Multinomial Estimations of Predictive Risk Factors for Traumatic Brain Injuries

Vladimir Rubinshteyn; Vincent Giordano; Douglas Cohen; Johnathon LeBaron; Sujoy Menon; Christopher Demaree

doi:10.7759/cureus.37307

Multinomial Estimations of Predictive Risk Factors for Traumatic Brain Injuries

Cureus. 2023 Apr 8;15(4):e37307. doi: 10.7759/cureus.37307. eCollection 2023 Apr.

Authors

Vladimir Rubinshteyn¹, Vincent Giordano², Douglas Cohen³, Johnathon LeBaron⁴, Sujoy Menon⁵, Christopher Demaree⁶

Affiliations

¹ Trauma Surgery, Richmond University Medical Center, Staten Island, USA.
² Trauma Services, Richmond University Medical Center, Staten Island, USA.
³ Neurosurgery, Richmond University Medical Center, Staten Island, USA.
⁴ Emergency Medicine, Richmond University Medical Center, Staten Island, USA.
⁵ Radiology, Richmond University Medical Center, Staten Island, USA.
⁶ Trauma Surgery, State University of New York Downstate Health Sciences University, Brooklyn, USA.

Abstract

Introduction Traumatic brain injuries (TBIs) affect millions of patients each year, with more than 220,000 hospitalizations in 2019 and 64,000 deaths in 2020 alone. TBIs span a plethora of injuries including cerebral contusions and lacerations, axonal injuries, optic pathway disruptions, and skull fractures. Previous research has established that characteristics such as sex, mechanism of injury (MOI), and blood-thinning agents have some causal connections to a variety of cranial traumas. Methods This paper sought to analyze aggravating risk factors for various TBIs in the New York City borough of Staten Island. Data on eight predictive risk variables were collected at a level 1 trauma center from January 1, 2022, to December 31, 2022: MOI, seizure history, anticoagulant/antiplatelet therapy, alcoholism, age, biological sex, tested alcohol level, and body mass index (BMI). A multinomial logistic regression was estimated to generate risk ratios (RRs), and chi-squared tests were carried out to determine univariate associations. Results It was found that blood thinner use and sex were both significant predictors of various types of TBIs. Additionally, those not tested for alcohol, including pediatric patients, were less likely to suffer most forms of TBI, while BMI had a negligible relationship with any TBI class. The use of blood-thinning agents put patients at an increased risk of concussions (relative risk ratio [RRR]: 1.82; 95% confidence interval [CI]: 1.10-3.02) and undiagnosed intracranial injuries (RRR: 1.90; 95% CI: 1.08-3.34). Men were at higher risk of multiple cranial injuries than women (RRR: 3.62; 95% CI: 1.38-9.48), as well as physical traumas such as brain lacerations and hemorrhages (RRR: 2.81, 95% CI: 1.28-6.18). BMI was weakly correlated with undiagnosed cranial injuries (RRR: 1.04; 95% CI: 1.00-1.08) and slightly uncorrelated with physical traumas (RRR: 0.94; 95% CI: 0.88-1.00). Those not tested for alcohol were at far less risk of multiple TBIs (RRR: 0.08; 95% CI: 0.01-0.66), concussions (RRR: 0.27; 95% CI: 0.11-0.71), and physical brain traumas (RRR: 0.33; 95% CI: 0.13-0.84). No parameter exhibited any statistical significance with skull fractures. Conclusion Particular risk factors for TBIs include biological sex and blood thinner use. Injury prevention efforts should be based on the category of TBI, with a particular focus on blood thinner users becoming concussive post-trauma. Attention should also be paid to men who engage in risky behavior such as binge drinking and crime sustaining more than one brain trauma or isolated brain bleeds. Therefore, improved hospital outreach for fall precautions in nursing homes and targeted interventions for at-risk men are vital for future projects.

Keywords: injury mechanism; injury risk; major trauma; moderate/severe tbi; sex differences; traumatic brain injury.