Prognostic model using 12 variables identifies 2.4-fold more children with CP than would have presented with encephalopathy<\/p>\n<\/h3>\n
By Elana Gotkine HealthDay Reporter<\/b><\/p>\n
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THURSDAY, Jan. 19, 2023 (HealthDay News) — A prognostic model using 12 clinical variables improves prediction of cerebral palsy (CP) compared with clinical presentation with encephalopathy, according to a study published online Jan. 17 in JAMA Pediatrics<\/em>.<\/p>\n Amira Rouabhi, from McGill University in Montreal, and colleagues conducted a case-control study using data from the Canadian Cerebral Palsy Registry for children with CP and the Alberta Pregnancy Outcomes and Nutrition study for controls to develop a CP prognostic tool that can be applied to all term neonates. A total of 3,250 infants were included.<\/p>\n The researchers found that encephalopathy was present in 28 percent of 1,184 infants with CP and 0 controls. The final prediction model included 12 variables and was able to classify 75 percent of infants correctly, with sensitivity and specificity of 56 and 82 percent, respectively, and a C-statistic of 0.74. Risk factors were additive. At a proposed threshold for screening of a probability greater than 0.3, sensitivity and specificity were 65 and 71 percent, respectively. Overall, 2.4-fold more children with CP were identified with the prognostic tool than would have presented with encephalopathy (odds ratio, 13.8).<\/p>\n “This tool may be used at a population level for the early detection of CP and may allow for infants with uneventful pregnancies or deliveries to be identified for early interventions,” the authors write.<\/p>\n Abstract\/Full Text (subscription or payment may be required)<\/a><\/p>\n Editorial (subscription or payment may be required)<\/a><\/p>\n <\/i><\/p>\n