Predicting Complicated Mild Traumatic Brain Injury in Adolescent Trauma to Enhance Clinical Decisions in Imaging.

Abstract

Background: The Pediatric Emergency Care Applied Research Network (PECARN) traumatic brain injury algorithm is used to identify children at low risk of clinically significant traumatic brain injuries to reduce computed tomography (CT) exposure. Adapting PECARN rules based on population-specific risk stratification has been suggested to improve diagnostic accuracy.

Objective: This study sought to identify center-specific patient variables, beyond PECARN rules, that may enhance the identification of patients requiring neuroimaging.

Methods: This single-center, retrospective cohort study was conducted from July 1, 2016, to July 1, 2020, in a Southwestern U.S. Level II pediatric trauma center. The inclusion criteria were adolescents (10-15 years), Glasgow Coma Scale (13-15), with a confirmed mechanical blow to the head. Patients without a head CT were excluded. Logistic regression was performed to identify additional complicated mild traumatic brain injury predictor variables beyond the PECARN.

Results: There were 136 patients studied; 21 (15%) presented with a complicated mild traumatic brain injury. Relative to motorcycle collision or all-terrain vehicle trauma (odds ratio [OR] 211.75, 95% confidence interval, CI [4.51, 9931.41], p < .001), an unspecified mechanism (OR 42.0, 95% CI [1.30, 1350.97], p = .03) and consult activation (OR 17.44, 95% CI [1.75, 173.31], p = .01) were significantly associated with complicated mild traumatic brain injury.

Conclusions: We identified additional factors associated with complex mild traumatic brain injury, including motorcycle collision and all-terrain vehicle trauma, unspecified mechanism, and consult activation that are not in the PECARN imaging decision rule. Adding these variables may aid in determining the need for appropriate CT scanning.