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Archives of Disease in Childhood 2006;91:885-891; doi:10.1136/adc.2005.083980
Copyright © 2006 BMJ Publishing Group Ltd & Royal College of Paediatrics and Child Health.

ORIGINAL ARTICLE

Derivation of the children’s head injury algorithm for the prediction of important clinical events decision rule for head injury in children

J Dunning1, J Patrick Daly2, J-P Lomas1, F Lecky3, J Batchelor1, K Mackway-Jones1 on behalf of the children’s head injury algorithm for the prediction of important clinical events (CHALICE) study group

1 Emergency Medicine Research Group (EMERGE), Emergency Department, Manchester Royal Infirmary, Manchester, UK
2 Manchester Computing, University of Manchester, Manchester
3 Emergency Department, Hope Hospital, Manchester

Correspondence to:
Correspondence to:
J Dunning
Emergency Medicine Research Group, Emergency Department, Manchester Royal Infirmary, Oxford Road, Manchester M13 9WL, UK; joeldunning{at}doctors.org.uk

Background: A quarter of all patients presenting to emergency departments are children. Although there are several large, well-conducted studies on adults enabling accurate selection of patients with head injury at high risk for computed tomography scanning, no such study has derived a rule for children.

Aim: To conduct a prospective multicentre diagnostic cohort study to provide a rule for selection of high-risk children with head injury for computed tomography scanning.

Design: All children presenting to the emergency departments of 10 hospitals in the northwest of England with any severity of head injury were recruited. A tailor-made proforma was used to collect data on around 40 clinical variables for each child. These variables were defined from a literature review, and a pilot study was conducted before the children’s head injury algorithm for the prediction of important clinical events (CHALICE) study. All children who had a clinically significant head injury (death, need for neurosurgical intervention or abnormality on a computed tomography scan) were identified. Recursive partitioning was used to create a highly sensitive rule for the prediction of significant intracranial pathology.

Results: 22 772 children were recruited over 21/2; years. 65% of these were boys and 56% were <5 years old. 281 children showed an abnormality on the computed tomography scan, 137 had a neurosurgical operation and 15 died. The CHALICE rule was derived with a sensitivity of 98% (95% confidence interval (CI) 96% to 100%) and a specificity of 87% (95% CI 86% to 87%) for the prediction of clinically significant head injury, and requires a computed tomography scan rate of 14%.

Conclusion: A highly sensitive clinical decision rule is derived for the identification of children who should undergo computed tomography scanning after head injury. This rule has the potential to improve and standardise the care of children presenting with head injuries. Validation of this rule in new cohorts of patients should now be undertaken.

Abbreviations: CHALICE, children’s head injury algorithm for the prediction of important clinical events; LOC, loss of consciousness; RCS, Royal College of Surgeons; SXR, skull radiograph


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