Abnormalities in evoked potentials associated with abnormal glycemia and brain injury in neonatal hypoxic-ischemic encephalopathy

Kamino, Daphne; Almazrooei, Asma; Pang, Elizabeth W.; Widjaja, Elysa; Moore, Aideen M.; Chau, Vann; Tam, Emily

doi:10.1016/j.clinph.2020.09.024

Cited by 15 publications

(12 citation statements)

References 35 publications

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“…We used continuous EEG recordings gathered as a part of a prospective cohort study between 2014 and 2016 in the NICU at the Hospital for Sick Children, Toronto, Canada (Pinchefsky et al, 2019;Kamino et al, 2021). The EEG records were collected up to the first five postnatal days from 27 neonates with average postmenstrual age (PMA) of 39.7 weeks (36-41.4) at birth with clinical signs of neonatal hypoxic-ischemic encephalopathy.…”

Section: Recordingmentioning

confidence: 99%

Building an Open Source Classifier for the Neonatal EEG Background: A Systematic Feature-Based Approach From Expert Scoring to Clinical Visualization

Moghadam

Pinchefsky

Tse

et al. 2021

Front. Hum. Neurosci.

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Neonatal brain monitoring in the neonatal intensive care units (NICU) requires a continuous review of the spontaneous cortical activity, i.e., the electroencephalograph (EEG) background activity. This needs development of bedside methods for an automated assessment of the EEG background activity. In this paper, we present development of the key components of a neonatal EEG background classifier, starting from the visual background scoring to classifier design, and finally to possible bedside visualization of the classifier results. A dataset with 13,200 5-minute EEG epochs (8–16 channels) from 27 infants with birth asphyxia was used for classifier training after scoring by two independent experts. We tested three classifier designs based on 98 computational features, and their performance was assessed with respect to scoring system, pre- and post-processing of labels and outputs, choice of channels, and visualization in monitor displays. The optimal solution achieved an overall classification accuracy of 97% with a range across subjects of 81–100%. We identified a set of 23 features that make the classifier highly robust to the choice of channels and missing data due to artefact rejection. Our results showed that an automated bedside classifier of EEG background is achievable, and we publish the full classifier algorithm to allow further clinical replication and validation studies.

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Section: Recordingmentioning

confidence: 99%

Building an Open Source Classifier for the Neonatal EEG Background: A Systematic Feature-Based Approach From Expert Scoring to Clinical Visualization

Moghadam

Pinchefsky

Tse

et al. 2021

Front. Hum. Neurosci.

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“…Therefore, a simple fully portable device can be helpful in many situations. Based on our first experience, we believe that the device might also extend the detection of such CNS and visual pathway dysfunctions that might not be sometimes recognizable by CT or MRI, such as in neuroborreliosis [18] various encephalopathies [19,20] or HIV positive patients [21]. However, a larger multicentric studies are needed for verification of its practical usability.…”

Section: Discussionmentioning

confidence: 98%

VEP examination with new portable device

Kuba

Kremláček

et al. 2022

Doc Ophthalmol

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Introduction We developed a new portable device called “VEPpeak” for the examination of visual evoked potentials (VEPs) to extend VEP examination beyond specialized electrophysiological laboratories and to simplify the use of this objective, noninvasive, and low-cost method for diagnostics of visual and central nervous system dysfunctions. Methods VEPpeak consists of a plastic headset with a total weight of 390 g containing four EEG amplifiers, an A/D converter, a control unit, and a visual LED stimulator built in the front, vertically adjustable peak. The device is powered and controlled via USB connection from a standard PC/notebook using custom software for visual stimuli generation and for VEP recording and processing. Up to four electrodes can be placed at any scalp location or in combination with two dry electrodes incorporated into the headset. External visual stimulators, such as a tablet, can be used with synchronization. Feasibility and validation studies were conducted with 86 healthy subjects and 76 neuro-ophthalmological patients including 67 who were during the same session also tested with a conventional VEP system. Results VEPpeak recordings to standard (pattern-reversal) and non-standard (motion-onset, red-green alternation) were robust and repeatable and obtained also in immobilized patients. Good comparability of results was achieved between VEPpeak and standard examination. Some systematic differences in peak latencies and amplitudes are consistent with differences in stimulus characteristics of the two compared systems. Discussion VEPpeak provides an inexpensive system for clinical use requiring portability. In addition to ISCEV standard VEP protocols, free choice of stimuli and bio-signal recordings make the device universal for many electrophysiological purposes.

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“…Visual evoked potentials (VEP) are typically obtained to assess the optic pathway in response to a flash of light. Most studies demonstrating association of abnormal VEPs with adverse neurodevelopmental outcome were obtained in the pre-hypothermia era, although in more recent cohorts of infants treated with therapeutic hypothermia for HIE, VEP abnormalities have been associated with impaired hearing-language scores and with abnormal glucose levels and MRI brain injury ( 76 – 78 ). Somatosensory evoked potentials (SEP) are measured by electric stimulation of both median nerves to assess function of the sensory cortex and sensory pathways.…”

Section: Serial Bedside Neuromonitoring Methodsmentioning

confidence: 99%

Optimal neuromonitoring techniques in neonates with hypoxic ischemic encephalopathy

Chock

Rao²,

Meurs³

2023

Front. Pediatr.

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Neonates with hypoxic ischemic encephalopathy (HIE) are at significant risk for adverse outcomes including death and neurodevelopmental impairment. Neuromonitoring provides critical diagnostic and prognostic information for these infants. Modalities providing continuous monitoring include continuous electroencephalography (cEEG), amplitude-integrated electroencephalography (aEEG), near-infrared spectroscopy (NIRS), and heart rate variability. Serial bedside neuromonitoring techniques include cranial ultrasound and somatic and visual evoked potentials but may be limited by discrete time points of assessment. EEG, aEEG, and NIRS provide distinct and complementary information about cerebral function and oxygen utilization. Integrated use of these neuromonitoring modalities in addition to other potential techniques such as heart rate variability may best predict imaging outcomes and longer-term neurodevelopment. This review examines available bedside neuromonitoring techniques for the neonate with HIE in the context of therapeutic hypothermia.

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Abnormalities in evoked potentials associated with abnormal glycemia and brain injury in neonatal hypoxic-ischemic encephalopathy

Cited by 15 publications

References 35 publications

Building an Open Source Classifier for the Neonatal EEG Background: A Systematic Feature-Based Approach From Expert Scoring to Clinical Visualization

Building an Open Source Classifier for the Neonatal EEG Background: A Systematic Feature-Based Approach From Expert Scoring to Clinical Visualization

VEP examination with new portable device

Optimal neuromonitoring techniques in neonates with hypoxic ischemic encephalopathy

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