Impact of the ICU acoustic environment on neonatal sleep

 描述(由申请人提供)：美国每年有超过40万名新生儿需要进入新生儿重症监护病房(NICU)。这些婴儿中的许多人后来患上了严重的神经系统疾病。我们的长期假设是，NICU的感觉环境与宫内环境截然不同，破坏了未成熟大脑对刺激敏感的可塑性，并导致异常发育结果，至少在一些脆弱的婴儿中是这样。健康的新生儿每天有三分之二的时间产生睡眠，这是一种复杂且高度调节的神经功能。新出现的证据表明，婴儿期晚期睡眠生理紊乱会导致随后的不良神经行为结果。很少对患病新生儿的睡眠进行分析，部分原因是一个关键的未解决的挑战：还没有建立一个实用、有效和定量的方法来监测新生儿的睡眠周期。研究人员的创新初步工作现在表明，几种定量睡眠测量--睡眠/醒来时间、睡眠碎片(熵)和阶段转换概率--可以预测神经状态。然而，促进理想新生儿睡眠的最佳环境尚不清楚。最近令人信服的数据突显了优化NICU环境的努力所固有的复杂性。早产儿受到外界声音的保护，以最大限度地减少睡眠中断，表现出语言发育不良。相反，在NICU中增加语言接触会带来更好的长期语言发展。因此，简单地提供一个安静的NICU环境可能不是一个理想的治疗方法。在这种情况下，现在提出的研究是由以下全球假设指导的：对于新生儿来说，正常的睡眠质量和数量有助于最佳的神经发育，但NICU的睡眠会受到潜在的可改变的环境噪声的干扰。目的1：在50例晚期早产和足月儿NICU患者中，将上述新的定量睡眠测量作为胎龄和出生后年龄的函数，并根据疾病严重程度进行调整。目的2：在多导睡眠图中，通过自动语言环境分析(LENA)测试，确定这些定量睡眠指标对非语言噪音、交谈和沉默时间的敏感性。目的3：通过睡眠/觉醒时长、信息熵和阶段转换概率来评估大量暴露于母亲语言而不是非语言噪音对新生儿睡眠的影响。在NICU中应用正式的PSG，结合创新的分析技术来评估睡眠阶段分布和睡眠碎片，将为新生儿大脑功能完整性提供新的、客观的衡量标准。这项拟议的研究将首次评估NICU声环境对定量PSG数据的影响。结果将为后续的干预设计提供信息，以优化NICU的声学环境，改善睡眠调节，并改善神经发育结果。

 DESCRIPTION (provided by applicant): More than 400,000 newborns delivered each year in the U.S. require admission to neonatal intensive care units (NICUs). Many of these infants later develop substantial neurologic morbidity. Our long-term hypothesis is that the NICU sensory environment, which differs dramatically from the in utero milieu, disrupts the stimulus- sensitive plasticity of the immature brain and contributes to abnormal developmental outcome, at least in some vulnerable infants. Healthy newborns generate sleep, a complex and highly regulated neurologic function, for two-thirds of each day. Emerging evidence suggests that disturbed sleep physiology during late infancy contributes to subsequent adverse neurobehavioral outcomes. Sleep is rarely analyzed in sick neonates, in part because of a key unsolved challenge: a practical, validated, and quantitative approach to monitoring neonatal sleep cycling has not been established. Innovative preliminary work by the investigators now suggests that several quantitative sleep measures - sleep/wake bout lengths, sleep fragmentation (entropy), and stage transition probabilities - may predict neurologic status. Yet, the optimal environment to promote ideal neonatal sleep is unknown. Compelling recent data highlight the complexities inherent in efforts to optimize the NICU environment. Preterm infants protected from extrinsic sound, to minimize sleep disruption, showed poor language development. Conversely, increased language exposure in the NICU led to better long-term language development. Therefore, simple provision of a quiet NICU environment may not be an ideal therapeutic approach. In this setting, the research now proposed is guided by the following Global Hypothesis: For neonates, normal quality and quantity of sleep contribute to optimal neurodevelopment, but sleep is disrupted in the NICU by potentially modifiable environmental noise. Aim 1: Characterize the above novel quantitative sleep measures as a function of gestational age and postnatal age, adjusted for illness severity, among 50 late-preterm and term NICU patients. Aim 2: Determine the sensitivity of these quantitative sleep measures to non-language noise, conversation, and periods of silence, quantified by automated language environment analysis (LENA) testing during polysomnography. Aim 3: Assess the effect of enriched exposure to mother's speech, as opposed to non-language noise, on neonatal sleep, as measured by sleep/wake bout lengths, entropy, and stage transition probabilities. Application of formal PSG in the NICU, with innovative analytic techniques to assess sleep stage distribution and sleep fragmentation, will provide novel, objective measures of neonatal brain functional integrity. The proposed study will be the first to assess the influence of the NICU acoustic environment on quantitative PSG data. Results will inform the subsequent design of interventions to optimize the NICU acoustic environment, ameliorate sleep regulation, and improve neurodevelopmental outcomes.