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Trial registered on ANZCTR


Registration number
ACTRN12621001471875
Ethics application status
Approved
Date submitted
15/02/2021
Date registered
27/10/2021
Date last updated
27/10/2021
Date data sharing statement initially provided
27/10/2021
Type of registration
Retrospectively registered

Titles & IDs
Public title
Real time seizure detection in Paediatric Intensive Care patients (RESET child brain)
– evaluation of the first quantitative electroencephalography program utilising the full 16 electrode set
Scientific title
Real time seizure detection in Paediatric Intensive Care patients (RESET child brain)
– evaluation of the first quantitative electroencephalography program assessing accuracy of PICU clinicians recognising seizures
Secondary ID [1] 303459 0
none
Universal Trial Number (UTN)
Trial acronym
RESET child brain
Linked study record
none

Health condition
Health condition(s) or problem(s) studied:
seizure
 320767 0
coma 320768 0
Condition category
Condition code
Neurological 318595 318595 0 0
Other neurological disorders

Intervention/exposure
Study type
Observational
Patient registry
False
Target follow-up duration
Target follow-up type
Description of intervention(s) / exposure
exposure: QEEG (quantitative software analysis tools now available to facilitate bedside EEG assessment)
condition observed: seizures
participants: children (less then 18 years) admitted to PICU in coma and at risk of seizures
observation: EEG performed as per standard clinical practice, duration determined by managing clinicians (but will be at least 1 hour) - QEEG software used and interpreted by bedside clinician
Intervention code [1] 319751 0
Diagnosis / Prognosis
Comparator / control treatment
QEEG interpreted by bedside clinicians will be compared to 'gold standard of neurologists interpreting raw EEG data
control group is the study neurologists interpreting the cEEG
Control group
Active

Outcomes
Primary outcome [1] 326553 0
Accuracy of nurses interpreting QEEG for identification of seizures will be assessed using sensitivity, specificity, positive predictive value and negative predictive value, comparing to conventional cEEG review by neurologists as the gold standard. Ninety-five percent confidence intervals (CI) will be reported for each performance measure. The following definitions will be used for the components required for calculation of these statistics:
Seizure
• True negative: No seizure event/s recorded on QEEG within the one-hour epoch, with no seizure event/s recorded on cEEG for the same time period
• False negative: No seizure event within the one-hour QEEG epoch, with one or more seizure event/s recorded on cEEG for the same time period
• False positive: Seizure event recorded on QEEG with no seizure event on cEEG within a five minute interval
• True positive: Seizure event recorded on QEEG within five minutes of a seizure on cEEG
Timepoint [1] 326553 0
at the time of EEG recording
Primary outcome [2] 329363 0
Accuracy of nurses interpreting QEEG for identification of status epilepticus will be assessed using sensitivity, specificity, positive predictive value and negative predictive value, comparing to conventional cEEG review by neurologists as the gold standard. Ninety-five percent confidence intervals (CI) will be reported for each performance measure. The following definitions will be used for the components required for calculation of these statistics:

Status epilepticus
True negative: No status event/s recorded on QEEG within a one-hour epoch, with no status event/s recorded on cEEG for the same time period
• False negative: No status event within a one-hour QEEG epoch, with one or more seizure event/s recorded on cEEG for the same time period
• False positive: status event recorded on QEEG with no status event on cEEG within a one-hour interval
• True positive: status event recorded on QEEG within one hour of a status event on cEEG
Timepoint [2] 329363 0
at the time of EEG recording
Secondary outcome [1] 391854 0
time to first seizure recognition per EEG recording - compare bedside clinicians interpreting QEEG and neurologists interpreting raw EEG
Timepoint [1] 391854 0
12 months post-study commencement
Secondary outcome [2] 401552 0
compare QEEG experts (EEG technician and/or neurologist blinded to raw EEG data) interpretation of QEEG offline and neurologists interpreting raw EEG. Interrater reliability for seizure detection for bedside clinician reviewing QEEG in real-time and offline review of QEEG by experts will be calculated.
Seizure
• True negative: No seizure event/s recorded on QEEG within the one-hour epoch, with no seizure event/s recorded on cEEG for the same time period
• False negative: No seizure event within the one-hour QEEG epoch, with one or more seizure event/s recorded on cEEG for the same time period
• False positive: Seizure event recorded on QEEG with no seizure event on cEEG within a five minute interval
• True positive: Seizure event recorded on QEEG within five minutes of a seizure on cEEG
Timepoint [2] 401552 0
12 months post study commencement
Secondary outcome [3] 402330 0
compare QEEG experts (EEG technician and/or neurologist blinded to raw EEG data) interpretation of QEEG offline and neurologists interpreting raw EEG. Interrater reliability for status detection for bedside clinician reviewing QEEG in real-time and offline review of QEEG by experts will be calculated.
Status epilepticus
True negative: No status event/s recorded on QEEG within a one-hour epoch, with no status event/s recorded on cEEG for the same time period
• False negative: No status event within a one-hour QEEG epoch, with one or more seizure event/s recorded on cEEG for the same time period
• False positive: status event recorded on QEEG with no status event on cEEG within a one-hour interval
• True positive: status event recorded on QEEG within one hour of a status event on cEEG
Timepoint [3] 402330 0
12 months post study commencement

Eligibility
Key inclusion criteria
EEG recording > /= 1 hour
< /= 18 years of age
Admission to study PICU
identified as at risk of seizures (defined as brain injury and unexplained coma or unable to assess clinically)
Minimum age
0 Days
Maximum age
18 Years
Sex
Both males and females
Can healthy volunteers participate?
No
Key exclusion criteria
Recording < 1 hour
Patients with decompressive craniectomy or injury to head that prevents from placing electrodes
Allergy to collodion glue

Study design
Purpose
Screening
Duration
Cross-sectional
Selection
Convenience sample
Timing
Prospective
Statistical methods / analysis
Sample size analysis
There is no validated and comparable data available. Based on the results of Kang et al (Kang JH, Sherill GC, Sinha SR, Swisher CB. A Trial of Real-Time Electrographic Seizure Detection by Neuro-ICU Nurses Using a Panel of Quantitative EEG Trends. Neurocrit Care. 2019. doi:10.1007/s12028-019-00673-z ), it is assumed that 30% of one-hour epochs will have one or more seizures present, sensitivity for detecting seizures will be approximately 85% and specificity of detecting seizures will be approximately 90%. To calculate 95% confidence intervals around the sensitivity and specificity estimates with a confidence interval width of 10%, the sample size needed for sensitivity is 717 one-hour epochs and 226 for specificity. On average, each EEG will have approximately 9-18 one-hour epochs, therefore 80 participants will be recruited. To allow a 15% attrition rate, our sampling period of one year will achieve recruitment of 100 children. This relatively large sample will allow an in-depth analysis of the methods considering the relatively large heterogeneity of the study population.
Independent EEG and QEEG assessors will be blinded to nursing assessments and patient details.
Standard test characteristics (sensitivity, specificity, positive predictive value, negative predictive value, and error rates) will be calculated for ability of the nurses/practitioners to detect the presence of seizures compared to conventional cEEG review by neurologists and/or neurophysiologists. Ninety-five percent confidence intervals (CI) will be reported for each performance measure. The responses that included 1–2 seizures, 3–5 seizures, 6–10 seizures, and > 10 seizures will be grouped as seizures being present for analyses that assesses for the presence or absence of seizures. Interrater reliability for seizure detection for the neurologist/neurophysiologist reviewing the conventional cEEG will be calculated.
Contingency analysis will be used to make comparisons of the mean diagnostic accuracy of seizure detection of the nurses by qEEG for seizures of different spatial extent (focal vs. hemispheric vs generalized/bilateral) and duration (< 1 vs. 1–5 min).
Chi-square statistics will be calculated for each of these analyses.
The accuracy of seizure detection by bedside PICU nurses will be determined by their ability to classify patients in ‘seizures present’ or ‘seizure absent’ categories compared to the reference Standard – epileptology assessment of EEG. The resulting numbers will be used to calculate the number of true positives, false positives, true negatives and false negatives using two by two tables. Criterion validity will be evaluated by calculating sensitivity, specificity, positive predictive value and negative predictive value. Accuracy of the Index tests will be derived from the area under the curve (AUC) using Receiver Operator Characteristic (ROC) curves. For all calculations, a p value < 0.05 will be considered statistically significant.
Subgroup analysis will be performed. Sensitivity and specificity of PICU neurocritical care nurses/practitioners determining clinical and subclinical seizure occurrence and non-convulsive status epileptics utilising QEEG trends in each 1-hour EEG epoch will be compared between:
• patients who have had a seizure confirmed on raw EEG by a neurologist and the relevant QEEG section printed for comparison, AND
• patients who did not have a seizure confirmed prior to the bedside nurse scoring the EEG.

A further comparison will occur for:
• patients who did have at least one real seizure confirmed on raw EEG by the neurologist in the final analysis, AND
• patients who did not have seizures during the EEG recording.

Time to seizure recognition will be recorded for QEEG review and will be compared to standard practice (EEG review).

Recruitment
Recruitment status
Recruiting
Date of first participant enrolment
Anticipated
Actual
27/11/2020
Date of last participant enrolment
Anticipated
31/03/2024
Actual
Date of last data collection
Anticipated
28/02/2025
Actual
Sample size
Target
80
Accrual to date
5
Final
Recruitment in Australia
Recruitment state(s)
QLD
Recruitment hospital [1] 18722 0
Queensland Children's Hospital - South Brisbane
Recruitment postcode(s) [1] 33164 0
4101 - South Brisbane

Funding & Sponsors
Funding source category [1] 307877 0
Charities/Societies/Foundations
Name [1] 307877 0
Children's Hospital Foundation
Country [1] 307877 0
Australia
Primary sponsor type
Hospital
Name
Queensland Children's Hospital
Address
41 Stanley Street, South Brisbane 4101 QLD
Country
Australia
Secondary sponsor category [1] 308588 0
University
Name [1] 308588 0
The University of Queensland
Address [1] 308588 0
Level 4/5, Centre for Children’s Health Research
41 Stanley Street
Queensland Children’s Hospital
South Brisbane 4101 QLD
Country [1] 308588 0
Australia

Ethics approval
Ethics application status
Approved
Ethics committee name [1] 307878 0
children's health queensland human health service human research ethics comittee
Ethics committee address [1] 307878 0
Level 7, Centre for Children’s Health Research
Queensland Children’s Hospital Precinct
62 Graham Street, South Brisbane QLD 4101
Ethics committee country [1] 307878 0
Australia
Date submitted for ethics approval [1] 307878 0
14/10/2019
Approval date [1] 307878 0
20/11/2019
Ethics approval number [1] 307878 0
HREC/19/QCHQ/58145

Summary
Brief summary
Children with critical illnesses are at high risk (> 20%) of developing seizures and brain
injury. Each year, over 10,000 children in Australasia require paediatric critical care unit
(PICU) admission. Significant advances in PICU mean more severely ill and injured children
now survive, and subsequently go home to the community. However, these children remain at high risk of seizure.
Therefore, it is essential that continuous improvements are made that address survivorship
and morbidity, especially recognition of patients at risk and preventing further brain injury
by monitoring appropriately to save brain function.
The measuring of brain activity (electroencephalography/EEG) is the only available form of
monitoring brain currents in patients with suspected seizures. Seizures are often invisible
otherwise, as children often show no visible signs.
Despite improvements in the field, recognising these seizures at the bedside in a timely
way is not possible for the treating team. This can have serious effects (high risk of brain
dysfunction), and potentially add to long term poor outcome or even death.
We will perform a worldwide first cohort study to show that EEG monitoring using automated seizure detection software can lead to accurate and timely seizure detections by bedside clinicians..
Trial website
none
Trial related presentations / publications
none
Public notes

Contacts
Principal investigator
Name 108790 0
Dr Michaela Waak
Address 108790 0
Level 7, Centre for Children’s Health Research
41 Stanley Street
Queensland Children’s Hospital
South Brisbane 4101 QLD
Country 108790 0
Australia
Phone 108790 0
+61 730699000
Fax 108790 0
Email 108790 0
[email protected]
Contact person for public queries
Name 108791 0
Michaela Waak
Address 108791 0
Level 7, Centre for Children’s Health Research
41 Stanley Street
Queensland Children’s Hospital
South BRisbane 4101 QLD
Country 108791 0
Australia
Phone 108791 0
+61 730681111
Fax 108791 0
Email 108791 0
[email protected]
Contact person for scientific queries
Name 108792 0
Michaela Waak
Address 108792 0
Level 7, Centre for Children’s Health Research
41 Stanley Street
Queensland Children’s Hospital
South Brisbane 4101 QLD
Country 108792 0
Australia
Phone 108792 0
+61 730681111
Fax 108792 0
Email 108792 0
[email protected]

Data sharing statement
Will individual participant data (IPD) for this trial be available (including data dictionaries)?
No
No/undecided IPD sharing reason/comment


What supporting documents are/will be available?

Doc. No.TypeCitationLinkEmailOther DetailsAttachment
10685Study protocol  [email protected]
10686Ethical approval  [email protected]



Results publications and other study-related documents

Documents added manually
No documents have been uploaded by study researchers.

Documents added automatically
SourceTitleYear of PublicationDOI
EmbaseReal-time seizure detection in paediatric intensive care patients: the RESET child brain protocol.2022https://dx.doi.org/10.1136/bmjopen-2021-059301
N.B. These documents automatically identified may not have been verified by the study sponsor.