- Tsze, Daniel;
- Kuppermann, Nathan;
- Casper, T;
- Barney, Bradley;
- Richer, Lawrence;
- Liberman, Danica;
- Okada, Pamela;
- Morris, Claudia;
- Myers, Sage;
- Soung, Jane;
- Mistry, Rakesh;
- Babcock, Lynn;
- Spencer, Sandra;
- Johnson, Michael;
- Klein, Eileen;
- Quayle, Kimberly;
- Steele, Dale;
- Cruz, Andrea;
- Rogers, Alexander;
- Thomas, Danny;
- Grupp-Phelan, Jacqueline;
- Johnson, Tiffani;
- Dayan, Peter
INTRODUCTION: Headache is a common chief complaint of children presenting to emergency departments (EDs). Approximately 0.5%-1% will have emergent intracranial abnormalities (EIAs) such as brain tumours or strokes. However, more than one-third undergo emergent neuroimaging in the ED, resulting in a large number of children unnecessarily exposed to radiation. The overuse of neuroimaging in children with headaches in the ED is driven by clinician concern for life-threatening EIAs and lack of clarity regarding which clinical characteristics accurately identify children with EIAs. The study objective is to derive and internally validate a stratification model that accurately identifies the risk of EIA in children with headaches based on clinically sensible and reliable variables. METHODS AND ANALYSIS: Prospective cohort study of 28 000 children with headaches presenting to any of 18 EDs in the Pediatric Emergency Care Applied Research Network (PECARN). We include children aged 2-17 years with a chief complaint of headache. We exclude children with a clear non-intracranial alternative diagnosis, fever, neuroimaging within previous year, neurological or developmental condition such that patient history or physical examination may be unreliable, Glasgow Coma Scale score<14, intoxication, known pregnancy, history of intracranial surgery, known structural abnormality of the brain, pre-existing condition predisposing to an intracranial abnormality or intracranial hypertension, head injury within 14 days or not speaking English or Spanish. Clinicians complete a standardised history and physical examination of all eligible patients. Primary outcome is the presence of an EIA as determined by neuroimaging or clinical follow-up. We will use binary recursive partitioning and multiple regression analyses to create and internally validate the risk stratification model. ETHICS AND DISSEMINATION: Ethics approval was obtained for all participating sites from the University of Utah single Institutional Review Board. A waiver of informed consent was granted for collection of ED data. Verbal consent is obtained for follow-up contact. Results will be disseminated through international conferences, peer-reviewed publications, and open-access materials.