Chalak Lina F, Zhang Rong
Department of Pediatrics and Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Dev Neurosci. 2017;39(1-4):89-96. doi: 10.1159/000457833. Epub 2017 Mar 30.
Neonatal encephalopathy (NE) resulting from birth asphyxia constitutes a major global public health burden for millions of infants every year, and despite therapeutic hypothermia, half of these neonates have poor neurological outcomes. As new neuroprotective interventions are being studied in clinical trials, there is a critical need to establish physiological surrogate markers of therapeutic efficacy, to guide patient selection and/or to modify the therapeutic intervention. The challenge in the field of neonatal brain injury has been the difficulty of clinically discerning NE severity within the short therapeutic window after birth or of analyzing the dynamic aspects of the cerebral circulation in sick NE newborns. To address this roadblock, we have recently developed a new "wavelet neurovascular bundle" analytical system that can measure cerebral autoregulation (CA) and neurovascular coupling (NVC) at multiple time scales under dynamic, nonstationary clinical conditions. This wavelet analysis may allow noninvasive quantification at the bedside of (1) CA (combining metrics of blood pressure and cerebral near-infrared spectroscopy, NIRS) and (2) NVC (combining metrics obtained from NIRS and EEG) in newborns with encephalopathy without mathematical assumptions of linear and stationary systems. In this concept paper, we present case examples of NE using the proposed physiological wavelet metrics of CA and NVC. The new approach, once validated in large NE studies, has the potential to optimize the selection of candidates for therapeutic decision-making, and the prediction of neurocognitive outcomes.
出生窒息导致的新生儿脑病(NE)每年给数百万婴儿带来重大的全球公共卫生负担,尽管有治疗性低温治疗,但这些新生儿中有一半的神经学预后较差。随着新的神经保护干预措施正在临床试验中进行研究,迫切需要建立治疗效果的生理替代标志物,以指导患者选择和/或调整治疗干预措施。新生儿脑损伤领域的挑战在于,在出生后的短治疗窗口期内临床上难以辨别NE的严重程度,或者难以分析患病NE新生儿脑循环的动态方面。为了解决这一障碍,我们最近开发了一种新的“小波神经血管束”分析系统,该系统可以在动态、非平稳的临床条件下,在多个时间尺度上测量脑自动调节(CA)和神经血管耦合(NVC)。这种小波分析可以在床边对脑病新生儿进行无创量化:(1)CA(结合血压和脑近红外光谱学(NIRS)指标)和(2)NVC(结合从NIRS和脑电图获得的指标),而无需线性和稳定系统的数学假设。在这篇概念论文中,我们展示了使用所提出的CA和NVC生理小波指标的NE病例实例。这种新方法一旦在大型NE研究中得到验证,就有可能优化治疗决策候选人的选择以及神经认知结果的预测。