Sex-Specific Human, Agent, and Environment-Related Interactions in Traumatic Brain Injury: Utility of The Haddon Matrix

Abstract

<h3>Research Objectives</h3> To explore sex differences in the Host, the Agent, and the Environment utilizing computational analysis of traumatic brain injury (TBI) events. <h3>Design</h3> The retrospective population-based study utilized province-wide population-based decade-long health administrative data collected through the routine operation of the publicly funded health system in Ontario, Canada. <h3>Setting</h3> We used a previously established cohort of patients discharged between the fiscal years 2007/2008 and 2015/2016 from acute care and from the emergency department (ED) with diagnoses of TBI. <h3>Participants</h3> We drew upon health records of 235,003 unique patients (57% male) with TBI and the same number of reference patients without TBI, who were individually matched based on sex, age, place of residence, and income level, to organize factors associated with the TBI event. We dissected complex and multidimensional TBI event data by exploiting data mining and information visualization methods in male and female patients separately. We adopted concepts of the Haddon Matrix (Human, Agent, Environment) to organize injury event factors and compare TBI events of male and female patients. <h3>Interventions</h3> Not applicable. <h3>Main Outcome Measures</h3> Sex differences in the health status of the Host, the Agent, and the Environment at the TBI event phase. <h3>Results</h3> Based on perceived similarities, the computational technique detected 35 injury event-related factors, allowing observation of a set of definable patterns within the Host, the Agent, and the Environment. We uncovered significant sex-based differences in Host, Agent, and Environment patterns. We found that the Host's health status is of great importance to injury severity, and the Agent and the Environment have implications for external causes of injury. <h3>Conclusions</h3> Study findings support the utility of computational data mining in examining patterns of information within the TBI event. <h3>Author(s) Disclosures</h3> Eunice Kennedy Shriver National Institute of Child Health & Human Development of the National Institutes of Health (NIH) under Award Number R21HD089106 and the National Institute Of Neurological Disorders And Stroke of the NIH under Award Number R01NS117921 and partially by Canada Research Chair Programs.