Quantitative Continuous EEG: Bridging the Gap Between the ICU Bedside and the EEG Interpreter

Kramer, Andreas H.; Kromm, Julie

doi:10.1007/s12028-019-00694-8

Cited by 12 publications

(6 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…7,8 And on the other hand, other studies have demonstrated that qEEG is a valid and reliable indicator of brain function relevant to many conditions and disorders. 9,10 However, despite the ongoing debate, we have seen a surge in the clinical use of qEEG in the last two decades, such as continuous EEG in critically ill patients in Intensive Care Units 11–13 .…”

Section: Introductionmentioning

confidence: 99%

Assessment of Classical and Non-Classical Quantitative Electroencephalographic Measures in Patients with Substance Use Disorders

Guerrero-Aranda,

Alvarado-Rodríguez,

Enríquez-Zaragoza

et al. 2023

Clin EEG Neurosci

View full text Add to dashboard Cite

Background: People diagnosed with substance use disorders (SUDs) are at risk for impairment of brain function and structure. However, physicians still do not have any clinical biomarker of brain impairment that helps diagnose or treat these patients when needed. The most common method to study these patients is the classical electroencephalographic (EEG) analyses of absolute and relative powers, but this has limited individual clinical applicability. Other non-classical measures such as frequency band ratios and entropy show promise in these patients. Therefore, there is a need to expand the use of quantitative (q)EEG beyond classical measures in clinical populations. Our aim is to assess a group of classical and non-classical qEEG measures in a population with SUDs. Methods: We selected 56 non-medicated and drug-free adult patients (30 males) diagnosed with SUDs and admitted to Rehabilitation Clinics. According to qualitative EEG findings, patients were divided into four groups. We estimated the absolute and relative powers and calculated the entropy, and the alpha/(delta + theta) ratio. Results: Our findings showed a significant variability of absolute and relative powers among patients with SUDs. We also observed a decrease in the EEG-based entropy index and alpha/(theta + delta) ratio, mainly in posterior regions, in the patients with abnormal qualitative EEG. Conclusions: Our findings support the view that the power spectrum is not a reliable biomarker on an individual level. Thus, we suggest shifting the approach from the power spectrum toward other potential methods and designs that may offer greater clinical possibilities.

show abstract

Section: Introductionmentioning

confidence: 99%

Assessment of Classical and Non-Classical Quantitative Electroencephalographic Measures in Patients with Substance Use Disorders

Guerrero-Aranda,

Alvarado-Rodríguez,

Enríquez-Zaragoza

et al. 2023

Clin EEG Neurosci

View full text Add to dashboard Cite

show abstract

“…Quantitative EEG analysis (qEEG) involves applying mathematical techniques to time series data to reveal, or extract, information that may not be readily apparent to the human eye. In recent years, qEEG has proven to be a valuable tool in various clinical contexts (Kramer and Kromm, 2019 ; Koberda, 2021 ; Tenney et al, 2021 ; Munjal et al, 2022 ). One widely used approach in clinical practice consists in analyzing spectral components by means of the classic measures that include absolute and relative power.…”

Section: Introductionmentioning

confidence: 99%

Quantitative EEG analysis in typical absence seizures: unveiling spectral dynamics and entropy patterns

Guerrero-Aranda,

Ramírez-Ponce,

Ramos-Quezada

et al. 2023

Front. Hum. Neurosci.

View full text Add to dashboard Cite

A typical absence seizure is a generalized epileptic event characterized by a sudden, brief alteration of consciousness that serves as a hallmark for various generalized epilepsy syndromes. Distinguishing between similar interictal and ictal electroencephalographic (EEG) epileptiform patterns poses a challenge. However, quantitative EEG, particularly spectral analysis focused on EEG rhythms, shows potential for differentiation. This study was designed to investigate discernible differences in EEG spectral dynamics and entropy patterns during the pre-ictal and post-ictal periods compared to the interictal state. We analyzed 20 EEG ictal patterns from 11 patients with confirmed typical absence seizures, and assessed recordings made during the pre-ictal, post-ictal, and interictal intervals. Power spectral density (PSD) was used for the quantitative analysis that focused on the delta, theta, alpha, and beta bands. In addition, we measured EEG signal regularity using approximate (ApEn) and multi-scale sample entropy (MSE). Findings demonstrate a significant increase in delta and theta power in the pre-ictal and post-ictal intervals compared to the interictal interval, especially in the posterior brain region. We also observed a notable decrease in entropy in the pre-ictal and post-ictal intervals, with a more pronounced effect in anterior brain regions. These results provide valuable information that can potentially aid in differentiating epileptiform patterns in typical absence seizures. The implications of our findings are promising for precision medicine approaches to epilepsy diagnoses and patient management. In conclusion, our quantitative analysis of EEG data suggests that PSD and entropy measures hold promise as potential biomarkers for distinguishing ictal from interictal epileptiform patterns in patients with confirmed or suspected typical absence seizures.

show abstract

“… 49 Provision of robust education and training components and inclusion of all PICU patients requiring cEEG for seizure detection have been identified as priorities. 49 …”

Section: Introductionmentioning

confidence: 99%

“…They have not been evaluated for real-time seizure detection in comatose critically ill children. Prospective studies testing QEEG in the point-of-care context to improve external validity have been suggested 49. Provision of robust education and training components and inclusion of all PICU patients requiring cEEG for seizure detection have been identified as priorities 49…”

Section: Introductionmentioning

confidence: 99%

Real-time seizure detection in paediatric intensive care patients: the RESET child brain protocol

et al. 2022

View full text Add to dashboard Cite

IntroductionApproximately 20%–40% of comatose children with risk factors in intensive care have electrographic-only seizures; these go unrecognised due to the absence of continuous electroencephalography (EEG) monitoring (cEEG). Utility of cEEG with high-quality assessment is currently limited due to high-resource requirements. New software analysis tools are available to facilitate bedside cEEG assessment using quantitative EEG (QEEG) trends. The primary aim of this study is to describe accuracy of interpretation of QEEG trends by paediatric intensive care unit (PICU) nurses compared with cEEG assessment by neurologist (standard clinical care) in children at risk of seizures and status epilepticus utilising diagnostic test statistics. The secondary aims are to determine time to seizure detection for QEEG users compared with standard clinical care and describe impact of confounders on accuracy of seizure detection.Methods and analysisThis will be a single-centre, prospective observational cohort study evaluating a paediatric QEEG programme utilising the full 19 electrode set. The setting will be a 36-bed quaternary PICU with medical, cardiac and general surgical cases. cEEG studies in PICU patients identified as ‘at risk of seizures’ will be analysed. Trained bedside clinical nurses will interpret the QEEG. Seizure events will be marked as seizures if >3 QEEG criteria occur. Post-hoc dedicated neurologists, who remain blinded to the QEEG analysis, will interpret the cEEG. Determination of standard test characteristics will assess the primary hypothesis. To calculate 95% (CIs) around the sensitivity and specificity estimates with a CI width of 10%, the sample size needed for sensitivity is 80 patients assuming each EEG will have approximately 9 to 18 1-hour epochs.Ethics and disseminationThe study has received approval by the Children’s Health Queensland Human Research Ethics Committee (HREC/19/QCHQ/58145). Results will be made available to the funders, critical care survivors and their caregivers, the relevant societies, and other researchers.Trial registration numberAustralian New Zealand Clinical Trials Registry (ANZCTR) 12621001471875.

show abstract

Quantitative Continuous EEG: Bridging the Gap Between the ICU Bedside and the EEG Interpreter

Cited by 12 publications

References 23 publications

Assessment of Classical and Non-Classical Quantitative Electroencephalographic Measures in Patients with Substance Use Disorders

Assessment of Classical and Non-Classical Quantitative Electroencephalographic Measures in Patients with Substance Use Disorders

Quantitative EEG analysis in typical absence seizures: unveiling spectral dynamics and entropy patterns

Real-time seizure detection in paediatric intensive care patients: the RESET child brain protocol

Contact Info

Product

Resources

About