A decision rule for identifying children at low risk for brain injuries after blunt head trauma

Abstract

Study objective

Computed tomography (CT) is frequently used in evaluating children with blunt head trauma. Routine use of CT, however, has disadvantages. Therefore, we sought to derive a decision rule for identifying children at low risk for traumatic brain injuries.

Methods

We enrolled children with blunt head trauma at a pediatric trauma center in an observational cohort study between July 1998 and September 2001. We evaluated clinical predictors of traumatic brain injury on CT scan and traumatic brain injury requiring acute intervention, defined by a neurosurgical procedure, antiepileptic medications for more than 1 week, persistent neurologic deficits, or hospitalization for at least 2 nights. We performed recursive partitioning to create clinical decision rules.

Results

Two thousand forty-three children were enrolled, 1,271 (62%) underwent CT, 98 (7.7%; 95% confidence interval [CI] 6.3% to 9.3%) had traumatic brain injuries on CT scan, and 105 (5.1%; 95% CI 4.2% to 6.2%) had traumatic brain injuries requiring acute intervention. Abnormal mental status, clinical signs of skull fracture, history of vomiting, scalp hematoma (in children ≤2 years of age), or headache identified 97/98 (99%; 95% CI 94% to 100%) of those with traumatic brain injuries on CT scan and 105/105 (100%; 95% CI 97% to 100%) of those with traumatic brain injuries requiring acute intervention. Of the 304 (24%) children undergoing CT who had none of these predictors, only 1 (0.3%; 95% CI 0% to 1.8%) had traumatic brain injury on CT, and that patient was discharged from the ED without complications.

Conclusion

Important factors for identifying children at low risk for traumatic brain injuries after blunt head trauma included the absence of: abnormal mental status, clinical signs of skull fracture, a history of vomiting, scalp hematoma (in children ≤2 years of age), and headache.

Introduction

Trauma is the leading cause of childhood death.¹ Traumatic brain injury is the leading cause of death and disability caused by trauma in children,2, 3, 4 resulting in approximately 3,000 deaths, 50,000 hospitalizations, and 650,000 emergency department (ED) visits per year in the United States.5, 6 Cranial computed tomography (CT) is routinely used in the assessment of children evaluated in the ED with head trauma; however, less than 10% of these CT scans are diagnostic of traumatic brain injuries.7, 8, 9, 10

Some studies have proposed that clinical signs and symptoms may be used to identify children at low risk for traumatic brain injuries after blunt head trauma.7, 11 Others have concluded that clinical signs and symptoms are inadequate for identifying these children.9, 10, 12, 13, 14 Many studies, however, were limited by small size of the study populations, retrospective design, uncontrolled or univariable data analyses, and nonstandardized age inclusion criteria and outcome variable definition.

Although CT is the diagnostic test of choice for evaluating children with head trauma, this procedure has disadvantages, including exposure to ionizing radiation,15, 16, 17, 18 transport of the child away from the direct supervision of emergency physicians, the frequent requirement for pharmacologic sedation,19, 20, 21 additional health care costs, and increased time for completing ED evaluation. Therefore, CT scans should ideally be selectively used.

Because the results of previous studies are inconclusive, variation exists in physicians' practice patterns regarding the use of CT scans in the ED evaluation of children with blunt head trauma.22, 23 Published guidelines acknowledge the limitations of available data and highlight the need for larger, prospective studies on this topic.8, 24, 25, 26 In this study, we sought to derive a clinical decision rule with high sensitivity for traumatic brain injury and high negative predictive value for identifying children without traumatic brain injuries after blunt head trauma, with the goal of maximizing the clinical efficiency of CT use. We hypothesized that a set of clinical signs and symptoms can accurately identify individuals at very low risk of traumatic brain injuries.