Detecting Non-convulsive Seizures in the Paediatric Intensive Care Unit

Study Overview
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Brief Summary
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The objective of this study is to determine if paediatric intensive care nurses and physicians can identify non-convulsive seizures in critically ill children using quantitative electroencephalography (EEG), in real time at the bedside. Quantitative EEG is a computer software tool which summarizes large volumes of brain wave electrical activity, called EEG into simple graphs and patterns. This has helped to shorten the EEG reading time.The study will also describe the neurological outcome of children monitored this way and assess if it's possible to use this approach. The investigators hypothesis is that paediatric intensive care nurses and physicians with focused training should be the first to identify non-convulsive seizures at the bedside using quantitative EEG, with reasonable accuracy and reliability. They should be able to confirm their findings with a neurologist to treat seizures quickly without over treatment. Due to the small numbers in this pilot study, the investigators are unlikely to be able to draw definitive conclusions on the clinical effects of this approach on the short- or long-term outcomes. This proof-of-concept study should, enable the investigators to assess if it's possible to use this method for a future multi-centre controlled study.

Detailed Description
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Overall Goals: The overall goals of this research are to: (i) determine the feasibility of studying another approach to the detection of non-convulsive seizures in the paediatric intensive care unit, (ii) determine if paediatric intensive care nurses and non-neurophysiologist critical-care physicians can accurately identify seizures in critically ill children by reading quantitative EEG trends, as well as the positive and negative predictive value and inter-rater reliability of this approach, (iii) explore children's short- and long-term neurological outcomes. Background: Non-convulsive seizures and non-convulsive status epilepticus are common in children with acute brain injury admitted to paediatric intensive care units. Electrographic seizure burden and status epilepticus contribute to neuronal injury, and worsen functional and quality of life outcomes. Accurate and timely diagnosis and treatment of non-convulsive seizures are essential in these critically ill children. Purpose: This exploratory study aims to: (i) enable the investigators, after proof of concept, to assess the feasibility of this method, (ii) determine the performance - in real time at the bedside of critically ill children - of caregivers other than neurologists to identify electrographical seizures, using panels of quantitative EEG trends, and (iii) describe the outcome of these children. Method: This pilot study will be a single-centre prospective open observational study. Thirty consecutive children who meet the specific criteria for continuous EEG in the paediatric intensive care unit at McMaster Children's Hospital will be eligible for enrolment. The paediatric intensive care nurse and resident or fellow will review the quantitative EEG trends to detect seizures at the bedside and complete the seizure log. This will be compared to the seizures detected on the raw EEG data read by the neurologist. Demographic data, baseline, short- and long-term (12-month) questionnaires of each child's global function, quality of life, seizures and brain behaviour will be completed to assess functional and quality of life outcomes. This will include a Seizure questionnaire, the Glasgow Outcome scale, the Paediatric Cerebral Performance Category score, the Paediatric Quality of Life Inventory, the Adaptive Behaviour Assessment System 3, the Child Behaviour Checklist and the Behaviour Rating Inventory of Executive Function 2. Expertise: The investigator team includes research experts in neurology, epilepsy, neurophysiology, developmental paediatrics, critical care and biostatistics. Significance: Due to the small numbers in this pilot study, the investigators are unlikely to be able to draw definitive conclusions on the clinical effects of this approach on the short- or long-term outcomes. This proof-of-concept study should enable the investigators to assess the feasibility of this method for a future multi-centre controlled study, which has the potential to revise and considerably improve the method of detecting non-convulsive seizures in the paediatric intensive care unit. If earlier detection and treatment of seizures in critically ill children are feasible, this should lead to improvements in short- and long-term neurological outcome and quality of life. These improvements may substantially benefit the person, family and society while reducing the burden placed on the health care system.

Official Title
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Detecting Non-convulsive Seizures in the Paediatric Intensive Care Unit: A Pilot Study of Another Approach

Conditions
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Non-convulsive Seizures

Intervention / Treatment
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* Device: Quantitative EEG and Seizure detector


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Infants and children (1 month - 18 years of age) Admission to McMaster Children's Hospital paediatric intensive care unit. Fulfill indications for Continuous EEG monitoring Informed consent received Exclusion Criteria: Suspected brain death

Ages Eligible for Study
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Minimum Age: 1 Month
Maximum Age: 18 Years

Sexes Eligible for Study
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All

Study Plan
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How is the study designed?
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Arms and Interventions

| Intervention/Treatment |
| --- |
|Device: Quantitative EEG and Seizure detector|Paediatric intensive care unit nurses, residents or fellows will perform hourly review of a bedside graphical display of the previous hour's epoch of quantitative EEG for seizure patterns. One page of quantitative EEG data represents one hour of recording. The graphical display will include a seizure-detection marker, seizure probability indicator, bilateral rhythmicity spectrogram and bilateral amplitude integrated EEG.|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Patient recruitment, | Will be analyzed based on descriptive statistics reported as an estimate of the 95 % confidence intervals. This feasibility study will be considered successful if the rates of recruitment, are 0.8 with 95% confidence intervals of +/- 0.14. | 2 years | 
| Data form completion | Will be analyzed based on descriptive statistics reported as an estimate of the 95 % confidence intervals. This feasibility study will be considered successful if the data collection, is 0.8 with 95% confidence intervals of +/- 0.14. | 2 years | 
| Equipment availability | Will be analyzed based on descriptive statistics reported as an estimate of the 95 % confidence intervals. This feasibility study will be considered successful if the equipment availability is 0.8 with 95% confidence intervals of +/- 0.14. | 2 years | 
| Study completion | Will be analyzed based on descriptive statistics reported as an estimate of the 95 % confidence intervals. This feasibility study will be considered successful if the study-completion is 0.8 with 95% confidence intervals of +/- 0.14. | 2 years | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Sensitivity | The Sensitivity of quantitative electroencephalography read by intensive care nurses and non-neurology expert physicians - to detect electrographical seizures in the paediatric intensive care unit will be estimated against the standard method of seizure detection currently used by neurology experts with continuous electroencephalography. | 2 years | 
| Specificity | The Specificity of quantitative electroencephalography read by intensive care nurses and non-neurology expert physicians - to detect electrographical seizures in the paediatric intensive care unit will be estimated against the standard method of seizure detection currently used by neurology experts with continuous electroencephalography. | 2 years | 
| Positive predictive value | The positive predictive value of quantitative electroencephalography read by intensive care nurses and non-neurology expert physicians - to detect electrographical seizures in the paediatric intensive care unit will be estimated against the standard method of seizure detection currently used by neurology experts with continuous electroencephalography. | 2 years | 
| Negative predictive value | The negative predictive value of quantitative electroencephalography read by intensive care nurses and non-neurology expert physicians - to detect electrographical seizures in the paediatric intensive care unit will be estimated against the standard method of seizure detection currently used by neurology experts with continuous electroencephalography. | 2 years | 
| Mortality | The outcome of mortality, will be analyzed descriptively. | 1 year | 
| Glasgow Outcome scale | Higher values represent a worse outcome: 8 - Death, 7 - Vegetative State (VS), 6 - Lower Severe Disability (Lower SD), 5 - Upper Severe Disability (Upper SD), 4 - Lower Moderate Disability (Lower MD), 3 - Upper Moderate Disability (Upper MD), 2 - Lower Good Recovery (Lower GR) 1 - Upper Good Recovery (Upper GR). Will be analyzed descriptively. Estimations will be made with 95% confidence intervals. | 1 year | 
| Pediatric Cerebral Performance Category score, | Higher values represent a worse outcome: Normal -1 Mild disability -2 Moderate disability -3 Severe disability -4 Coma and vegetative state -5 Death -6. Will be analyzed descriptively. Estimations will be made with 95% confidence intervals. | 1 year | 
| Pediatric Quality of Life Inventory | Will be analyzed descriptively. Estimations will be made with 95% confidence intervals | 1 year | 
| Adaptive Behaviour Assessment System III, | Will be analyzed descriptively. Estimations will be made with 95% confidence intervals | 1 year | 
| Child Behaviour Checklist | Will be analyzed descriptively. Estimations will be made with 95% confidence intervals | 1year | 
| Behaviour Rating Inventory of Executive Function II | Will be analyzed descriptively. Estimations will be made with 95% confidence intervals | 1 year |