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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]

none

Universal Trial Number (UTN)

Trial acronym

RESET child brain

Linked study record

none

Health condition

Health condition(s) or problem(s) studied:

seizure

coma

Condition category

Condition code

Neurological

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]

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]

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]

at the time of EEG recording

Primary outcome [2]

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]

at the time of EEG recording

Secondary outcome [1]

time to first seizure recognition per EEG recording - compare bedside clinicians interpreting QEEG and neurologists interpreting raw EEG

Timepoint [1]

12 months post-study commencement

Secondary outcome [2]

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]

12 months post study commencement

Secondary outcome [3]

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]

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?

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

Accrual to date

Final

Recruitment in Australia

Recruitment state(s)

QLD

Recruitment hospital [1]

Queensland Children's Hospital - South Brisbane

Recruitment postcode(s) [1]

4101 - South Brisbane

Funding & Sponsors

Funding source category [1]

Charities/Societies/Foundations

Name [1]

Children's Hospital Foundation

Address [1]

PO Box 8009 Woolloongabba, QLD 4102

Country [1]

Australia

Primary sponsor type

Hospital

Name

Queensland Children's Hospital

Address

41 Stanley Street, South Brisbane 4101 QLD

Country

Australia

Secondary sponsor category [1]

University

Name [1]

The University of Queensland

Address [1]

Level 4/5, Centre for Children’s Health Research
41 Stanley Street
Queensland Children’s Hospital
South Brisbane 4101 QLD

Country [1]

Australia

Ethics approval

Ethics application status

Approved

Ethics committee name [1]

children's health queensland human health service human research ethics comittee

Ethics committee address [1]

Level 7, Centre for Children’s Health Research
Queensland Children’s Hospital Precinct
62 Graham Street, South Brisbane QLD 4101

Ethics committee country [1]

Australia

Date submitted for ethics approval [1]

14/10/2019

Approval date [1]

20/11/2019

Ethics approval number [1]

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

Dr Michaela Waak

Address

Level 7, Centre for Children’s Health Research
41 Stanley Street
Queensland Children’s Hospital
South Brisbane 4101 QLD

Country

Australia

Phone

+61 730699000

Fax

[email protected]

Contact person for public queries

Name

Michaela Waak

Address

Level 7, Centre for Children’s Health Research
41 Stanley Street
Queensland Children’s Hospital
South BRisbane 4101 QLD

Country

Australia

Phone

+61 730681111

Fax

[email protected]

Contact person for scientific queries

Name

Michaela Waak

Address

Level 7, Centre for Children’s Health Research
41 Stanley Street
Queensland Children’s Hospital
South Brisbane 4101 QLD

Country

Australia

Phone

+61 730681111

Fax

[email protected]

Data sharing statement

Will individual participant data (IPD) for this trial be available (including data dictionaries)?

No/undecided IPD sharing reason/comment

What supporting documents are/will be available?

Doc. No.	Type	Citation	Link	Email	Other Details	Attachment
10685	Study protocol			[email protected]
10686	Ethical approval			[email protected]

Results publications and other study-related documents

Documents added manually

No documents have been uploaded by study researchers.

Documents added automatically

Source	Title	Year of Publication	DOI
Embase	Real-time seizure detection in paediatric intensive care patients: the RESET child brain protocol.	2022	https://dx.doi.org/10.1136/bmjopen-2021-059301

N.B. These documents automatically identified may not have been verified by the study sponsor.

Trial Review

Documents added manually

Documents added automatically