Rouabhi et al present a novel prognostic tool for identifying the risk of cerebral palsy (CP) in a “low-risk” term newborn, using a large sample of population register data from Canadian infants. Selected clinical variables based on published risk factors were used to build and test a model. Variables not contributing to the model were removed, enabling development of a streamlined prognostic tool. The authors identified 12 clinical variables for inclusion within the tool, all of which are routinely collected clinical information about pregnancy and maternal history (eg, preeclampsia, tobacco use), labor and delivery history (eg, prolonged rupture of membranes, Apgar scores), and infant characteristics (eg, sex, birth weight). The tool calculates a prediction value for risk of CP and gives corresponding ranges from lower than normal to much higher than normal. Importantly, there are recommendations for the additional screening needed at each risk range. This enables streamlined resource use, from routine developmental screening by primary care professionals to referral for specialized assessments such as the General Movements Assessment (GMA) and Hammersmith Neurological Examination (HINE). Term infants with highest risk for CP (those with neonatal encephalopathy and seizures) were not included in the model as it was assumed these infants meet criteria for routine developmental screening as per clinical guideline recommendations.
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