development preterm infant

Published: 9 October 2023| Version 2 | DOI: 10.17632/h464gsf77t.2
Azadeh Darabi, Raheleh Faramarzi


The primary hypothesis of this research was to ascertain whether specific neonatal and maternal factors significantly influence the neurodevelopmental outcomes in preterm infants. It was hypothesized that variables such as gestational age, birth weight, and specific neonatal complications would have a notable impact on the developmental trajectories of these infants, as measured through the Bayley Scales of Infant and Toddler Development. The dataset is a rich compilation of data gathered from a retrospective cohort study conducted on preterm infants admitted to the NICU at Ghaem Hospital, Mashhad, between 2016 and 2020. It encompasses a wide range of variables that provide a comprehensive view of both maternal and neonatal factors. Notable findings from the data indicate significant associations between several neonatal and maternal factors and developmental outcomes in preterm infants. Variables such as Intrauterine Growth Restriction (IUGR), pneumothorax, and Bronchopulmonary Dysplasia (BPD) were found to be significantly associated with impairments in various developmental domains. Furthermore, the data revealed that longer durations of hospitalization and oxygen therapy were linked with negative developmental outcomes in different domains.To interpret the data, researchers can analyze the associations between the various recorded variables and the developmental outcomes measured through the Bayley Scales. The dataset includes detailed categorizations within developmental domains, offering insights into the severity and type of developmental delays experienced by the infants. The data can be utilized to conduct further research into the complex interplay of biological and environmental factors influencing preterm infant development. It can serve as a foundational resource for developing targeted early intervention strategies, thereby aiding in optimizing developmental outcomes for this vulnerable population. Researchers aiming to use this data should approach it with a comprehensive analytical strategy, considering the multifaceted nature of the variables involved. It would be beneficial to employ statistical analyses such as logistic regression to identify potential associations and influences between the variables. By providing a detailed overview of both neonatal and maternal factors, the dataset promises to be a significant asset in fostering further research in the field of neonatal healthcare, potentially paving the way for advancements in preventative and interventional strategies to enhance the quality of life for preterm infants.



Mashhad University of Medical Sciences Faculty of Medicine


Infant, Cognitive Assessment, Brain Development