title: Comparing CATCH, CHALICE and PECARN clinical decision rules for paediatric head injuries.
abstract: Many children present to emergency departments following head injury (HI), with a small number at risk of avoidable poor outcome. Difficulty identifying such children, coupled with increased availability of cranial CT, has led to variation in practice and increased CT rates. Clinical decision rules (CDRs) have been derived for paediatric HI but there is no published comparison to assist in deciding which to implement. The content of the three of highest quality and accuracy are described and compared. Systematic reviews of paediatric HI CDRs were published in 2009 and 2011. To identify CDRs published since the most recent review, key databases were searched, selecting studies which included CDRs involving children aged 0-18 years with a history of HI. Quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies Tool, and performance evaluated by reported accuracy. Three high quality CDRs were identified: CATCH (Canadian Assessment of Tomography for Childhood Head Injury) CHALICE (Children's Head Injury Algorithm for the Prediction of Important Clinical Events) and PECARN (Paediatric Emergency Care Applied Research Network). All were derived with high methodological standards but differed in key areas, including study population, outcomes and severity of HI. Each stated different predictor variables and only PECARN provided a separate algorithm for young children. CATCH and CHALICE identify children requiring CT and PECARN those who do not. All perform with high sensitivity and low specificity. PECARN is the only validated CDR, and none has undergone impact analysis. These three CDRs should undergo validation and comparison in a single population, with analysis of their impact on practice and financial implications, to aid relevant bodies in deciding which to implement.
authors.affiliation: Emergency Department, Royal Children's Hospital, Melbourne, Australia. mark.lyttle@uhbristol.nhs.uk
authors.forename: Mark D
authors.initials: MD
authors.lastname: Lyttle
authors.forename: Louise
authors.initials: L
authors.lastname: Crowe
authors.forename: Ed
authors.initials: E
authors.lastname: Oakley
authors.forename: Joel
authors.initials: J
authors.lastname: Dunning
authors.forename: Franz E
authors.initials: FE
authors.lastname: Babl
mesh_terms: D000465:Algorithms; D002648:Child; D002675:Child, Preschool; D006259:Craniocerebral Trauma / Q000000981:diagnostic imaging* / Q000453:epidemiology; D003661:Decision Support Techniques; D015600:Glasgow Coma Scale; D006801:Humans; D015994:Incidence; D007223:Infant; D007231:Infant, Newborn; D011237:Predictive Value of Tests; D014057:Tomography, X-Ray Computed / Q000706:statistics & numerical data*