A New Model to Identify Preterm Neonates at High-Risk for Cognitive Impairments and School Readiness

识别认知障碍和入学准备高风险早产儿的新模型

• 批准号: 10442095
• 负责人: NEHAL A. PARIKH
• 金额: $ 89.97万
• 依托单位: CINCINNATI CHILDRENS HOSP MED CTR
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-05-15 至 2027-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10442095
• 关键词: Academic skills; Adult; Affect; Age; American; Area; Attention; Base of the Brain; Behavior; Behavioral; Biological; Birth; Brain; Brain imaging; Categories; Child; Chronic Disease; Clinical; Code; Cognitive; Cohort Studies; Collection; Control Groups; Country; Data; Development; Diagnosis; Diffuse; Diffusion Magnetic Resonance Imaging; Early Diagnosis; Early Intervention; Early identification; Early intervention trials; Emotional; Employment; Enrollment; Face; Failure; Functional Magnetic Resonance Imaging; Funding; Future; Goals; Grant; Hospitalization; Impaired cognition; Impairment; Income; Individual; Infant; Inflammation; Informal Social Control; Intervention; Knowledge; Learning; Longitudinal Studies; Machine Learning; Magnetic Resonance Imaging; Maps; Matched Group; Mathematics; Measures; Mediating; Mediator of activation protein; Mental Health; Meta-Analysis; Mission; Modeling; National Institute of Neurological Disorders and Stroke; Neonatal; Neurodevelopmental Impairment; Neuronal Plasticity; Population; Pregnancy; Premature Birth; Premature Infant; Prevalence; Problem behavior; Public Health; Race; Randomized Clinical Trials; Readiness; Reading; Research; Sampling; School-Age Population; Schools; Series; Short-Term Memory; Testing; Therapeutic Intervention; Time; Work; brain magnetic resonance imaging; cognitive ability; cognitive function; cohort; design; developmental disease; early childhood; executive function; functional disability; high risk; high risk infant; language impairment; machine learning model; magnetic resonance imaging biomarker; multidisciplinary; novel; population based; preterm newborn; prognostic; prognostic model; recruit; sex; socioeconomics; success; white matter

Project Summary/Abstract Children born very preterm (VPT; <32 weeks’ gestation) face a disproportionate burden of neurodevelopmental impairments (NDI). Impairments in the subdomains of mathematics, reading, and behavior are the most common NDI, affecting 25-50% of VPT children. These abilities are critical to school readiness and success at work. In the first cycle of this grant, we assembled the largest North American cohort of VPT infants and performed advanced brain MRI at term corrected age (CA) with longitudinal neurodevelopmental assessments. We demonstrated the clinical importance of diffuse white matter abnormality (DWMA) and multiple other novel MRI biomarkers to enhance prediction of short-term NDI at 2 or 3 years CA. During this second funding cycle, our unique cohort will reach the critical early school ages of 5 to 7 years, when higher-order cognitive abilities in math and reading, emotional self-regulation, and behavior become more apparent and accurately testable. The ability to accurately predict these functions several years earlier could enable early interventions. Assessment of the dynamic trajectories of NDI in VPT children and their modifiable environmental and biologic causes can also accelerate the development of targeted neuroprotective interventions during these critical early years when neuroplasticity is at its peak. The overall objectives of this proposal are to map the early childhood trajectory of brain structural and functional changes and develop early and accurate prognostic models of school readiness. Our rationale is that elucidation of the long-term impact of DWMA, identification of the trajectory and mediators of NDI changes, and robust prognostic models of school readiness will enable novel early intervention trials in targeted VPT infants. To achieve our goals, we will perform morphometric, diffusion, and functional MRI at age 5 and comprehensive developmental testing at 5 and 7 years CA in our cohort of VPT children and a matched group of term-control children. To advance this highly impactful area of research, we propose the following three specific aims: (1) Determine the impact of DWMA at term CA on brain development and functional impairments at age 5; (2) Model individual trajectories of NDI and identify the mediators of neurodevelopmental changes between 3 and 7 years CA; and (3) Develop early prognostic models of school readiness. For the first aim we will correlate objectively quantified DWMA volume at term CA with brain structural and functional connectivity derived from advanced MRI and with higher-order cognitive functions, both at 5 years CA. Under Aim 2, we will plot individual trajectories of neurodevelopmental scores and identify the mediators of trajectory change between 3 and 7 years CA. For the third aim, we will apply the rich collection of clinical, biologic, and neurodevelopmental data collected between birth and 3 years CA to predict our three measures of school readiness at 5 and 7 years CA. This study will provide U.S. population-based prevalence data about the long-term adverse neuroanatomic and functional consequences of VPT birth, identify mediators of NDI change, and facilitate early prediction of school readiness to enable targeted EI and novel randomized clinical trials for VPT children.

项目摘要/摘要 早产儿(怀孕32周)面临着不成比例的神经发育负担 减值(NDI)。数学、阅读和行为等子领域的障碍是最常见的 NDI，影响25%-50%的VPT儿童。这些能力对于准备好上学和在工作中取得成功至关重要。在……里面 在这笔赠款的第一个周期，我们召集了北美最大的VPT婴儿队列，并进行了 具有纵向神经发育评估的足月矫正年龄(CA)高级脑MRI。我们 显示弥漫性脑白质异常(DWMA)和其他多种新的MRI的临床重要性 生物标记物可加强对CA 2或3年短期NDI的预测。在第二个资金周期内，我们的 独特的队列将达到5至7岁的关键早期上学年龄，当较高级别的认知能力在 数学和阅读、情绪自我调节和行为变得更加明显和准确。这个 几年前准确预测这些功能的能力可以使早期干预成为可能。评估 VPT儿童NDI的动态轨迹及其可改变的环境和生物原因 还加快制定有针对性的神经保护干预措施，在这些关键的早年， 神经可塑性正处于顶峰。这项提案的总体目标是描绘儿童早期发展的轨迹 大脑结构和功能的变化，并开发早期和准确的入学准备预测模型。 我们的理论基础是阐明DWMA的长期影响，确定其发展轨迹和调解人 NDI变化和学校准备情况的稳健预测模型将使新的早期干预试验成为可能 针对VPT婴儿。为了实现我们的目标，我们将在年龄段进行形态测量、扩散和功能磁共振成像 在我们的VPT儿童队列中，在5岁和7岁CA时进行5岁和综合发育测试 一组有学期控制的孩子。为了推进这一极具影响力的研究领域，我们提出了以下三项建议 具体目标：(1)确定CA期DWMA对脑发育和功能损害的影响 在5岁时；(2)模拟NDI的个体轨迹并确定神经发育变化的中介因素 在3到7岁CA之间；和(3)开发学校准备情况的早期预测模型。为了达到第一个目标，我们 会客观地将CA时量化的DWMA体积与脑结构和功能连接相关 源自先进的磁共振成像，并具有更高阶的认知功能，均在5年CA。在目标2下，我们将 绘制神经发育分数的个体轨迹图，并确定轨迹变化的中介 3年和7年CA。对于第三个目标，我们将应用丰富的临床、生物学和神经发育资料。 从出生到3年收集的数据用来预测我们在5岁和7岁时的三项入学准备情况 加州。这项研究将提供基于美国人群的长期不利神经解剖学的患病率数据 和VPT出生的功能后果，识别NDI变化的中介因素，并促进早期预测 学校准备好为VPT儿童进行有针对性的EI和新的随机临床试验。