MOTORCYCLE HELMET USE AND FATALITIES IN THE SOUTHEAST REGION OF THE USA

Introduction: The federal government estimates that per mile traveled in 2018, the number of deaths on motorcycles was nearly 27 times the number in cars. In the United States there is no universal helmet law. In twenty-two states, motorcycle helmets are entirely optional, while in nineteen states and the District of Columbia universal motorcycle helmets laws requiring helmets for all riders regardless of age are implemented and nine states only require younger motorcycle riders to wear a helmet, with varying age limits. Objectives: The overall objectives of this study were to evaluate the following: (1) number of fatalities (with and without helmet use), (2) fatality rate per motorcycle registration, (3) fatality percentage with age, (4) percent fatality due to alcohol impairment, and (5) location of collision impact to the rider in two southern states (Mississippi and Alabama) where helmet laws are established compared with a southern state (Florida) that only requires riders less than 20 years of age to be helmeted. Methods: Data from 2015-2018 were obtained from the National Highway Transportation Safety Administration Reporting System (FARS) and supplemented with state related and CDC data. Results: In all three states, the most common collision was a front-end impact. Mississippi had the highest percentage of motorcycle fatalities even with >80% of riders helmeted when the fatal accident occurred, followed by Florida motorcyclist who are only 50% of the time helmeted. In all three southern states similar percentage of fatalities were seen in each age group with higher fatalities associated with age range of 30-39 years. Conclusions: Variables such as helmet type, distance from a level 1 trauma center, poor roads, weather conditions, and visibility of the rider may also be factors that contribute to a higher incidence of fatality and need to be further investigated to improve motorcycle safety.

Use of Computerized Neurocognitive Assessment Software for the Detection of Alcohol Intoxication

Background: Acute ingestion of alcohol impairs cognitive function and poses significant threat to public health and safety with impaired operation of motor vehicles. However, there is a lack of access to tools to assess one's cognitive impairment due to alcohol. The purpose of this study was to explore the use of a neuropsychological assessment software, BrainCheck, to assess levels of alcohol impairment based on performance on the neuropsychological assessments. Methods: We administered the BrainCheck battery to 91 volunteer participants. Participants were required to take a baseline battery prior to any alcohol ingestion, and another testing battery after a voluntary drinking period. Blood alcohol concentration (BAC) for the participant was obtained using a breathalyzer. We performed statistical analysis comparing alcohol vs. non-alcohol performance on the BrainCheck battery, and used significant metrics of these assessments to generate predictive models. Results: Statistical analyses were performed comparing participants performance on the BrainCheck battery before and after alcohol consumption. Comparison was also done comparing performance between an intoxicated group with a BAC > 0.05, and a sober group with a BAC ≤ 0.05. Two assessment metrics were found to be significant among comparison groups after P-value correction, and four test metrics were observed to moderately correlate (|r| > 0.40) with BAC levels. Three linear regression models (least-squares, ridge and LASSO) were built to predict participant BAC levels, with the best performing model being the least-squares model with a RMSE of 0.027. We also built a predictive logistic regression model to detect whether the participant is intoxicated or not, with 80.6% accuracy, 73.3% sensitivity, and 75.0% specificity. Discussion: The BrainCheck battery has potential to predict alcohol impairment, including participant BAC levels and if the participant is intoxicated or not. BrainCheck provides another option to assess an individual's cognitive impairment due to alcohol, with the utility of being portable and available on one's smartphone.

MP54: The prevalence and pattern of drugs detected in injured drivers in four Canadian provinces

Introduction: Many drugs, including cannabis and alcohol, cause impairment and contribute to motor vehicle collisions (MVCs). Policy makers require knowledge of the prevalence of drug use in crash-involved drivers, and types of drugs used in order to develop effective prevention programs. This issue is particularly relevant with the recent legalization of cannabis. We aim to study the prevalence of alcohol, cannabis, sedating medications, and other drugs in injured drivers from 4 Canadian Provinces. Methods: This prospective cohort study obtained excess clinical blood samples from consecutive injured drivers who attended a participating Canadian trauma centre following a MVC. Blood samples were analyzed using a broad spectrum toxicology screen capable of detecting cannabinoids, cocaine, amphetamines (including their major analogues), and opioids as well as psychotropic pharmaceuticals (including antihistamines, benzodiazepines, other hypnotics, and sedating antidepressants). Alcohol and cannabinoids were quantified. Health records were reviewed to extract demographic, medical, and MVC information using a standardized data collection tool. Results: This study has been collecting data in 4 trauma centres in British Columbia (BC) since 2011 and was launched in 2 trauma centres in Alberta (AB), 1 in Saskatchewan (SK), and 2 in Ontario (ON) in 2018. In preliminary results from BC (n = 2412), 8% of injured drivers tested positive for THC and 13% for alcohol. Preliminary results from other provinces (n = 301) suggest a regional variation in prevalence of drivers testing positive for THC (10% - 27%), alcohol (17% - 29%), and other drugs. By May 2018, an estimated 4500 cases from BC, 600 from AB, 150 from SK, and 650 from ON will have been analyzed. We will report the prevalence of positive tests for alcohol, THC, other recreational drugs, and sedating medications, pre and post cannabis legalization. The number of cases with alcohol and/or THC levels above Canadian per se limits will also be reported. Results will be reported according to province, driver sex, age, single vs. multi vehicle crashes, and requirement for hospital admission. Conclusion: This will be among the largest international datasets on drug use by injured drivers. Our findings will provide patterns of drug and alcohol impairment in 4 Canadian provinces pre and post cannabis legalization. The significance of these findings and implication for impaired driving policy and prevention programs in Canada will be discussed.