A systematic review of tests to predict cerebral palsy in young children

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Bosanquet, Margot
Copeland, Lisa
Ware, Robert
Boyd, Roslyn
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2013
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Abstract

Aim: This systematic review evaluates the accuracy of predictive assessments and investigations used to assist in the diagnosis of cerebral palsy (CP) in preschool-age children (<5y). Method: Six databases were searched for studies that included a diagnosis of CP validated after 2 years of age. The validity of the studies meeting the criteria was evaluated using the Standards for Reporting Diagnostic Accuracy criteria. Where possible, results were pooled and a meta-analysis was undertaken. Results: Nineteen out of 351 studies met the full inclusion criteria, including studies of general movements assessment (GMA), cranial ultrasound, brain magnetic resonance imaging (MRI), and neurological examination. All studies assessed high-risk populations including preterm (gestational range 23–41wks) and low-birthweight infants (range 500–4350g). Summary estimates of sensitivity and specificity of GMA were 98% (95% confidence interval [CI] 74–100%) and 91% (95% CI 83–93%) respectively; of cranial ultrasound 74% (95% CI 63–83%) and 92% (95% CI 81–96%) respectively; and of neurological examination 88% (95% CI 55–97%) and 87% (95% CI 57–97%) respectively. MRI performed at term corrected age (in preterm infants) appeared to be a strong predictor of CP, with sensitivity ranging in individual studies from 86 to 100% and specificity ranging from 89 to 97% There was inadequate evidence for the use of other predictive tools. Summary: This review found that the assessment with the best evidence and strength for predictive accuracy is the GMA. MRI has a good predictive value when performed at term-corrected age. Cranial ultrasound is as specific as MRI and has the advantage of being readily available at the bedside. Studies to date have focused on high-risk infants. The accuracy of these tests in low-risk infants remains unclear and requires further research.

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Developmental Medicine and Child Neurology

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55

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5

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Biomedical and clinical sciences

Clinical sciences not elsewhere classified

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