Neuropsychological Outcome and Diffusion Tensor Imaging in Complicated versus Uncomplicated Mild Traumatic Brain Injury

This study examined whether intracranial neuroimaging abnormalities in those with mild traumatic brain injury (MTBI) (i.e., “complicated” MTBIs) are associated with worse subacute outcomes as measured by cognitive testing, symptom ratings, and/or diffusion tensor imaging (DTI). We hypothesized that (i) as a group, participants with complicated MTBIs would report greater symptoms and have worse neurocognitive outcomes than those with uncomplicated MTBI, and (ii) as a group, participants with complicated MTBIs would show more Diffusion Tensor Imaging (DTI) abnormalities. Participants were 62 adults with MTBIs (31 complicated and 31 uncomplicated) who completed neurocognitive testing, symptom ratings, and DTI on a 3T MRI scanner approximately 6-8 weeks post injury. There were no statistically significant differences between groups on symptom ratings or on a broad range of neuropsychological tests. When comparing the groups using tract-based spatial statistics for DTI, no significant difference was found for axial diffusivity or mean diffusivity. However, several brain regions demonstrated increased radial diffusivity (purported to measure myelin integrity), and decreased fractional anisotropy in the complicated group compared with the uncomplicated group. Finally, when we extended the DTI analysis, using a multivariate atlas based approach, to 32 orthopedic trauma controls (TC), the findings did not reveal significantly more areas of abnormal DTI signal in the complicated vs. uncomplicated groups, although both MTBI groups had a greater number of areas with increased radial diffusivity compared with the trauma controls. This study illustrates that macrostructural neuroimaging changes following MTBI are associated with measurable changes in DTI signal. Of note, however, the division of MTBI into complicated and uncomplicated subtypes did not predict worse clinical outcome at 6-8 weeks post injury

Predictors of poor health and functional recovery following road trauma: protocol of a British Columbian inception cohort study

Introduction Road trauma (RT) is a major public health problem affecting physical and mental health, and may result in prolonged absenteeism from work or study. It is important for healthcare providers to know which RT survivors are at risk of a poor outcome, and policy-makers should know the associated costs. Unfortunately, outcome after RT is poorly understood, especially for RT survivors who are treated and released from an emergency department (ED) without the need for hospital admission. Currently, there is almost no research on risk factors for a poor outcome among RT survivors. This study will use current Canadian data to address these knowledge gaps.Methods and analysis We will follow an inception cohort of 1500 RT survivors (16 years and older) who visited a participating ED within 24 hours of the accident. Baseline interviews determine pre-existing health and functional status, and other potential risk factors for a poor outcome. Follow-up interviews at 2, 4, 6, and 12 months (key stages of recovery) use standardised health-related quality of life tools to determine physical and mental health outcome, functional recovery, and healthcare resource use and lost productivity costs.Ethics and dissemination The Road Trauma Outcome Study is approved by our institutional Research Ethics Board. This study aims to provide healthcare providers with knowledge on how quickly RT survivors recover from their injuries and who may be more likely to have a poor outcome. We anticipate that this information will be used to improve management of all road users following RT. Healthcare resource use and lost productivity costs will be collected to provide a better cost estimate of the effects of RT. This information can be used by policy-makers to make informed decisions on RT prevention programmes

Association of air quality during forest fire season with respiratory emergency department visits in Vancouver, British Columbia

Background: Climate change has been deemed the biggest global health threat of the 21st century. One consequence of climate change is the increasing frequency and severity of forest fires. Smoke from wildfires has the ability to negatively impact air quality over large distances. The aim of this study was to examine the association that air quality had on emergency department visits for cardiac, respiratory and psychiatric/behavioral health chief complaints during forest fire season in Vancouver, British Columbia. Methods: The study period was January 1, 2009 – December 31, 2019. Forest fire season was defined as April 1- September 30. Air quality (measured by PM2.5 in ug/m3) was obtained from the Vancouver International Airport (YVR) Air Quality station. Emergency department visit data (CEDIS triage complaint) was acquired from a regional emergency department database. A generalized linear mixed model with Poisson link function was used to determine the relative risk (as a percentage) for respiratory, cardiac and psychiatric/behavioral health CEDIS triage complaints associated with a 10 unit increase in PM2.5. Results: PM2.5 during forest fire season was significantly associated with emergency department visits for respiratory chief complaints. For every 10 ug/m3 increase in PM2.5, there was a 4.61% (95% CI: 3.07, 6.17) increase in relative risk of respiratory chief complaints presenting to emergency departments. No association was found between PM2.5 and cardiac or psychiatric/behavioral health chief complaints during forest fire season or non-forest fire season. During non-forest fire season, PM2.5 was found to be negatively associated with respiratory (-3.57, 95% CI: -5.44, -1.66) and cardiac chief complaints (-2.77, 95% CI: -4.16, -1.47). Conclusion: Our results indicate a probable association between air quality during forest fire season and emergency department visits for respiratory chief complaints. This provides further illustration of the widespread impact of climate change, and underscores the importance of efforts to address it

Driving Contraventions.

<p>This figure shows the number of driving contraventions issued per 1,000 licensed drivers according to police patrol. The cross hatched areas represent sparsely populated patrols where the rates may be unstable.</p

Winter Temperature.

<p>This figure shows variation in winter temperatures across BC’s police patrols.</p

Relationship between crash type and explanatory factors.

<p>This figure uses vertical bars to show the association between predictive factors and crash outcomes. The shade correlates with unadjusted p values (deeper shade = smaller p values), solid outlines indicate relationships that remain significant after correction for multiple comparisons (Bonferroni). The height of the bars indicate the percentage change in crash events per unit change in predictive factor, where one unit is the interquartile range for that factor.</p