Early risk for ADHD symptoms in young children with Down syndrome

摘要 唐氏综合征（DS）患者患注意力缺陷和多动障碍的风险较高 （ADHD）。这种合并症与DS患者在整个病程中的适应困难有关。 寿命，并有助于与DS个人的医疗保健相关的明显的经济负担 和他们的家人因此，共病ADHD是DS患者的主要健康问题。但 目前还没有科学依据来早期发现和治疗这种并发症。为了解决这个 在我们的知识差距，这个项目将采用创新的回顾性研究设计，使我们能够 利用大量DS婴儿（n= 78）的现有数据，然后将这些数据与 4-5岁时ADHD症状和认知的当前表现。我们还将研究生物医学的作用， 婴儿认知与后期ADHD症状之间联系的风险，并检查了 睡眠障碍，先天性心脏病，早产和其他经常发生的疾病的影响， DS.我们将使用一种先进的定量分析方法，利用结构内的潜在变量模型， 方程建模框架来研究这些纵向关联。这项研究的结果将有助于 早期发现共病精神症状，并直接解决DS INCLUDE目标“定义 DS患者的并发症的表现和病程”，以告知未来的治疗 创新和改善这一人群的适应能力。

Abstract Individuals with Down syndrome (DS) are at elevated risk for Attention Deficit and Hyperactivity Disorder (ADHD). This comorbidity is associated with adaptation difficulties among individuals with DS throughout their lifespan, and contributes to the pronounced financial burden associated with health care for individuals with DS and their families. Comorbid ADHD, therefore, is a major health concern for individuals with DS. However, there is currently no scientific foundation for the early detection and treatment of this comorbidity. To address this gap in our knowledge, this project will adopt an innovative retrospective research design that will allow us to leverage a wealth of existing data on a large cohort of infants with DS (n= 78), and then link those data to the current presentation of ADHD symptoms and cognition at 4-5 years. We will also examine the role of biomedical risk in the link between infant cognition and later ADHD symptoms, with an examination of the moderating effects of sleep disturbance, congenital heart defects, prematurity, and other conditions that occur frequently in DS. We will use an advanced quantitative analytic approach utilizing latent variable models within a structural equation modeling framework to examine these longitudinal associations. Findings from this study will facilitate earlier detection of comorbid psychiatric symptoms and directly address the DS INCLUDE objective of “defining the presentation and course of co-occurring conditions in individuals with DS” to inform future treatment innovations and improve adaptation in this population.