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

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

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

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.

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

PUBLICATION TYPE: Research Support, N.I.H., Extr

Journal: The Journal of pediatrics

VOLUME: 153

Page Numbers: 466-72

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ISSN: 1097-6833

DAY: 2

MONTH: 06

YEAR: 2008

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

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LANGUAGE: eng

NlmUniqueID: 375410

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

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

Country: United States

AGENCY: United States NINDS

GRANT: 1 U01 NS 40069-01A2

ACRONYM: NS

MEDLINETA: J Pediatr

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