The Important Role for Physicians as Advocates for Firearm and Road Traffic Injury Prevention

The purpose of this article is to discuss the important role for physicians in advocating for the prevention of road traffic and firearm injuries. Physicians have shown to be effective advocates for a variety of injuries, and this needs to continue and be enhanced for these injury categories. Road traffic and firearm injuries are among the leading causes of death across the lifespan. The influence and credibility of physicians enhance the messages they provide in advocacy efforts. It is important that physicians educate and counsel patients in a variety of healthcare settings along with joining advocacy efforts of professional associations. Recommendations are provided for advocacy components related to these injuries. Also, it is very important that physicians receive training in medical school and/or residency about injuries and how to successfully advocate for evidence-based injury prevention strategies.

Mortality-Risk Prediction Model from Road-Traffic Injury in Drunk Drivers: Machine Learning Approach

Background: Alcohol-related road-traffic injury is the leading cause of premature death in middle- and lower-income countries, including Thailand. Applying machine-learning algorithms can improve the effectiveness of driver-impairment screening strategies by legal limits. Methods: Using 4794 RTI drivers from secondary cross-sectional data from the Thai Governmental Road Safety Evaluation project in 2002–2004, the machine-learning models (Gradient Boosting Classifier: GBC, Multi-Layers Perceptrons: MLP, Random Forest: RF, K-Nearest Neighbor: KNN) and a parsimonious logistic regression (Logit) were developed for predicting the mortality risk from road-traffic injury in drunk drivers. The predictors included alcohol concentration level in blood or breath, driver characteristics and environmental factors. Results: Of 4974 drivers in the derived dataset, 4365 (92%) were surviving drivers and 429 (8%) were dead drivers. The class imbalance was rebalanced by the Synthetic Minority Oversampling Technique (SMOTE) into a 1:1 ratio. All models obtained good-to-excellent discrimination performance. The AUC of GBC, RF, KNN, MLP, and Logit models were 0.95 (95% CI 0.90 to 1.00), 0.92 (95% CI 0.87 to 0.97), 0.86 (95% CI 0.83 to 0.89), 0.83 (95% CI 0.78 to 0.88), and 0.81 (95% CI 0.75 to 0.87), respectively. MLP and GBC also had a good model calibration, visualized by the calibration plot. Conclusions: Our machine-learning models can predict road-traffic mortality risk with good model discrimination and calibration. External validation using current data is recommended for future implementation.

State of pedestrian road safety in Uganda: a qualitative study of existing interventions

Background: Pedestrians in Uganda account for 40% of road traffic fatalities and 25% of serious injuries annually. We explored the current pedestrian road traffic injury interventions in Uganda to understand why pedestrian injuries and deaths continue despite the presence of interventions. Methods: We conducted a qualitative study that involved a desk review of road safety policy, regulatory documents, and reports. We supplemented the document review with 14 key informant interviews and 4 focus group discussions with par- ticipants involved in road safety. Qualitative thematic content analysis was done using ATLAS. ti 7 software. Results: Five thematic topics emerged. Specifically, Uganda had a Non-Motorized Transport Policy whose implementation revealed several gaps. The needs of pedestrians and contextual evidence were ignored in road systems. The key program- matic challenges in pedestrian road safety management included inadequate funding, lack of political support, and lack of stakeholder collaboration. There was no evidence of plans for monitoring and evaluation of the various pedestrian road safety interventions. Conclusion: The research revealed low prioritization of pedestrian needs in the design, implementation, and evaluation of pedestrian road safety interventions. Addressing Uganda’s pedestrian needs requires concerted efforts to coordinate all road safety activities, political commitment, and budgetary support at all levels. Keywords: Pedestrian; safety intervention; qualitative; Uganda.

Determinants of Prolonged Length of Stay among Patients with Road Traffic Injury at the Philippine General Hospital: A Retrospective Cohort Study

Introduction. Road traffic injuries are among the leading causes of preventable death, claiming around 7000 lives every year. Furthermore, road traffic can injure or disable thousands more every year in the Philippines. Objectives. This study determined the hospital length-of-stay patterns and risk factors for a prolonged length of stay in a tertiary hospital after road traffic injury. Methods. A retrospective cohort study was conducted to determine the determinants of the length of stay in the Philippine General Hospital (PGH) among road traffic injury victims for the year 2016. Length of stay was recorded according to the median. The other variables were cross-tabulated against the length of stay, and each of their crude odds ratios along with corresponding p-values were presented. Continuous variables were analyzed using Wilcoxon Mann-Whitney U-test. The predictor model for the determinants of prolonged length of stay in the hospital was built using forward selection. Likelihood-ratio test was used to compare the model with and without the exposure variable. Results. A total of 427 road traffic injury victims were admitted to the Philippine General Hospital in 2016. The mean age of the patients was 31.55 years (±14.97) with a median age of 29 years. The majority of patients were males (82.4%) and single (60.8%). Most patients were riding a motorcycle during the time of the accident (64.2%) while 20% were pedestrians. The majority of the victims were intoxicated (74.3%) and were not using helmets (57.1%) at the time of the accident. Most of the victims received first aid (69.2%) and the mean time of admission was 3.03 (±13.31) days while the median time to admission was 12 hours. Receiving first aid (p<0.01), availed services (p<0.01), and married civil status (p=0.04) were found to be strongly associated with length of hospital stay. Without controlling for any confounders, pay patients (OR = 3.46, 95% CI: 1.3, -9.87), elective patients (OR = 7.88, 95% CI: 2.64, 31.61), and those in non-trauma wards (OR=2.07, 95% CI: 1.29, 3.36) had higher odds for longer hospitalization stay. On the other hand, those who did not receive first aid (OR = 0.55, CI:0.35, 0.85) had lower odds for prolonged hospitalization. Those who suffered face injury and did not suffer external injuries had a higher mean rank, suggesting a longer length of hospital stay. On the other hand, upon controlling variables found to be associated with previous studies, those with low Glasgow coma scale (GCS) scores were 2.77 times (95% CI: 1.13, 6.91) more likely to stay longer in the hospital. Conclusion. The type of victim, mortality status, age, and sex were found to be important determinants of prolonged hospitalization. To lessen the number of fatalities and road trauma injuries, laws on road safety should be strictly and properly implemented. Shared responsibility of all road users is also important in improving the safe usage of roads.

Drinking and Night-Time Driving May Increase the Risk of Severe Health Outcomes: A 5-Year Retrospective Study of Traffic Injuries among International Travelers at a University Hospital Emergency Center in Thailand

Road traffic injury (RTI) is a leading cause of death in developing countries. This burden affects not only locals, but also international travelers. Data on international travelers with RTIs in Thailand, especially from a medical perspective, are limited. This study aimed to analyze the factors associated with severe health outcomes following RTIs among international travelers at a university hospital emergency center in Thailand from January 2015 to December 2019. The retrieved data consisted of demographics, risks, preventive factors, and health outcomes. The severity of outcome was classified as fatality, hospitalization, or non-severe. A multinomial logistic regression model was used to identify the possible determinants of severity of health outcome among international travelers with RTI. A total of 720 travelers with RTIs (69% males; 82.5% were Southeast Asian) were included, with a mean age of 28.5 years. Of these, 144 (20%) had severe health outcomes: 64 (9%) fatalities and 80 (11%) hospitalizations. The level of severity of outcome was not associated with travelers’ demographics, but was associated with conventional risk factors, i.e., motorcycle use, alcohol/drug use, night-time driving, and less use of seatbelt/helmet. In a multinomial logistic regression analysis, alcohol drinking (adjusted odds ratio (AOR) 2.53, 95% confidence interval (CI) 1.41–4.55) and night-time driving (AOR 2.54, 95% CI 1.36–4.75) were associated with hospitalization. Patients who had a history of tetanus vaccination were less likely to die (AOR 0.37, 95% CI 0.17–0.81). In conclusion, one-fifth of RTIs resulted in severe health outcomes, and 9% were fatal. Road safety campaigns in Thailand should target travelers of all nationalities. Interventions that enhance travelers’ safety practices and proper preparation for road accidents should be explored further.