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Updated: Nov 11, 2025

Assessment and Evaluation of the High Risk Neonate: The NICU Network Neurobehavioral Scale
Published on: August 25, 2014
Predictors of persistent and changing developmental problems of preterm children
Arend F Bos1, Jorijn Hornman2, Andrea F de Winter2
1Beatrix Children's Hospital, Division of Neonatology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.
Predicting developmental problems in preterm children is crucial for early intervention. Specific perinatal and social factors, like maternal mental illness and small-for-gestational age birth, significantly improve prediction accuracy for these children.
Area of Science:
- Pediatrics
- Developmental Psychology
- Public Health
Background:
- Accurate prediction of developmental problems in preterm-born children is essential for timely and targeted interventions.
- Understanding the trajectory of developmental issues from early childhood to school entry is critical.
Purpose of the Study:
- To identify perinatal and social factors associated with persistent, emerging, and resolving developmental problems in early-preterm (EP) and moderately-and-late-preterm (MLP) children.
- To assess the predictive value of these factors for developmental outcomes from before to after school entry.
Main Methods:
- A longitudinal observational cohort study involving 341 EPs and 565 MLPs.
- Developmental problems were assessed using the Ages and Stages Questionnaire at ages 4 and 5.
- Logistic regression analyses were employed to examine associations between 48 perinatal and social factors and developmental problem trajectories.
Main Results:
- Persistent problems were observed in 8.7% of EPs and 4.3% of MLPs; emerging problems affected 5.1% of EPs and 1.9% of MLPs.
- Key predictors for persistent problems included maternal chronic mental illness, male sex, small-for-gestational age (SGA) birth, and multiparity.
- Prolonged premature rupture of membranes (PPROM) in MLPs predicted emerging problems. The inclusion of identified risk factors improved prediction model variance from 3.0% to 21.9%.
Conclusions:
- Few perinatal and social factors consistently predicted developmental problems across both EP and MLP groups.
- Neonatal conditions like SGA and PPROM in MLPs are associated with persistent developmental issues.
- Identifying specific risk factors significantly enhances the prediction of developmental problems in preterm children, enabling better intervention strategies.
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