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Real-time seizure detection in paediatric intensive care patients: the RESET child brain protocol
INTRODUCTION: Approximately 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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9171209/ https://www.ncbi.nlm.nih.gov/pubmed/36691237 http://dx.doi.org/10.1136/bmjopen-2021-059301 |
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author | Waak, Michaela Gibbons, Kristen Sparkes, Louise Harnischfeger, Jane Gurr, Sandra Schibler, Andreas Slater, Anthony Malone, Stephen |
author_facet | Waak, Michaela Gibbons, Kristen Sparkes, Louise Harnischfeger, Jane Gurr, Sandra Schibler, Andreas Slater, Anthony Malone, Stephen |
author_sort | Waak, Michaela |
collection | PubMed |
description | INTRODUCTION: Approximately 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 ANALYSIS: This 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 DISSEMINATION: The 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 NUMBER: Australian New Zealand Clinical Trials Registry (ANZCTR) 12621001471875. |
format | Online Article Text |
id | pubmed-9171209 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-91712092022-06-16 Real-time seizure detection in paediatric intensive care patients: the RESET child brain protocol Waak, Michaela Gibbons, Kristen Sparkes, Louise Harnischfeger, Jane Gurr, Sandra Schibler, Andreas Slater, Anthony Malone, Stephen BMJ Open Intensive Care INTRODUCTION: Approximately 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 ANALYSIS: This 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 DISSEMINATION: The 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 NUMBER: Australian New Zealand Clinical Trials Registry (ANZCTR) 12621001471875. BMJ Publishing Group 2022-06-03 /pmc/articles/PMC9171209/ /pubmed/36691237 http://dx.doi.org/10.1136/bmjopen-2021-059301 Text en © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Intensive Care Waak, Michaela Gibbons, Kristen Sparkes, Louise Harnischfeger, Jane Gurr, Sandra Schibler, Andreas Slater, Anthony Malone, Stephen Real-time seizure detection in paediatric intensive care patients: the RESET child brain protocol |
title | Real-time seizure detection in paediatric intensive care patients: the RESET child brain protocol |
title_full | Real-time seizure detection in paediatric intensive care patients: the RESET child brain protocol |
title_fullStr | Real-time seizure detection in paediatric intensive care patients: the RESET child brain protocol |
title_full_unstemmed | Real-time seizure detection in paediatric intensive care patients: the RESET child brain protocol |
title_short | Real-time seizure detection in paediatric intensive care patients: the RESET child brain protocol |
title_sort | real-time seizure detection in paediatric intensive care patients: the reset child brain protocol |
topic | Intensive Care |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9171209/ https://www.ncbi.nlm.nih.gov/pubmed/36691237 http://dx.doi.org/10.1136/bmjopen-2021-059301 |
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