Thursday, November 21, 2024
11/21/2024
Project Summary/Abstract The goal of this project is to develop a portable, low-cost tool to aid in the diagnosis and management of neonates born with neurologic complications. The project will develop instrumentation technology and associated software to enable early detection of neurologic brain injury and seizure activity for newborns delivered in care facilities that lack a full suite of neurological diagnostic tools. In neonates with birth asphyxia, seizures are very common and most frequently subclinical. Many studies have observed that even experienced clinicians have difficulty correctly identifying seizures in this population. Subsequently, clinical paroxysms that do not truly represent seizure are frequently over-treated and subclinical seizures, including status epilepticus, go unrecognized and untreated. As such, the use of continuous video‐electroencephalograph (EEG) monitoring is the gold standard for recognizing and treating seizures in this population. It is also very helpful at identifying which children have sustained brain injury, including hypoxia. This resource intense modality has become the standard of care at many tertiary medical centers but unfortunately remains unavailable to many clinicians at smaller birth facilities. Quantitative EEG, including the use of amplitude-integrated EEG (aEEG), has gained widespread use at most neonatal ICUs, and represents a more user-friendly bedside tool for identifying brain injury and seizures. The proposed phase II project aims to design, build, and evaluate a low- cost telemedicine-enabled aEEG monitor and associated multi-instrument software package that supports widespread use of aEEG in community-based birth / care facilities.
HHS’ Tracking Accountability in Government Grants System (TAGGS) website provides access to detailed descriptions of grants, loans, aggregated direct payments and other types of financial assistance awarded by the HHS Operating Divisions (OPDIVs) and the Office of the Secretary Staff Divisions (STAFFDIVs).
