development preterm infant

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.

本研究的核心假设为：明确特定新生儿与孕产妇相关因素是否会对早产儿的神经发育结局产生显著影响。研究推测，胎龄、出生体重及特定新生儿并发症等变量，会通过贝利婴幼儿发育量表（Bayley Scales of Infant and Toddler Development）所评估的维度，对该类婴儿的发育轨迹产生显著影响。
本数据集源自2016至2020年间，针对伊朗马什哈德盖姆医院（Ghaem Hospital）新生儿重症监护病房（Neonatal Intensive Care Unit, NICU）收治的早产儿开展的回顾性队列研究，是一类涵盖丰富数据的汇编资料。数据集包含多维度变量，可全面展现孕产妇与新生儿两方面的相关因素。
该数据集的关键研究结果显示，多项新生儿与孕产妇相关因素与早产儿的发育结局存在显著关联。诸如宫内生长受限（Intrauterine Growth Restriction, IUGR）、气胸、支气管肺发育不良（Bronchopulmonary Dysplasia, BPD）等变量，均被证实与多发育领域的功能损害存在显著关联。此外，数据还显示，更长的住院时长与氧疗时长，与各发育领域的不良结局存在关联。
研究者可通过分析各类记录变量与贝利量表所评估的发育结局之间的关联，来解读本数据集。数据集对各发育领域进行了细致分类，可帮助研究者深入了解婴儿所经历的发育迟缓的严重程度与类型。本数据集可用于开展进一步研究，以解析影响早产儿发育的生物学与环境因素间的复杂相互作用。
该数据集可作为开发针对性早期干预策略的基础资源，助力优化这一脆弱群体的发育结局。计划使用本数据集的研究者，应结合所涉及变量的多维度特性，采用全面的分析策略开展研究。采用逻辑回归等统计学分析方法，以识别变量间潜在的关联与影响机制，将有助于研究的开展。
本数据集全面涵盖了孕产妇与新生儿相关因素的详细信息，有望成为推动新生儿保健领域进一步研究的重要资源，或可为开发预防性与干预性策略以提升早产儿的生活质量开辟新路径。

搜集汇总

背景与挑战

背景概述

该数据集是一个关于早产儿神经发育的回顾性队列研究，收集了2016年至2020年间Ghaem医院NICU收治的早产儿数据，涵盖新生儿和母体因素。研究发现，宫内生长受限、气胸和支气管肺发育不良等变量与发育障碍显著相关，住院和氧疗时间延长也与不良发育结果有关，数据可用于分析发育轨迹和制定干预策略。