Early Screening for Cerebral Palsy: A Systematic Review
Desi Newberry1, Kaylee Apel, Jessica Metcalf
1Author Affiliations: Duke University School of Nursing, Durham, North Carolina (Dr Newberry, Mrs Apel, Ms Metcalf, Mrs Stephens, Ms Snyder, Ms Bernstein, Ms Roche, Mrs Pace, Ms Tillmaand, and Mrs Topper); UNC Neonatology Chapel Hill, North Carolina (Dr Newberry); Duke University Hospital (Dr Newberry); and Duke University Medical Center Library, Durham, North Carolina (Ms Ledbetter).
Background:
Cerebral palsy (CP) is the most common motor disability in childhood. Preterm infants, particularly those born before 28 weeks' gestation or extremely low birth weight, are at an increased risk due to the vulnerability of the developing brain.
Purpose:
The purpose of this systematic review is to evaluate the predictive accuracy and clinical utility of various neonatal screening methods in concluding early diagnosis of CP.
Data Sources:
A comprehensive systematic review of evidence-based research was conducted using MEDLINE (PubMed), Embase (Elsevier), and Web of Science (Clarivate) including key words and subject headings.
Study Selection:
Inclusion criteria included preterm infants at high risk for CP, CP diagnosis prior to 12 months of age. A total of 3835 citations were identified, duplicates were removed, and 2283 citations were screened by 2 reviewers each. Of these, 154 citations were identified and reviewed in full, with 44 citations selected for inclusion.
Data Extraction:
Extraction was performed using the study characteristics including study design, study purpose, assessment tools utilized, gestational age, sample size, age of CP assessment, results, conclusion, limitations, and risk of bias.
Results:
Early screening for CP in preterm infants using a combination of neuroimaging, motor performance, and neurological assessments improves diagnostic accuracy before 12 months of age.
Implications For Practice And Research:
The General Movements Assessment and MRI are especially effective in early diagnosis; further validation is needed on new technologies. Early identification enables timely intervention, which may improve developmental outcomes and reduce long-term disability in this high-risk population.
