Stratification of risk for emergent intracranial abnormalities in children with headaches: a Pediatric Emergency Care Applied Research Network (PECARN) study protocol. BMJ Open 2023 Nov 22;13(11):e079040
Date
11/23/2023Pubmed ID
37993148Pubmed Central ID
PMC10668138DOI
10.1136/bmjopen-2023-079040Scopus ID
2-s2.0-85177837213 (requires institutional sign-in at Scopus site)Abstract
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.
Author List
Tsze DS, Kuppermann N, Casper TC, Barney BJ, Richer LP, Liberman DB, Okada PJ, Morris CR, Myers SR, Soung JK, Mistry RD, Babcock L, Spencer SP, Johnson MD, Klein EJ, Quayle KS, Steele DW, Cruz AT, Rogers AJ, Thomas DG, Grupp-Phelan JM, Johnson TJ, Dayan PS, Pediatric Emergency Care Applied Research Network (PECARN)Author
Danny G. Thomas MD, MPH Professor in the Pediatrics department at Medical College of WisconsinMESH terms used to index this publication - Major topics in bold
ChildCraniocerebral Trauma
Emergency Service, Hospital
Emergency Treatment
Female
Headache
Humans
Pregnancy
Prospective Studies
