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J Pediatr. 2008 Oct;153(4):466-72. doi: 10.1016/j.jpeds.2008.04.013. Epub 2008 Jun 2.

An algorithm for identifying and classifying cerebral palsy in young children.

Author information

  • 1Division of Pediatric Neurology, Department of Pediatrics, Boston Medical Center, Boston University, Boston, MA, USA. karl.kuban@bmc.org

Abstract

OBJECTIVE:

To develop an algorithm on the basis of data obtained with a reliable, standardized neurological examination and report the prevalence of cerebral palsy (CP) subtypes (diparesis, hemiparesis, and quadriparesis) in a cohort of 2-year-old children born before 28 weeks gestation.

STUDY DESIGN:

We compared children with CP subtypes on extent of handicap and frequency of microcephaly, cognitive impairment, and screening positive for autism.

RESULTS:

Of the 1056 children examined, 11.4% (120) were given an algorithm-based classification of CP. Of these children, 31% had diparesis, 17% had hemiparesis, and 52% had quadriparesis. Children with quadriparesis were 9 times more likely than children with diparesis (76% versus 8%) to be more highly impaired and 5 times more likely than children with diparesis to be microcephalic (43% versus 8%). They were more than twice as likely as children with diparesis to have a score <70 on the mental scale of the BSID-II (75% versus 34%) and had the highest rate of the Modified Checklist for Autism in Toddlers positivity (76%) compared with children with diparesis (30%) and children without CP (18%).

CONCLUSION:

We developed an algorithm that classifies CP subtypes, which should permit comparison among studies. Extent of gross motor dysfunction and rates of co-morbidities are highest in children with quadriparesis and lowest in children with diparesis.

Comment in

PMID:
18534210
[PubMed - indexed for MEDLINE]
PMCID:
PMC2581842
Free PMC Article

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