A mechanistic understanding of treatment-related outcomes of sleep disordered breathing using functional near infrared spectroscopy

使用功能性近红外光谱从机制上理解睡眠呼吸障碍的治疗相关结果

• 批准号: 10565985
• 负责人: Amal Isaiah
• 金额: $ 58.19万
• 依托单位: UNIVERSITY OF MARYLAND BALTIMORE
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-02-01 至 2028-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10565985
• 关键词: 15 year old; Address; Adenoidal structure; Adverse effects; Adverse event; Affect; Algorithms; Attention; Behavior; Brain; Brain region; Caregivers; Characteristics; Child; Child Behavior; Childhood; Clinical; Cognition; Cognitive; Coupled; Data Science; Disease; Disparity; Drowsiness; Enrollment; Equipment and supply inventories; Excision; Exposure to; Friends; Functional Magnetic Resonance Imaging; General Anesthesia; Harm Reduction; Impairment; Impulsivity; Knowledge; Learning Disorders; Measures; Mediating; Medical; Modeling; Observational Study; Obstructive Sleep Apnea; Operative Surgical Procedures; Outcome; Parents; Patient Selection; Patient observation; Patients; Pediatric Surgical Procedures; Performance; Polysomnography; Population Heterogeneity; Prefrontal Cortex; Problem behavior; Quality of life; Questionnaires; Race; Reporting; Resolution; Risk Reduction; Severities; Sleep; Sleep Apnea Syndromes; Sleep disturbances; Snoring; Societies; Socioeconomic Status; Stratification; Structure; Supportive care; Symptoms; Techniques; Testing; Tonsil; Treatment outcome; United States; United States National Institutes of Health; Unnecessary Surgery; adverse outcome; aged; behavior measurement; clinical practice; cost effective; executive function; experience; follow up assessment; functional near infrared spectroscopy; health care service utilization; improved; interdisciplinary approach; model development; multidisciplinary; neural; novel marker; outcome prediction; predictive modeling; primary outcome; response; satisfaction; screening; secondary outcome; shared decision making; specific biomarkers; treatment group

PROJECT SUMMARY Sleep disordered breathing (SDB), characterized by snoring and sleep disruption, affects one in ten children. Adverse outcomes of SDB such as problem behaviors, sleepiness, and lower quality of life contribute to poor classroom performance and are thought to be related to structural and functional alterations within the prefrontal cortex (PFC) of the brain. All clinical societies therefore support universal screening for SDB in children and its treatment by removal of tonsils and adenoids (adenotonsillectomy or ‘AT’), a surgery performed in 500,000 chil- dren annually in the United States alone. However, some children also experience spontaneous resolution of SDB and therefore watchful waiting is also an acceptable treatment option for these children. Currently there are no uniformly accepted criteria for children likely to benefit from AT as opposed to watchful waiting. Polysomnog- raphy is currently used for stratification of SDB severity. However, polysomnographic parameters neither corre- late with behavior, cognition, or quality of life nor the outcomes of AT in children with SDB. Therefore, two major gaps in knowledge exist, which include the lack of (i) understanding the mechanism by which AT impacts SDB outcomes, and (ii) a predictive model for selection of children likely to benefit from AT. Addressing these gaps could improve patient selection, reduce harm, and increase parental satisfaction related to one of the most com- mon pediatric surgical procedures. We have shown that the relationship between SDB and children’s behavior is mediated by structural alterations within or close to the PFC. Using functional near-infrared spectroscopy (fNIRS), we have further demonstrated that regional brain activation within the prefrontal cortex (PFC) correlates with behavioral measures in children with SDB. Using a range of data science techniques, we have additionally shown that polysomnographic param- eters do not predict SDB or AT outcomes. Here we propose the use of a novel biomarker for functional activation of the PFC using fNIRS and baseline patient characteristics to predict outcomes of children undergoing SDB treatment. In 200 children undergoing management of SDB by early AT or a strategy of watchful waiting at two large and diverse clinical practices, our specific aims include: Aim 1) To determine the extent to which cognitive outcomes of AT are mediated by PFC activation, Aim 2) To determine the extent to which parent-reported out- comes of AT are mediated by PFC activation, and Aim 3) To develop a predictive model for SDB treatment outcomes using demographic, anthropometric, polysomnographic, and fNIRS variables. Using a multidisciplinary approach with world-class expertise in data science approaches, this proposal seeks to address gaps in our mechanistic understanding of AT outcomes and establish an objective, child-friendly, and cost-effective ap- proach for identification of surgical candidates.

项目摘要 睡眠失调的呼吸（SDB）以打ing和睡眠破坏为特征，影响十分之一的孩子。 SDB的不利结果，例如问题行为，嗜睡和生活质量较低，有助于贫困 课堂表现，被认为与前额叶内的结构和功能变化有关 大脑的皮质（PFC）。因此，所有临床社会都支持儿童及其SDB的普遍筛查 通过去除扁桃体和腺样体（腺孔切除术或“ AT”）的治疗，在500,000个辣椒中进行了手术 仅在美国，每年一次。但是，有些孩子还经历了赞助的决议 因此，SDB和注意等待也是这些孩子的可接受治疗选择。目前有 没有对儿童的统一认可的标准，可能会从中受益，而不是注意等待。多症 图形目前用于SDB严重程度的分层。但是，多摄像学参数都不 晚期行为，认知或生活质量或SDB儿童的成果。因此，两个专业 知识中存在差距，其中包括缺乏（i）了解影响SDB的机制 结果，以及（ii）选择可能受益于AT的儿童的预测模型。解决这些差距 可以改善患者的选择，减少伤害，并提高与最合并之一相关的父母满意度 MON小儿手术程序。 我们已经表明，SDB与儿童行为之间的关系是由结构改变介导的 内部或靠近PFC。使用功能性近红外光谱（FNIRS），我们进一步证明了 前额叶皮层（PFC）内的区域大脑激活与儿童的行为度量相关 与SDB。使用一系列数据科学技术，我们还表明，多个学术摄像学参数 ETERS不预测SDB或在结果下。在这里，我们建议使用一种新型生物标志物进行功能激活 使用FNIRS和基线患者特征来预测经历SDB的儿童的结果 治疗。在200名儿童接受SDB管理的200名儿童中，或者是观察两个的策略 大而多样化的临床实践，我们的具体目的包括：目标1）确定认知的程度 AT的结果是由PFC激活介导的，目标2）确定父母报告的程度 AT的出现是由PFC激活介导的，目标3）开发用于SDB处理的预测模型 使用人口统计学，人体测量学，多渗透学和FNIRS变量的结果。使用多学科 与世界一流的数据科学方法专业知识的方法，该提案旨在解决我们的差距 机械理解以结果的理解，并建立客观，儿童友好且具有成本效益的AP- 用于识别手术候选者的攻击。