The long-term objective of this study is to develop a highly accurate decision rule for the evaluation of children with blunt head trauma. This decision rule will identify all children with traumatic brain injury (TBI), yet also will result in less frequent use of computerized tomography (CT) scans in children with blunt head trauma evaluated in emergency departments (EDs).

The specific aims are to derive and internally validate a clinical decision rule which accurately and reliably identifies children at high risk and those at near-zero risk of TBI after blunt head trauma. TBI is the leading cause of death and disability in children older than one year. Some children with TBIs are initially unrecognized, leading to preventable morbidity. Although CT scanning is the gold standard for diagnosing TBI in head-injured children, and failure to diagnose TBI increases morbidity and mortality, overuse of CT scanning has important drawbacks. The most important among these is radiation exposure which may result in death from malignancy, estimated as 1 radiation-induced fatality per 2000-5000 pediatric cranial CT scans. Fewer than 10% of CT scans currently performed on children with head injury reveal TBI, thus CT scans are used inefficiently. 

The methods of our study will be a prospective, multicenter observational study of children with blunt head trauma evaluated in the 25 hospitals of the Pediatric Emergency Care Applied Research Network (PECARN) of the Maternal and Child Health Bureau.  These 25 hospitals evaluate more than 808,000 children of diverse geographic and racial/ethnic background in their EDs on an annual basis (of whom approximately 16,000 have blunt head trauma).  Children with blunt head trauma at these centers will be evaluated and enrolled into the study at time of presentation to the participating EDs over two years, and will be followed prospectively to detect the outcomes of interest: 1)TBI on CT scan and, 2) TBI in need of acute intervention (defined by the need for neurosurgery, endotracheal intubation for > 24 hours, or hospitalization for 2 or more nights).  The clinical data collected at the time of ED presentation will then be analyzed using binary recursive partitioning to generate a clinical decision rule(s) for the identification of children at high risk, and near-zero risk of TBI.  This rule will be tested in the PECARN network and widespread dissemination will result in more efficient, evidence-based evaluation of children with head trauma which in turn will decrease the frequency of CT use.