Research Project
8520365
DESCRIPTION (provided by applicant): Most preterm infants have episodes of apnea (cessation of breathing), bradycardia (low heart rate), and desaturations (low levels of oxygen in the blood) or what is collectively called as ABD events. The resolution of such ABD episodes depends to a large extent on the maturation of the central nervous system (CNS).The electroencephalogram (EEG) is the only reliable and noninvasive tool required for recording from the CNS, and determining electrographic markers that could predict recurrence or resolution of ABD episodes. Despite such obvious need, standard EEG is not constantly available in most Neonatal Intensive Care Units (NICUs). The main obstacles to its routine availability in NICUs include high cost of standard EEG machines, inability of most standard machines to operate in electrically-noisy environments such as the NICU, and more importantly the absence of full-time coverage neurologists for prompt EEG interpretation. There is an obvious unmet need for routine EEG availability in the NICU, not only for identification of maturation of brain electrical activity in infants with ABD events, but also for identification of seizures, evaluation of treatment response, and prognosticating high-risk neonates in the choice of early neuroprotective treatments. Allowing for routine EEG availability in the NICU requires the innovation of a product capable of overcoming the aforementioned impediments, particularly allowing for immediate EEG assessment by remote neurologists, without compromising the quality of EEG's generated in that setting. We propose, first, to determine the feasibility of obtaining an artifact-free EEG in the NICU with accurate detection of background rhythm abnormalities. For this purpose we will leverage the performance of our existing digital wireless telemetry unit, the microEEG for the NICU, particularly in prolonged recordings. Secondly, we propose to finalize the development of an inexpensive system to record an artifact free EEG in the NICU, and develop a case management system for obtaining a centralized network of EEG interpretation from off-site neurologists. Finally, we will examine the level of agreement between the various EEG interpretations provided by the neurologists, and therefore set up consensus guidelines for low agreement EEG interpretations.
