Does relative or absolute EEG power have prognostic value in HIE setting?

Govindan, Rathinaswamy B.; Massaro, An N.; Vézina, Gilbert; Tsuchida, Tammy N.; Cristante, Caitlin; Plessis, Adré du

doi:10.1016/j.clinph.2016.10.094

Cited by 16 publications

(11 citation statements)

References 4 publications

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“…35,36 We have shown in our earlier studies that absolute spectral power tracks evolving encephalopathy better than the relative power. 7,37 Clinical grade of encephalopathy at presentation remains the mainstay of early prognostication in HIE. Prior studies have correlated qualitative and quantitative EEG metrics to Sarnat stage of encephalopathy.…”

Section: Discussionmentioning

confidence: 99%

“…For each 10-minute window, the spectral analysis was performed using a Welch periodogram approach. 7,19 EEG data were divided into 3-second epochs to estimate the spectrum in a frequency resolution of 0.33 Hz (1/3 second). The periodogram of the EEG in each epoch was calculated as the square of the absolute of the Fourier transform of the data.…”

Section: Eeg Preprocessing and Spectral Characterizationmentioning

confidence: 99%

“…Following our earlier study, the spectral power in the delta frequency band was defined as the median of the logarithm of the spectral power in the frequency band of 0.5-4 Hz. 7 This procedure was repeated for every electrode.…”

Section: Eeg Preprocessing and Spectral Characterizationmentioning

confidence: 99%

“…6 We previously reported the potential utility of delta power as a quantitative EEG metric in HIE. 7 Recent studies have evaluated various other quantitative EEG metrics in neonates with HIE, [8][9][10][11] but they examined only a few discrete time periods (eg, in the first 24 hours of life or during rewarming) and/or used EEG data from a limited number of electrodes. As encephalopathy evolves acutely and location of brain injury is variable, only a comprehensive examination of all surface cortical regions throughout therapeutic hypothermia can identify which time point(s) after injury and which EEG lead location(s) are most predictive of the course and severity of encephalopathy.…”

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confidence: 99%

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Prognostic Value of Continuous Electroencephalogram Delta Power in Neonates With Hypoxic-Ischemic Encephalopathy

et al. 2020

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The objective was to examine the discriminatory ability of electroencephalogram (EEG) delta power in neonates with hypoxic-ischemic encephalopathy (HIE) with well-defined outcomes. Prolonged continuous EEG recordings from term neonates with HIE during therapeutic hypothermia enrolled in a prospective observational study were examined. Adverse outcome was defined as death or severe brain injury by magnetic resonance imaging (MRI); favorable outcome was defined as normal or mild injury by MRI. Neonates were stratified by Sarnat grade of encephalopathy at admission. EEG was partitioned into 10-minute nonoverlapping artifact- and seizure-free epochs. Delta power was calculated and compared between the groups using receiver operating characteristic (ROC) analyses and Wilcoxon rank-sum tests. An area under the ROC curve >0.7 with P <.05 was considered a significant separation between groups. The favorable outcome group (n = 67) had higher delta power than the adverse outcome group (n = 28) across the majority of time periods from 9 to 90 hours of life. Delta power discriminated outcome groups for neonates with moderate encephalopathy (63 favorable and 14 adverse outcome) earlier in cooling (9-42 hours of life) than neonates with severe encephalopathy (21-42 hours of life). Outcome groups were differentiated after 81 hours of life in neonates with moderate and severe encephalopathy. Delta power can distinguish cooled HIE neonates with adverse outcome independently of the encephalopathy grade at presentation. Delta power may be a real-time continuous biomarker of evolving encephalopathy and brain injury/death in neonates with HIE.

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Section: Discussionmentioning

confidence: 99%

Section: Eeg Preprocessing and Spectral Characterizationmentioning

confidence: 99%

Section: Eeg Preprocessing and Spectral Characterizationmentioning

confidence: 99%

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confidence: 99%

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Prognostic Value of Continuous Electroencephalogram Delta Power in Neonates With Hypoxic-Ischemic Encephalopathy

et al. 2020

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“…Therefore, it is common to observe excessive delta and theta absolute power as well as excessive theta subband relative power in ESRD patients with MICS. However, as noted in a communication paper, EEG in encephalopathy frequently has high variability, and the average absolute power is more capable of reflecting this signal variability than the relative power (Govindan et al, 2017 ). The reliability of the relative power is questionable in encephalopathy classifications, and this observation may explain why the theta subband relative power result does not correlate with any clinical data and why the beta 3 relative power is not a significant predictor variable in the MICS classification model.…”

Section: Discussionmentioning

confidence: 99%

QEEG characteristics associated with malnutrition-inflammation complex syndrome

Jatupornpoonsub

Thimachai²,

Supasyndh³

et al. 2023

Front. Hum. Neurosci.

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End-stage renal disease (ESRD) has been linked to cerebral complications due to the comorbidity of malnutrition and inflammation, which is referred to as malnutrition-inflammation complex syndrome (MICS). The severity of this condition is clinically assessed with the malnutrition-inflammation score (MIS), and a cutoff of five is used to optimally distinguish patients with and without MICS. However, this tool is still invasive and inconvenient, because it combines medical records, physical examination, and laboratory results. These steps require clinicians and limit MIS usage on a regular basis. Cerebral diseases in ESRD patients can be evaluated reliably and conveniently by using quantitative electroencephalogram (QEEG), which possibly reflects the severity of MICS likewise. Given the links between kidney and brain abnormalities, we hypothesized that some QEEG patterns might be associated with the severity of MICS and could be used to distinguish ESRD patients with and without MICS. Hence, we recruited 62 ESRD participants and divided them into two subgroups: ESRD with MICS (17 women (59%), age 60.31 ± 7.79 years, MIS < 5) and ESRD without MICS (20 women (61%), age 62.03 ± 9.29 years, MIS ≥ 5). These participants willingly participated in MIS and QEEG assessments. We found that MICS-related factors may alter QEEG characteristics, including the absolute power of the delta, theta, and beta 1 bands, the relative power of the theta and beta 3 subbands, the coherence of the delta and theta bands, and the amplitude asymmetry of the beta 1 band, in certain brain regions. Although most of these QEEG patterns are significantly correlated with MIS, the delta absolute power, beta 1 amplitude asymmetry, and theta coherence are the optimal inputs for the logistic regression model, which can accurately classify ESRD patients with and without MICS (90.0 ± 5.7% area under the receiver operating characteristic curve). We suggest that these QEEG features can be used not only to evaluate the severity of cerebral disorders in ESRD patients but also to noninvasively monitor MICS in clinical practice.

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Quantitative EEG in the neonatal intensive care unit: Current application and future promise

Keene,

Benedetti,

Tomko

et al. 2023

Annals of the Child Neurology Society

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ImportanceQuantitative electroencephalography (qEEG) has been used in the neonatal intensive care unit (NICU) for several decades. Recent innovations have led to renewed interest in expanding its role in the NICU with the goal of improving both acute care of neonates in the NICU and longer‐term outcomes.ObservationsEEG in the NICU is primarily used to identify neonatal seizures. Sophisticated analysis of EEG can detect other acute neurological emergencies and provide additional information about short‐ and long‐term neurodevelopmental and epileptic prognosis. Using EEG for these additional findings may be limited by access to EEG resources and a constrained supply of neonatal neurophysiologists who can consistently evaluate unique neonatal EEG patterns.RelevanceQuantitative EEG analysis is a rapidly developing technology with the potential to augment and support the interpretation of neonatal EEGs. This review focuses on the status of qEEG use in the NICU for identification and prediction of seizures and use in neuroprognostication. It also examines areas of promise for bedside qEEG applications.

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Does relative or absolute EEG power have prognostic value in HIE setting?

Cited by 16 publications

References 4 publications

Prognostic Value of Continuous Electroencephalogram Delta Power in Neonates With Hypoxic-Ischemic Encephalopathy

Prognostic Value of Continuous Electroencephalogram Delta Power in Neonates With Hypoxic-Ischemic Encephalopathy

QEEG characteristics associated with malnutrition-inflammation complex syndrome

Quantitative EEG in the neonatal intensive care unit: Current application and future promise

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