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 以打鼾和睡眠中断为特征的睡眠呼吸障碍（SDB）影响着十分之一的儿童。 SDB的不良后果，如问题行为、嗜睡和生活质量下降，导致不良的 课堂表现，并被认为是有关的结构和功能的变化，在前额叶 大脑皮层（PFC）。因此，所有临床学会都支持对儿童进行SDB的普遍筛查， 通过切除扁桃体和腺样体（腺样体切除术或“AT”）进行治疗，该手术在50万儿童中进行， 每年仅在美国就有100万人。然而，有些孩子也会自发地解决问题。 SDB和因此观察等待也是这些儿童可以接受的治疗选择。目前有 对于可能从AT中受益的儿童，没有统一接受的标准，而不是警惕等待。多梦 目前使用造影对SDB的严重程度进行分层。然而，多导睡眠图参数也不相关- 与SDB儿童的行为、认知或生活质量以及AT的结果无关。因此，两大 存在知识差距，包括缺乏（i）理解AT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。填补这些空白 可以改善患者的选择，减少伤害，并提高父母的满意度，这是最常见的问题之一， 小儿外科手术。 我们已经表明，SDB和儿童的行为之间的关系是通过结构改变介导的 使用功能近红外光谱（fNIRS），我们进一步证明了 前额叶皮层（PFC）区域的大脑激活与儿童的行为测量相关， 关于SDB使用一系列的数据科学技术，我们还表明，多导睡眠参数- 指标不能预测SDB或AT的结局。在这里，我们提出使用一种新的生物标志物的功能激活 使用fNIRS和基线患者特征预测接受SDB的儿童的结局 治疗在200名接受早期AT或2岁时观察等待策略管理SDB的儿童中， 大而多样的临床实践，我们的具体目标包括：目的1）为了确定认知的程度， AT的结果是由PFC激活介导的，目的2）为了确定父母报告的程度， AT的发生是由PFC激活介导的，目的3）建立SDB治疗的预测模型 使用人口统计学、人体测量学、多导睡眠图和fNIRS变量的结果。采用多学科 在数据科学方法方面拥有世界一流的专业知识，该提案旨在解决我们在数据科学方法方面的差距。 对AT结果的机械理解，并建立一个客观的，儿童友好的，具有成本效益的方法， 确定外科候选人的方法。