracy. Electronic laboratory records from two tertiary-care hospitals were searched to identify all patients for whom a serum ethylene glycol and methanol measurement was ordered between January 1, 1996 and March 31, 2002. Cases were eligible for analysis if serum sodium, blood urea nitrogen, glucose, ethanol, ethylene glycol, methanol, and osmolality were measured simultaneously. Serum molarity was calculated using the Smithline and Gardner equation and ethanol coefficients of 1 and 1.25 mOsm/mM. The diagnostic accuracy of the osmole gap was evaluated for identifying patients with toxic alcohol levels above the recommended threshold for antidotal therapy and hemodialysis using receiver-operator characteristic curves, likelihood ratios, and positive and negative predictive values. One hundred and thirty-one patients were included in the analysis, 20 of whom had ethylene glycol or methanol serum concentrations above the threshold for antidotal therapy. The use of an ethanol coefficient of 1.25 mOsm/mM yielded higher specificities and positive predictive values, without affecting sensitivity and negative predictive values. Employing an osmole gap threshold of 10 for the identification of patients requiring antidotal therapy resulted in a sensitivity of 0.9 and 0.85, and a specificity of 0.22 and 0. 5, with equations 1 and 2 respectively. The sensitivity increased to 1 for both equations for the identification of patients requiring dialysis. Table 1 Equations used to calculate the serum molarity prior to the calculation of the osmole gap. Equation Number Equation 1 Osm_c = 2 * Na (mEq/L) + BUN (mmol/L) + glucose (mmol/L) + ethanol (mmol/L) 2 Osm_c = 2 * Na (mEq/L) + BUN (mmol/L) + glucose (mmol/L) + 1.25 * ethanol (mmol/L) Equation 2 in effect inflates the ethanol concentration by 25% prior to calculating the osmole gap, as proposed by Purssell et al.[18] Osm_c = calculated molarity; Na = sodium; BUN = blood urea nitrogen To convert from SI units, use the following corrections: BUN/2.8 mg/dl, glucose/18.1 mg/dl, ethanol/0.217 mg/dl Table 2 Area under the curve (diagnostic index) for osmole gap to identify toxic alcohol exposure. Exposure Threshold AUC (95% CI) p value AUC₂ - AUC₁ (95% CI) p value ANTIDOTAL THERAPY Equation 1 0.736 (0.599, 0.873) < 0.001 0.049 (-0.001, 0.099) 0.057 Equation 2 0.785 (0.665, 0.905) < 0.001 HEMODIALYSIS Equation 1 0.827 (0.715, 0.939) < 0.001 0.043 (-0.001, 0.086) 0.056 Equation 2 0.870 (0.784, 0.956) < 0.001 AUC = area under the curve; SE = standard error; CI = confidence interval In this sample, an osmole gap threshold of 10 has a sensitivity and negative predictive value of 1 for identifying patients for whom hemodialysis is recommended, independent of the ethanol coefficient applied. In patients potentially requiring antidotal therapy, applying an ethanol coefficient of 1.25 resulted in a higher specificity and positive predictive value without compromising the sensitivity.

Objectives Determine the prevalence of drug use in injured drivers and identify associated demographic factors and crash characteristics. Design Prospective cross-sectional study. Setting Seven trauma centres in British Columbia, Canada (2010–2012). Participants Automobile drivers who had blood obtained within 6 h of a crash. Main outcome measures We analysed blood for cannabis, alcohol and other impairing drugs using liquid chromatography/mass spectrometry (LCMS). Results 1097 drivers met inclusion criteria. 60% were aged 20–50 years, 63.2% were male and 29.0% were admitted to hospital. We found alcohol in 17.8% (15.6% to 20.1%) of drivers. Cannabis was the second most common recreational drug: cannabis metabolites were present in 12.6% (10.7% to 14.7%) of drivers and we detected Δ-9-tetrahydrocannabinol (Δ-9-THC) in 7.3% (5.9% to 9.0%), indicating recent use. Males and drivers aged under 30 years were most likely to use cannabis. We detected cocaine in 2.8% (2.0% to 4.0%) of drivers and amphetamines in 1.2% (0.7% to 2.0%). We also found medications including benzodiazepines (4.0% (2.9% to 5.3%)), antidepressants (6.5% (5.2% to 8.1%)) and diphenhydramine (4.7% (3.5% to 6.2%)). Drivers aged over 50 years and those requiring hospital admission were most likely to have used medications. Overall, 40.1% (37.2% to 43.0%) of drivers tested positive for alcohol or at least one impairing drug and 12.7% (10.7% to 14.7%) tested positive for more than one substance. Conclusions Alcohol, cannabis and a broad range of other impairing drugs are commonly detected in injured drivers. Alcohol is well known to cause crashes, but further research is needed to determine the impact of other drug use, including drug–alcohol and drug–drug combinations, on crash risk. In particular, more work is needed to understand the role of medications in causing crashes to guide driver education programmes and improve public safety.

Widely varying crash circumstances have been reported for bicycling injuries, likely because of differing bicycling populations and environments. We used data from the Bicyclists’ Injuries and the Cycling Environment Study in Vancouver and Toronto, Canada, to describe the crash circumstances of people injured while cycling for utilitarian and leisure purposes. We examined the association of crash circumstances with route type. Adult cyclists injured and treated in a hospital emergency department described their crash circumstances. These were classified into major categories (collision vs. fall, motor vehicle involved vs. not) and subcategories. The distribution of circumstances was tallied for each of 14 route types defined in an earlier analysis. Ratios of observed vs. expected were tallied for each circumstance and route type combination. Of 690 crashes, 683 could be characterized for this analysis. Most (74%) were collisions. Collisions included those with motor vehicles (34%), streetcar (tram) or train tracks (14%), other surface features (10%), infrastructure (10%), and pedestrians, cyclists, or animals (6%). The remainder of the crashes were falls (26%), many as a result of collision avoidance manoeuvres. Motor vehicles were involved directly or indirectly with 48% of crashes. Crash circumstances were distributed differently by route type, for example, collisions with motor vehicles, including “doorings”, were overrepresented on major streets with parked cars. Collisions involving streetcar tracks were overrepresented on major streets. Collisions involving infrastructure (curbs, posts, bollards, street furniture) were overrepresented on multiuse paths and bike paths. These data supplement our previous analyses of relative risks by route type by indicating the types of crashes that occur on each route type. This information can guide municipal engineers and planners towards improvements that would make cycling safer.