An article published Online First and in a future edition of The Lancet reports that using validated prediction rules to identify children at very low risk of clinically-important traumatic brain injuries (ciTBIs) can reduce the need for CT scans. This can therefore diminish their resulting radiation exposure. The article is the work of Prof Nathan Kuppermann, Departments of Emergency Medicine and Pediatrics, University of California, Davis Medical Center, Sacramento, CA, USA and colleagues from the PECARN investigators network.
Worldwide, traumatic brain injury is the principal cause of death and disability in children. Every year in the USA, head trauma in individuals under 18 years of age results in about 7,400 deaths, over 60,000 hospital admissions, and over 600,000 emergency department visits. The CT scan is a vital diagnostic tool. However it elevates future risk of radiation-induced cancer. The authors determined how to identify children at very low risk of ciTBI for whom CT might be both pointless and undesirable.
A total of 42,000 children were included in this study. A quarter was less than 2 years of age. The rest were aged between 2 to 18 years. When investigators want to create a prediction rule, they should do so on a large group of patients to get as precise a rule as possible. This group of patients is called a “derivation group” on which the prediction rule is “derived”. However, any group of patients has certain characteristics and modes of behaviour. This may cause the prediction rule derived on that group to only be accurate when applied to that unique group. The investigators should therefore then test the prediction rule derived on the “derivation group” on a new group of patients, called the “validation group” to assess the validity of the rule.
The prediction rules were created using a ‘derivation’ population, and then applied to see if they worked on a ‘validation’ population. CT scans were obtained on 35 percent of the children, ciTBIs occurred in 376 (1 percent) and 60 (0.1 percent) underwent neurosurgery.
In the validation population, the clinical characteristics used to predict that children younger than 2 years did not have a ciTBI were:
вЂў normal mental status
вЂў no scalp haematoma (swelling) except frontal
вЂў no loss of consciousness or loss of consciousness of less than five seconds
вЂў non-severe injury mechanism
вЂў no palpable skull fracture
вЂў acting normally according to the parents
This predicted with 100 percent accuracy for 1,176 patients younger than 2 years who did not have a ciTBI in the validation population. 24 percent of the CT-imaged children younger than 2 years were in this low-risk group.
The prediction rule to identify children 2 years and older who did not have ciTBI included these characteristics:
вЂў normal mental status
вЂў no loss of consciousness
вЂў no vomiting
вЂў non-severe injury mechanism
вЂў no signs of basilar skull fracture
вЂў no severe headache
This correctly predicted all but 2 out of 3,800 patients (99.95 percent) who did not have a ciTBI in the validation population. 20 percent of the CT-scanned patients 2 years and older were in this low-risk group. Therefore, the results showed that, using these prediction rules for children presenting with head trauma, 1 in 4 children younger than 2 years and 1 in 5 older than 2 years who would likely have had CT scans without prediction rules could avoid these CT scans and their accompanying radiation exposure when the rules are applied.
The authors write in conclusion: “In this study of more than 42 000 children with minor blunt head trauma, we derived and validated highly accurate prediction rules for children at very low risk of ciTBIs for whom CT scans should be avoided. Application of these rules could limit CT use, protecting children from unnecessary radiation risks. Furthermore, these rules provide the necessary data to assist clinicians and families in CT decision making after head trauma.”
In an associated note, Dr Patricia C. Parkin, Hospital for Sick Children, University of Toronto Faculty of Medicine, Canada, and Dr Jonathon L. Maguire, Hospital for Sick Children, University of Toronto Faculty of Medicine, Canada, and Li Ka Shing, Knowledge Institute of St Michael’s Hospital, Toronto, Canada, remark: “Decision aids might provide structured presentations of options and outcomes, and many decisions, even in acute care settings, are sensitive to patients’ values and preferences…Perhaps as this field moves forward to assessment of the effect of the rules on physicians’ behaviour and clinical outcomes (impact analysis), clinicians and investigators might consider involving patients in the decision-making process. Then, when asking the question ‘should my head-injured child have a CT scan?, parents can weigh the probability of a clinically important traumatic brain injury with the probability of harm from ionising radiation from the CT scan.”
“Identification of children at very low risk of clinically-important brain injuries after head trauma: a prospective cohort study”
Nathan Kuppermann, James F Holmes, Peter S Dayan, John D Hoyle, Jr, Shireen M Atabaki, Richard Holubkov, Frances M Nadel, David Monroe, Rachel M Stanley, Dominic A Borgialli, Mohamed K Badawy, Jeff E Schunk, Kimberly S Quayle, Prashant Mahajan, Richard Lichenstein, Kathleen A Lillis, Michael G Tunik, Elizabeth S Jacobs, James M Callahan, Marc H Gorelick, Todd F Glass, Lois K Lee, Michael C Bachman, Arthur Cooper, Elizabeth C Powell, Michael J Gerardi, Kraig A Melville, J Paul Muizelaar, David H Wisner, Sally Jo Zuspan, J Michael Dean, Sandra L Wootton-Gorges, for the Pediatric Emergency Care Applied Research Network (PECARN)
Stephanie Brunner (B.A.)